Diagnostic Delay among New Smear Positive Pulmonary
Tuberculosis Patients in Amhara Region, Northwest Ethiopia:
A Two-Perspective Analysis
Solomon Abebe Yimer
Supervisors:
Professor Gunnar Bjune MD, PHD
CO - Supervisor
Associate Professor Getu Degu
University of Oslo
Faculty of Medicine
Department of General Practice and Community Medicine
Section for International Health
University of Oslo
June/2004
Thesis Submitted in Partial Fulfillment of the
Master of Philosophy Degree in International Community Health
Abstract
Delay in the diagnosis of tuberculosis (TB) causes more severe illness, more
complication and an increased period of infectivity in the community. A study in Amhara
region in 2001 showed that, among those who had history of cough of more than 3
weeks, only 30% visited the formal health care facilities. We hypothesized that there was
a significant patients’ and health systems’ delay in the diagnosis of pulmonary TB in
Amhara region, and this study was conducted to test our hypothesis.
Objectives: To determine and analyze the length and associated risk factors of patients’
health providers’ and health systems’ delay among new smear positive pulmonary TB
patients in Amhara region, Northwest Ethiopia.
Methods: Within the setting of government health care facilities in Amhara region, we
conducted a cross-sectional study from September 1 - December 31/2003. A total of 384
new smear positive pulmonary TB patients participated in the study. Patients were
interviewed on the same date of the diagnosis using a semi-structured questionnaire.
Result: The median total delay was 80 days (IQR 44-130 days) and the median patients’
delay was 30 days (IQR 15-90 days). Forty eight percent of the subjects delayed for more
than one month. The median health providers’ and health systems’ delays were 61 and 21
days, respectively. In logistics regression, home distance >10 Km to a medical provider
(adjusted odds ratio [ORadj] 3.81, 95% confidence interval [CI] 2.21-6.57) and selftreatment (adjusted odds ratio [ORadj] 1.69, 95% confidence interval [CI] 1.86-6.57)
were associated with patients’ delay. Prior attendance to a health post/clinic (adjusted
odds ratio [ORadj] 3.50, 95% confidence interval [CI] 1.86-6.57) and consulting private
medical providers (adjusted odds ratio [ORadj] 2.10, 95% confidence interval [CI] 1.183.71) were associated with increased health systems’ delay.
Conclusion: Delay in the diagnosis of pulmonary TB is unacceptably high in Amhara
region. The delay is primarily related to the health providers. Accessing a simple and
rapid diagnostic test for TB at the lowest health care facilities (health post/clinic) and
encouraging a dialogue among all health providers are imperative interventions to reduce
health systems’ delays. Besides these, due emphasis should be given to further
decentralization of DOTS to the periphery and increasing public awareness of the disease
among the population.
Acknowledgement
I would extremely like to thank the Norwegian Heart and Lung association (LHL) and the
Norwegian Agency for Development Cooperation (NORAD) for providing me the
financial support to conduct my study without which this project would not have been
realized.
My special thanks go to my main supervisor Professor Gunnar Bjune from the University
Oslo for his critical comments and supervision from developing the project proposal up
to writing up the final thesis. I would also like to thank my co-supervisor associate
professor Getu Degu, from the Gondar College of Medical Sciences in Ethiopia for his
advice to my project.
I am grateful to the Amhara Regional State Health Bureau and the health departments and
districts health offices in the region for their approval and coordination in conducting my
study under their responsibilities.
I sincerely appreciate the kind cooperation and contribution of all the patients who
participated in this study. I would like also to express my sincere apreciatiation to all my
data collectors namely; Geletaw Ayalew, Derib Asen, Mohammed Yesuf, Temesgen
Birara Mesele Damte, Birhanun Melak, Bogale Dememe, Ayalew Asen, Mekonnen
Amena, Azeb Tamirat, Abayinesh Alemu. Mahiteme Haile, Teshay Tarekegne, Asalif
Demissie, Firehiwot Kassa, Betelhem, Alem Faris, Assefa Ali for their time and patience
in interviewing patients.
My heartfelt thanks go to Mette Klouman and Jens Henning Rygh from Norway and Dr
Mohammed A/Rahim from Sudan for sharing ideas and valuable comments. I am also
proud to include the contribution Dr Fekadu Abebe, Ingvild Dalen, Dr M.G. Farah, Yosef
Abate, Alemu Kebede, Tesfaye Sisay, Dr Adane Bantayehu, Ayalew Endris, Getaneh
Derseh, Dr Abebe Eshetu, and Tamirat Assefa for their various supports to my project.
Finally, my deepest gratitude go to my parents, Abebe Yimer and Belayinesh Fantaw
back home for taking care of my children while I was attending my study for a long time
far away in Norway. I acknowledge the support and patience of my wife Engidawork
Tesfaye and my children Yimrha and Natnael Solomon. I would like to thank also my
brother Dereje Abebe, Biruk Haile and Birtukan Tesfaye from UK for their continuous
encouragement and material support.
Table of contents
Chapter one: Introduction
1.1 Country profile
1.1.1
Ethiopia………………………………………………………………………….1
1 1.2 Tuberculosis in
Ethiopia………………………………………………………...7
1.1.3 Background of the study area/Amhara
region…………………………………..8
1.1.4
Tuberculosis
in
Amhara
region………………………………………………...10
1.2 Back-ground and statement of the
problem…………………………………….13
1.3 Literature
Review…………………………………………………………………….15
1.3.1 Global burden of
tuberculosis……………………………………………….....15
1.3.3
Reasons
for
increase……………………………………....17
global
tuberculosis
1.3.4
The
global
tuberculosis
control………………………………………………...21
1.3.4.1
What
is
DOTS
strategy?
……………………………………………..21
1.3.4.2
Tuberculosis
case
detection…………………………………………..23
1.3.4.3
Tuberculosis
suspects
and
case
finding………………………………22
1.3.5
The
importance
of
diagnostic
delay
in
tuberculosis
control…………………....24
1.3.6
What
do
we
know
about
diagnostic
delays?
…………………………………...25
1.3.6.1
Differences
in
the
definition
of
diagnostic
delay…………………….25
1.3.6.2
Lengths
of
diagnostic
behind
diagnostic
delays…………………………………………26
1.3.6.3
Reasons
delays……………………………………26
1.4
Research
questions,
hypothesis
and
objectives
of
study……………….32
Chapter two: Subjects and methods
2.1 Study
area/setting………………………………………………………………...34
2.2 Study
design……………………………………………………………………...34
2.2
Population………………………………………………………………………..34
2.3 Sampling procedure and sample
size…………………………………………….35
the
2.4 Data collection
procedure………………………………………………………..35
2.4.1 Preparation for data
collection…………………………………………36
2.4.2 Data collection
method………………………………………………...36
2.4.2 Description of
data……………………………………………………..37
2.5.3
Variables……………………………………………………………….37
2.4.3.1. Definitions of main
variables………………………………………..38
2.4.4 Data
quality…………………………………………………………….40
2.5 Data
analysis……………………………………………………………………..40
2.6 Communication of
results………………………………………………………..41
2.7 Ethical
considerations……………………………………………………………42
Chapter three: The study results
3.1 Socio-demographic
characteristics……………………………………………………...43
3.2 Initial symptoms, perception of illness and first
action…………………………………47
3.3 Lengths and Associated risk factors of the different
delays…………………………….49
3.3.1. A. All health providers considered as a reference point……………………………..
50
3.3.1. A.1 The first health provider and the period of health
seeking………………50
3.3.1. A. 2 Health providers’
delay………………………………………………….51
3.3.1. B. Only medical providers considered as a reference
point………………………….54
3.3.1. B.1 Patients’
delay……………………………………………………………54
3.3.1. B.2 Medical providers’
delay………………………………………………...59
3.3.1. B.3 Health systems’ delay
…………………………………………………...63
3.3.6. B.4 Diagnosing facility’s delay
……………………………………………...68
3.3.7 Total
delay…………………………………………………………………….69
3.3.8 TB diagnosis in medical private
providers……………………………………75
3.3.9
Stigma………………………………………………………………………….75
Chapter four: Discussion
4.1 The distribution of the sample
population……………………………………………...77
4.2 The health seeking period and the health providers’
delay……………………………..77
4.3 Patients’
delay…………………………………………………………………………..78
4.4. Health systems’
delay…………………………………………………………………..81
4.5 Diagnosing facilitys’
delay……………………………………………………………...83
4.6 Total
delay………………………………………………………………………………84
4. 7 The role of knowledge, perception and behavior in diagnostic
delay………………….88
4.8 The contribution of the different health providers in diagnostic
delay…………………88
4.8.1 Drug retail
outlets……………………………………………………………..88
4.8.2 Traditional health care
providers……………………………………………...89
4.8.3 Private medical
providers……………………………………………………..90
4.8.4 Local
injectors………………………………………………………………...91
4.9 Strengths, weaknesses and limitations of the
study……………………………………..92
Chapter five: Conclusions and Recommendations
4.10
Conclusion…………………………………………………………………………….. 94
4.11
Recommendations……………………………………………………………………...94
4.12 Further research
implications…………………………………………………………..96
References
List of references
Appendices
List of appendices
Appendix 1.Questionnaire for patients
Appendix 2 Information about the research project
Appendix 3 Declaration of consent for the study
Appendix 4. Ethical approval document from the Regional Committee for Medical
Research
Ethics in Western Norway
Appendix 5. Ethical approval document from the National Ethical clearance Committee
in
Ethiopia.
Abbreviations
AFB
Acid fast bacilli
AIDS
Acquired immune deficiency syndrome
ANC
Ante-natal care
ANRNHRB
Amhara National Regional State Health
Bureau
BZHD
Bahirdar Zonal Health Department
CO
Central office
DOTS
Directly observed treatment short-course
Epi Info
Epidemiology Program Office
GNP
Gross national product
HIV
Human immunodeficiency virus
HIV/AIDS
Human immunodeficiency virus/acquired
immunodeficiency syndrome
IMR
Infant mortality rate
IEC
Information education communication
IUATLD
International Union Against Tuberculosis
and Lung Disease
MDT/DOT
Multi-drug therapy/directly observed
therapy
MDR-TB
Multi drug resistance tuberculosis
MOH
Ministry of Health
MMR
Maternal mortality rate
NTLCP
National Tuberculosis and Leprosy control
Program
PLHW
People living with HIV
RTLCP
Regional Tuberculosis and Leprosy control
Program
SPSS
Statistical package for the social sciences
TB
Tuberculosis
TBMU
Tuberculosis management units
TLCP
Tuberculosis and Leprosy Control Program
U5MR
Under five mortality rate
UNESCO
United Nations Educational Scientific and
Cultural Organization
UNHCR
United Nations Higher Commission for
refugees
UNICEF
United Nations Children Fund
WTLCP
Wereda Tuberculosis and Leprosy Control
Program
WHO
World Health Organization
ZTLCP
Zonal Tuberculosis and Leprosy Control
Program
Explanations of words with specific meanings and written version of
“Amharic “words frequently used in the text
Birr:
The Ethiopian national currency. At present, 1 Birr is equivalent to
USD 0.12 or NOK 0.90
Debtera:
An indigenous healer who receives his training from within the
church (only men can become debtera).
Dergue:
The former military government of Ethiopia that ruled the country
from
1974-1993.
Kebele:
The lowest administrative unit next to the woreda in the region
with
a population 3-5000.
Local injector:
An individual who practices administering injections to patients
presenting to him/her without prescription from a formal medical
provider. The procedure is usually performed behind closed door.
Nefas/Bird:
It is the” wind” which is believed to causes tuberculosis if one is
exposed to it.
Region:
A semi-autonomous state (political administrative body) next to
the central government of Ethiopia.
Sanba-nekersa:
Ethiopian word describing pulmonary tuberculosis.
Tsebel
Tsebel (holy water) are substances such as water, soil or ash,
which are blessed in the name of a particular saint
Woreda:
It is more or less equivalent to a district with a population ranging
from 90000-300000.
Zone
The second political administrative body next to the region with a
population ranging from 500,000-3, 000,000.
Chapter one: Introduction
1.1 Country profile (Ethiopia)
A. Demography
Ethiopia has an area of about 1 million square kilometers. The altitudinal
variation in Ethiopia ranges from below sea level to 4300m above sea level. This
offers numerous micro-climatic habitats ranging from tropical to near temperate
zones. This coupled with the fact that man has inhabited the Nile valley for
millennia could very well be the reason for the existence of several cultivated
plants whose origin is believed to be Ethiopia. These plants include the cereals:
Avena abyssinica (Ethiopian Oats) Elusine coracana (finger millets) and
Eragrostis tef (teff), the oil crops: Guizota abyssinica (noog), Ricinus cummis
(Castor oil plant), the starch plant: Enset ventricosum and the forage crop:
Cynods aethiopicum (star grass) and the drug and fatigue plant: Catha edulis
(chat) and Caffea arbica (coffee) (1).
Ethiopia is a country with a current population estimated at 67 million of which
more than 54 million (85.1%) live in rural areas. Ethiopia is one of the most
populous countries in Africa ranking third after Nigeria and Egypt. It is a multiethnic society with approximately 100 ethnic groups contributing their own
cultures and languages. The constitution of the Federal Democratic Republic of
Ethiopia established a federal system of government with nine regional states
and two city administrative councils. The role of the federal government is limited
to directing the countries fiscal, defense, and foreign affairs and articulating
economic and social policies and normative role in sectors of public services.
The state governments are empowered to design and operate region specific
programs and policies in the management of natural resources, primary and
secondary education, health services and the maintenance of internal law and
order (2).
B. Economy
The Ethiopian economy is classified into three categories: the agricultural sector
dominated by peasant agriculture, the live stock sector dominated by nomadic
pastorals and the modern sector which is in the process of coming into its own.
Over 85% of the labor force is engaged in the first two sectors. With rapid
population growth and the consequent rise of the population /land ratio, farm size
per household has been declining over the years. Thus landlessness, particularly
among the rural youth is becoming a serious problem. In fact, landlessness,
which is a function of demographic and environmental factors is the major
determinant of rural poverty. Among the consequences of landlessness is
increased migration of landless youth into nearby cities, placing considerable
pressure on urban social and economic services.
The Ethiopian government has adopted an Agricultural Development led
Industrialization (ADLI) policy and programs that recognize the interdependent
relationship between agricultural and industrial development. The policy is
directed to addressing the dual need for bringing about a relatively rapid
structural differentiation of the economy and for dealing with the problem of food
insecurity at both the household and societal levels. The problem of food
insecurity represents a serious developmental challenge. While efforts in
agricultural development are paying dividends in areas with abundant rainfall,
Ethiopia has seen little progress in rain deficient areas. The strategy adopted for
achieving a breakthrough in these difficult areas is to reduce dependence on
rainfall and achieving acreage under irrigation, and engage in agricultural
diversification (2).
C. The social sector
From the development point of view, the social sector is still week. National
Health Service coverage is at 51 percent from about 30 percent a decade ago.
The accelerated training of health professionals has yielded encouraging signs of
deployment of health professionals to rural areas. The health system’s weakness
lies primarily in its failure to bringing about behavioral change in the attitude of
Ethiopians toward personal and environmental hygiene
The education sector is undergoing rehabilitation. During most of the last
decades of the 20th century, enrollment remained practically at a standstill but it
has begun to increase since the turn of the current century. The new educational
policy is geared to producing an educated workforce that will forge a dynamic
economy. Ethiopia’s educational reorientation has led to greater emphasis on
technical and vocational education at the secondary level (2).
Table 1 Demographic and socio-economic characteristics, Ethiopia, 2002
______________________________________________________________
Indicators
Estimate
______________________________________________________________
Total population
67 million
Birth per 1,000 population
44
Deaths per 1,000 population
15
Rate of natural increase (percent)
2.9
Infant mortality rate (per 1,000 births)
97
Total fertility rate
5.9
Percent of population below age 15
Percent of population over age 65
44
3
Life expectancy at birth
52
Percent urban
15
Adult literacy rate
39.1
Percent of combined 1st, 2n and 3rd level gross enrollment (99)
27
Gross national product in US$
102
Percent of population not using clean water sources
76
Percent of children under five who are underweight
47
Percent population living under $ 1 a day
31.2
Percent of annual population growth between 2000 and 2005
2.4
Percent of population with health service coverage
Percent of population with access to essential drugs
51
50-79
______________________________________________________________
D. Health service in Ethiopia
Modern health service
More than 80% of the common diseases in Ethiopia are communicable (3). The
conventional health system is underdeveloped and able to provide health service
to about half of the population. Much of the rural population and a significant
portion of the urban population have no access to any type of modern health
care. There is an inability of the health care delivery system to respond
qualitatively or quantitatively to the health needs of the population (3).
In Ethiopia, there was no enunciated health policy until the fifties. Towards the
end of the imperial period a comprehensive health service policy was adopted
through initiatives from the WHO. However, the downfall of the regime precluded
the possibility of putting this scheme to the test (4). The Dergue regime that
came into power in the mid-seventies formulated a more elaborated health
policy, a policy that gave emphasis to disease prevention and control, priority to
rural areas in health service and promotion of self reliance and community
participation. This policy worked in a centralized system. After the over-through
of the Dergue regime in 1993, the new government adopted a new health policy,
which gave emphasis to decentralization and democratization of the health
service system (4).
According to the recent health policy, modern health service in Ethiopia should
be organized in a four-tier health care delivery system where there are primary
health care units with 5-satellite health posts, each serving a population of 5000
at the periphery, and with a national referral hospital at the top meant to serve 5
million people. In the middle there are district and zonal hospitals. However, the
new organization of health care delivery system is becoming hard to achieve as it
costs a lot of resources (4). Considering the overall national requirements and
the standard achieved in other countries, the available health infrastructures are
below the desired level. There is still only one hospital for 584,500 persons, one
health center for 272,400 persons and one health station for 22,800 persons (5).
E. Health expenditure and health outcome
Ethiopia has one of the worst health statuses in the world, and this is mainly due
to the deteriorating socio-economic situation resulting in a low standard of living,
poor environmental condition and inadequate health services. The need for an
expanded and more efficient health sector in Ethiopia is overwhelming. As a
proportion of gross-national product (GNP), Ethiopia’s public sector spending in
2001 (4.7%) was below the average for lowest income in Africa. In real terms this
translates into less than US$ 1 per capita, which places it near the bottom in
Africa (5).
Among its health outcomes, Ethiopia stands out as having some of the highest
levels of malnutrition (48% of children are underweight, 8% stunted, and 14%
wasted). The infant mortality rate is a valuable indicator of health and
development. Between 1998 and 2000, the infant mortality rate (IMR) reached
105/1000 live births and the under- five mortality rate (U5MR) accounted for
161/1000 live births. These figures are very high by world standards and Ethiopia
remains among the countries in the world continuously classified as very high
IMR and U5MR countries by United Nations Children’s Fund (UNICEF).
Ethiopia’s maternal mortality rate (MMR) estimated at 5.82 per 1000 live births is
significantly higher than all other developing countries (4).The present health
status of the Ethiopian population has generally been aggravated by a low percapita share of public health expenditure, thus, low absolute level of health
expenditure is clearly a constraint on health service delivery and in Ethiopia is far
below estimates of what a basic package of health services would cost (less than
US$ 13) (6).
F. Traditional medicine in Ethiopia
Traditional medicine is an age-old medical system practiced in all societies
differing in level of usage. For centuries Ethiopians relied heavily on a system of
health care containing both emperico-magical and magico-religious elements (1).
The indigenous health care system is as diverse as the cultural diversity and as
varied as the physical environment, which fosters unique flora, and fauna that are
often used as prime tools of the trade in the struggle against a variety of health
problems (1).
Indigenous medicine in Ethiopia is heavily influenced by religious beliefs. Many
of the cures that are used are derived from the Ethiopian Orthodox Church. While
most of the saints in the church have specific healing practices associated with
them, Mikael (for both men and women) and Mariam (for women) are probably
most famous for their power to heal. When a person becomes sick, his friends
and relatives may say to him, "Mikael must be with you. Mikael will protect you."
Likewise, Mariam is said to protect the health of women, especially during
childbirth. Even in cases where people seek bio-medical treatment, the eventual
outcome of the treatment, whether complete recovery, continued illness or death,
is often attributed to the will of the saint (7).
Religious basis of indigenous medicine uses tsebel (holy water) as a treatment
for various illnesses. Tsebel are substances such as water, soil or ash, which are
blessed in the name of a particular saint. They are used as prophylaxes and
treatments for a wide range of illnesses. In order for a tsebel to work, the sick
person must be a devout believer in its effectiveness. If the tsebel fails to cure or
protect against illness, the integrity of the patient's belief is challenged rather than
the efficiency of the tsebel.
One of the most powerful types of healers is the debtera, who receives his
training (for only men can become debtera) from within the church. Whereas
most indigenous healers' treatments are orally learned, practiced, and passed
on, the debtera's knowledge is derived from a series of texts written for the most
part in Ge'ez. These texts and the training that is necessary for their proper use
are accessible only to selected men who have already completed their training
for the priesthood (7).
The other categories of traditional healers include herbalists. These groups of
healers use plants to regulate organs, separate or expel the causative agents. More
than 50% of the healers are herbalists. There are also other categories of healers
including bone setters, uvula, and tonsil cutters, tooth extractors traditional birth
attendants, cuppers and tattooists (7).
As part of the community, traditional practitioners have over time developed very
close relationships with the population in which they live. Their communication
skills, easy access and spiritual healing have earned them respect and dignity
(7).
F. Traditional medicine and policy framework
The first recognition of the practice of traditional medicine in Ethiopia was made
in 1948 under the Medical Practitioners’ Registration Act (4). Recent policy
guidelines prepared by the government include the drug policy. According to the
guidelines of the policy (4):
1. Due attention shall be given to the development of beneficial aspects of
traditional medicine including related research and its gradual integration
into modern medicine
2. Traditional medicine shall be accorded appropriate attention by: Identifying
and encouraging utilization of its beneficial aspects, coordinating and
encouraging research including its linkage with modern medicine,
developing appropriate regulations and registration for its practice.
3. Facilitate the gradual integration of traditional drugs with modern medicine
by giving due attention to the traditional practices and identifying the
beneficial and harmful aspects through investigation and research.
4. Attention shall be given to strengthening the sector through research and
development. Research priorities shall be given to those traditional drugs
which are in wide use.
G. Integration of traditional medicine with bio-medicine
In Ethiopia, both indigenous traditional medical practice and conventional
medical practice are in operation and in most cases they conflict openly or
covertly. Biomedical professionals have been known to be among the people
who are very prejudiced against traditional healers and their medicine. There is
also unwillingness on the part of the traditional medical practitioners to share
their knowledge. Lack of recognition of traditional healers by the modern health
care providers creates resentment and insecurity in the traditional healers
leading to their alienation and isolation (9).
1.2 Tuberculosis (TB) in Ethiopia
According to the Ministry of health (MOH) hospital statistics data, TB is the
leading cause of morbidity, the third cause of hospital admission and the first
cause of hospital death in the country. It is estimated that there are about a
quarter of a million cases in the country and more than 40,000 persons die of TB
every year (3).
In Ethiopia, even though the effort to control TB was started in the early 1960s
with the establishment of TB centers and sanatoriums in three major urban
areas, there was practically no impact in reducing the toll of TB (10).
After the introduction of the concept of National TB Control Programs (NTCP) by
the World Health Organization (WHO), the MOH adopted this concept and
subsequently opened the central office (CO) of the NTCP in 1976. From its
conception, the CO had received neither sufficient budgetary nor manpower
allocations and thus remained virtually non-functional. It was in 1992 that a
standardized and well-organized TB control program incorporating Directly
Observed Treatment Short-course (DOTS) was implemented in a few areas of
the country. It has now reached a geographical coverage of 76 % of the entire
country (10)
In view of the remarkable achievements of the combined TB and Leprosy Control
Program (TLCP) achievements in other countries, it was decided to combine the
two programs in Ethiopia into the National TB and Leprosy Control Programs
(NTLCP). The combined program under the coordination and technical
leadership of the CO came into effect in 1994. The implementation of the
combined TLCP began in 1997 with the development of TLCP manual. Before
the inception of a TLCP in Ethiopia, little information was available about the
extent of the TB epidemic. A national survey which was conducted from 19871990 estimated the annual risk of infection to be 1.5% (10).
Currently, Ethiopia is one of the twenty-two high burden countries in the world
and the second to the top in Africa (10). In the year 2001, the TLCP registered
94,957 cases of TB from the DOTS implementing areas, among which 33,028
were new smear positive pulmonary TB cases (36% of the total new cases). This
represents a case notification rate of 173 and 60 per 100,000 populations for all
forms of TB and new smear-positive cases, respectively. The increase is
attributed to the expansion of DOTS in the country. By the end of the year 2001,
the DOTS program covered 56 zones in nine regions and two administrative
councils. Geographically, these zones represent 76% of the country, in which
about 55 million (85%) people live (10)
1.1.3 The study Area (Amhara region)
A. Demography
The Amhara regional state is the second largest region of the country. It is
located in the Northwestern part of the country and has a total surface area of
161, 828.4 Sq. kms (16% of the area of the country). The region shares
boundaries with Tigray in the north, Oromyia in the south and Benishanngul
Gumez in the west and Afar in the east. The topography of the region can be
divided into two main parts namely the low- land and the high-lands (1500 meter
above sea level). The highlands comprise the northern and eastern part of the
region while the low land is mainly located in the Northwestern part of the region
(11).
Based on the 1994 population census of the region, the population in 2003 was
estimated to be 17,740,521, out of which 8,880,262 (50.1%) were males and
8,860,259 (49.9%) were females. Among the total population of the region,
15,792,698 (89.02%) live in rural areas whereas the remaining 1,947,823
(10.98%) live in urban and suburban areas. Administratively, the region is divided
into 11 zones, 113 woredas and 3500 kebeles. The kebeles constitute the lowest
administrative unit within the woreda comprising an average population of 5000
inhabitants (11).
B. Socio-economic characteristics
The majority of the population lives below the poverty line. The housing condition
in the region is very poor. In most cases a single room is used for dwelling for the
entire family.
Especially in rural areas, people share the same room with
animals. The average household for rural areas is 5.5 and for urban areas is 4.5
while the total average household size for both areas is around 5. The
dependency ratio among the age group 15-64 years of age is found to be 110
dependents per 100 persons. There are significant numbers of homeless people
and street children. Currently their number is increasing at an alarming rate (11).
Subsistence agriculture is the backbone of the region’s rural economy. Crop and
live stock production are the major components of the agricultural sector.
Farming is mainly rain fed and undertaken by traditional methods. The region has
been exposed to repeated drought. On the other hand, the region possesses
many tourist attractions like the rock-hewn Churches in Lalibela, the castles of
Fasilledes and the Semein Mountains with its wild life. The United Nations
Educational, Scientific and Cultural Organization (UNESCO) as parts of the world
heritage has registered all of these. Moreover Lake Tana with its historical
monasteries and churches, the Tisabay waterfall in the Blue-Nile are other tourist
attractions in the region (11). With regards to communications, roads and air
travel are the main means of transportation. There is one international airport at
Bahirdar, which is the capital of the region. All weather roads cover
approximately 10.2 km per 1000 sq km. Telephone, postal services and
electricity are limited to the major towns of the region. The region has its own
regional radio station and a weekly newspaper. There are also additional
educational radio stations in 6 zones of the region (11).
C. Health services
More than 80% of the region’s health problems are attributed to communicable
diseases. According to the health and health related indicators of the region (11,
12), malaria, HIV/AIDS and TB are the major deadly diseases in the region. The
health service coverage is 41.1%, crude birth and death rates are estimated at
27.9 and18 /1000 live births, respectively. The prevalence of HIV among ANC
attendants in the year 2001 was 24%. There are 14 hospitals, 78 health centers
and 519 health posts currently active for the provision of health care to the
population. The private sector is also actively engaged in rendering health care.
In the region, there are 130 privately owned clinics with different levels, 40 drug
stores, and 256 rural drug venders. TB patients are diagnosed at private clinics
and referred to the government TB management units (TBMU) for the initiation of
anti -TB chemotherapy (11).
1.1.4 TB control program in Amhara region
A. Organization
Structurally, until the year 2000, the regional TB and leprosy control program
(RTLCP) was organized in the regional health bureau as a unit/section under the
communicable disease control team within the former health programs
department currently called as the disease prevention and control department. In
2001, the unit was upgraded to TB & Leprosy control and prevention team within
diseases prevention and control department. The team comprises 3 health
workers one team leader, senior expert (MD) and one RTLCP junior expert
(nurse). Currently the team has two health workers, namely one team leader
MD/MPH and one senior expert (MD) (13).
The regional health bureau has a responsibility to control and supervise the
Zonal Tuberculosis and Leprosy Control Program (ZTLCP) at zonal level, and the
ZTLC is at the same time responsible for controlling TB and all other
communicable diseases at the district level. Health officers in 72% of the zones
staff the ZTLCP. At woreda level, there is one woreda TB and leprosy control
(WTLC) expert on the malaria and other communicable diseases desk. However,
the position is filled in only some woredas. In the majority of the woredas, nurses
working at the TBMU in the health centers cover the position of the woreda TBLC
coordination work.
In 2002, TB was among the leading causes of morbidity and mortality in the
region. A total of 6553 smear positive new cases were diagnosed. And the case
detection rate was 41%. This was far less than the intended target of 70 %( 13).
The TB and Leprosy control team in the MOH supports the TB control program in
Amhara region technically and financially. The support includes among other
things, anti-TB drugs, laboratory supplies and other expenses for training and
review meetings. The regional health bureau also allocates budget for purchase
of supplementary drugs at regular bases.
B. Decentralization of DOTS in Amhara region
DOTS strategy is being implemented in the region. Health centers and hospitals
are serving as diagnostic and treatment units while clinics and health posts serve
as treatment units (13). According to the regional health bureau, in 2002, there
was a plan to decentralize the service to 65% of health units of the region. Each
woreda and zonal administration was expected to reach the target set by the
bureau by the end of the year. Accordingly, 4 zones achieved DOTS service
decentralization to >65% of health units. These zones were namely Waghemera
and Bahirdar 100% Oromia 75% and North Shewa 67%. However, the remaining
7 zones fail to achieve the target. Namely south Wollo 7.4%, north-Wollo 37%,
west-Gojjam 41%, south Gondar 44%, north Gondar 46%, east Gojjam 49.5%,
and Awie 52%.
The reasons, for not achieving the planned target at a regional level in 2002 and
in the above mentioned zones in particular were: the delay in releasing the
budget from the MOH, time limits due to different campaigns (polio, and measles)
and high turnover of health workers at different levels. Most importantly among
the 11 zonal coordinators, 8 of them either moved to other position or began their
postgraduate studies. The only 3 zones not affected were east Gojjam, Awi, and
north Gondar zones. But these zones were among the campaign areas of the
region. The bureau believed that, a combination of one or more factors as stated
above has resulted in inhibiting the decentralization process as it was planned to
achieve the target at district and zonal levels (10).
For 2004 the regional health bureau’s plan is to reach an overall DOTS coverage
of >85%. However, the bureau fears that the plan might not be achieved if
adequate resources are not released on time from the MOH to the region (10).
The regional health bureau also reported that it had encountered problems in the
already decentralized areas. The major problems encountered according to the
bureau were; poor recording and reporting, failure to send smear positive
pulmonary patients for follow up sputum examination, failure to send feedback on
the outcome of patients, directly observed treatment is not strictly observed as
health workers may at times leave for some days closing the clinic, shortage of
budget for collecting drugs/supplies from the WHO, lack of drugs monitoring and
management system, high turn over of staff and related consequences (13).
Quality control
The regional health bureau started quality control on AFB direct microscopy in
1998. However, due to several limitations the activity was on and off until 2000.
Since 2000 the regional health bureau has regularly been collecting slides from 6
zones. After 2nd rereading by the regional health and research laboratory,
discrepant slides are submitted to the central reference laboratory for the third rereading. During 1996 only one discrepant slide was sent to the central reference
laboratory. Based on the findings of the quality control on the slide, corrective
measures were taken by the regional health bureau (13).
1.2 Background information and statement of the
problem
TB is a chronic infectious disease caused in most cases by Mycobacterium
tuberculosis, an acid-fast rod-shaped bacillus. Occasionally, it can also be
caused by Mycobacterium bovis and Mycobacterium africanum. It is transmitted
by air and mainly affects the lungs (10).
TB is a leading public health problem worldwide particularly in the developing
countries. In view of the seriousness of the problem, WHO in 1993 declared it to
be a Global emergency. Of the 1.7 billion people estimated to be infected with
the TB bacillus, 1.3 billion live in developing countries. At the present time, it is
estimated that there are 16 to 20 million cases worldwide with 8.74 million new
cases every year. Two million of these people die every year. These constitute
26% of avoidable adult deaths worldwide (14).
Globally, the burden of TB is increasing at an alarming rate. Various factors
including poverty, population growth, migration and HIV/AIDS could be
contributing to maintaining for the continued threat of TB in the world. But a
significant problem lies with the fact that many cases remain undiagnosed (15).
This could be due to various factors, principally found within the categories:
patients delaying seeking health care or failure of the health care systems to
timely diagnose patients.
Delays in the diagnosis lead to an increased period of infectivity in the
community. It is estimated that an untreated smear positive patient may infect on
average more than 10 contacts annually and over 20 during the natural history of
the disease until death (16). Delayed diagnosis also causes patients to have
more severe disease, more complications and lead to higher mortality (16). This
hits families in the developing world very hard, particularly because younger
active productive age groups are the chief victims of the disease.
Delays in the diagnosis of TB have been reported in both industrialized and
developing countries and vary considerably, from 6.2 weeks in Australia (17) to
12 weeks in Botswana (18) and 16 weeks in Ghana (16). A number of factors
have been identified that appear to influence delay in diagnosis and
commencement of treatment. These include the individual’s perception of the
disease, the severity of the disease, access to health services, and the expertise
of health personnel (19).
In all delay studies conducted so far, conflicting reports exist on how patient
socio- economic characteristics, gender and the health services affect diagnostic
delay. Besides this, the already available information regarding diagnostic delay
has been evaluated to be inadequate at a consultative meeting that was held in
Geneva in 2000 (20).
Delay in diagnosis has been observed in Amhara region, North West Ethiopia.
An unpublished community based survey which was conducted in 2001, revealed
that, among those who showed the main symptoms of TB for more than 3 weeks,
only 30% visited the formal health care facilities (21). This might show that a
significant number of patients are not correctly diagnosed, or prefer to go to other
health providers, or fail to seek appropriate health care at an early stage of the
disease. Therefore, there was an urgent need to investigate this problem so as to
improve the case finding activities in the region. And hence the current study was
conducted.
In Ethiopia, two studies were conducted on delay in TB. One was conducted in
southern Ethiopia in a hospital setting (22) and another one in 1998, in the capital
city in a health center setting (23). Both studies assessed patients’ and health
system’s delays by taking diagnosing facilities as the first level of health care
contact for patients seeking health. The roles of other health providers were not
included in their studies. As the health service coverage in the country is very low
(<50%), a number of people use other options to get health care for their health
problems (3). These include the various categories of traditional health care
practitioners and others. Taking this reality into account, the current study has
managed to incorporate all health providers known to be potential venues for
patients seeking health. Therefore, considering the importance of implementation
research, which has an important role in increasing our knowledge of the factors
affecting diagnostic delay, this study was conducted to examine diagnostic delay
among smear positive pulmonary TB patients in Amhara region, Northwest
Ethiopia.
The researcher believes that, this study, by including all health providers as
potential venues for seeking health care has managed to collect relevant
information regarding the health seeking behavior, lengths and risk factors of
delay both from the patient and the provider side. It is hoped that, the regional TB
control program will use this information to improve the current low case
detection rate in the region.
1.3 Literature Review
1.3.1 Global burden of TB
Despite effective treatment, TB remains a major public health problem on a
global scale. Due to its frequency, its transmission pattern and its potential
effects, TB has significance to public health that exceeds most other diseases.
TB today may infect anyone by breathing in the air where a TB patient has
coughed, sneezed, talked or spat. Left untreated, each person with active TB will
infect on average between 10-15 people every year (24).
From the global perspective, TB is perhaps the greatest infectious killer of all
time. It is the seventh most important cause of mortality worldwide and the fourth
most important cause of death in developing regions. Over centuries, it has taken
over one billion lives (25). TB today is estimated to cause about 2 million deaths
and 8.74 million new cases yearly (26). TB causes more than 26% avoidable
adult (15-59 years of age) deaths in the developing world, which results in
tremendous social and economic costs. The WHO has identified 22 high burden
countries that account for 79% of all TB cases worldwide, and all of them are low
or middle-income countries (25).
According to the WHO, the NTCPs reported that, by the end of 2002, 69% of the
world’s population lived in countries, or parts of countries, covered by DOTS.
DOTS programs notified 3.0 million new cases, of which 1.4 million were smear
positive. A total of 13.3 million TB patients and 6.8 million smear-positive patients
were in DOTS programs between 1995 and 2002 (26).
The distribution of TB is very uneven in the world. Of the estimated 8.74 million
cases emerging globally each year, only 5 percent occur in the industrialized
countries. In these countries, the bulk of infected persons are found among the
elderly, while in most low-income countries, the large majority of infected persons
are in the economically most productive and reproductive age groups (27).
TB accounts for 8.4% of healthy years of life being lost among men and 7%
among women. The economic costs of TB in terms of lost production are
therefore considerable. Further studies show that TB is concentrated in lower
socio-economic groups, in households least able to cope with the burden (25).
Globally, the prevalence of infection is thought to be similar in males and
females. There is an estimated 2:1.1 male to female ratio of cases notified to
public health authority worldwide. However, the rate of developing active disease
from a primary infection with M. tuberculosis (progression rate) may be greater
among women of reproductive age than men of the same age (25). As the
leading infectious killer of youth and adults, TB kills more women than all causes
of maternal mortality combined (15).
From a public health perspective, TB is a high priority disease because of the
tremendous burden it imparts and the existence of interventions of proven
efficacy that are some of the most cost effective we have (28). Since 1994, WHO
has recommended and scaled up the TB control strategy, brand named as DOTS
(directly observed treatment short course). Other global initiatives, which have
recently emerged in response to the global TB crisis are stop TB, the Global
Alliance for TB Drug Development, the TB Diagnostic Initiative and the TB
Vaccine Initiative (25).
The goals of TB control are to reduce mortality, morbidity and transmission of the
disease, while preventing drug resistance, until TB no longer poses a threat to
public health. It also aims to reduce human suffering and the social and
economic burden families and communities have to bear as a consequence. To
achieve this, it is necessary to ensure access to diagnosis, treatment and cure
for each TB patient and to protect vulnerable populations from TB and its drugresistant forms (29).
2.2.2 Reasons for Global TB increase
A. Demography
TB is a disease concentrated in lower socio-economic groups, and increasing
economic inequalities together with population growth creates an increase in TB
cases. People’s life expectancy is also increasing and as a result, any increase in
resources has been absorbed by an increase in cases (30). Demographic factors
have played a major role in the global re-emergence of TB. Childhood mortality
rates have declined much more rapidly than birth rates over the past 30 years,
resulting in dramatic increase in the size of adolescents and young adult
population in the world. The population mostly of poor countries has increased.
The highest incidence of TB across the world is in central Africa and southern
Asia, particularly in India, where the population increase is known to be the most
rapid. Current annual population growth in these countries is about 100 million,
which means that global TB incidence in absolute numbers will continue to
increase by around 100.000 cases every year. In Ethiopia, the population is
rapidly increasing at a rate of 2.9% every year (31). This contributes to the
increased incidence of TB in the country.
B. TB and HIV
Factors associated with resurgence of TB in many countries include HIV
epidemic. Infection with HIV leads to extensive destruction of the immune
defense mechanisms of the body. As a result, those infected with HIV become ill
with severe and often deadly diseases to which persons without HIV infection
would not usually be susceptible (24). Throughout the industrialized and the
developing world, TB and HIV are closely linked in mutually disadvantageous
synergy: HIV infection promotes the progression of TB infection to disease, and
TB accelerates the course of HIV. HIV infection greatly increases the likelihood
that infection with M. tuberculosis, either recent or latent, will progress to active
TB. In fact, HIV infection may be the most potent risk factor for TB yet identified.
Conversely, TB is the most common cause of death in persons with HIV infection
in the world (24).
Globally, TB is the leading cause of HIV-related morbidity and mortality. In
developing countries, HIV-infected people run an annual risk of 5-15% of
developing TB. At least one in three people living with HIV (PLWH) will develop
TB (32). The escalating TB case rate over the past decade in sub-Saharan Africa
is largely attributable to the HIV epidemic (33). In 1997, the prevalence of M.
tuberculosis and HIV co-infection worldwide was 0.18% and 640,000 incident TB
cases (8%) had HIV infection. It was estimated that in the year 2000, the global
incidence of HIV-positive TB cases was 12 %. The number of people living with
TB and HIV co-infection was 16.3 million. Of the estimated 2 million TB deaths in
the world, about 0.5 million deaths were HIV- positive TB cases (32). SubSaharan Africa bears the highest burden of HIV positive TB cases followed by
south East Asia (32).
In Ethiopia, even though there are not many studies conducted to analyze the
impact of HIV on TB, few studies have documented that about 40% of adult TB
cases in urban areas are HIV-positive (10).
C. Poverty
Poverty has been strongly associated with the incidence of TB. Low socioeconomic indicators tend to result in crowded living conditions, conditions that
are conducive to increased transmission of tubercle bacilli should a case occur,
resulting thus in a generally higher prevalence of TB infection with subsequent
increased incidence of the disease. Poverty may also reduce access to health
care services, thus prolonging the period of infectiousness of TB patients and
further increasing the risk of infection among the contacts of such a patient (34).
Social and economic trends have contributed to the spread of TB. Over the past
10 years the number of less developed countries has doubled while GNP in
some middle-income countries has decreased. This has meant a decrease in the
availability of resources for TB control programs. Poverty, malnutrition and
overcrowding have for a long time been recognized as the main predisposing
factors for TB. It is estimated that about one third of the world’s population is
infected with TB but far from every body gets sick. The immune system walls off
the TB bacilli, which are protected by a thick waxy coat and they can lie dormant
(inactive) for years. When one’s immune system is weakened, the chances of
getting sick are much greater. The strength of the immune system is related to
nutritional status, hygienic conditions, susceptibility to other infection as well as
access to health care and vaccination throughout a lifetime (25).
From the late 19th century, improvement of socio-economic conditions
contributed more to the large decline in the prevalence of TB in industrialized
countries than all the medical interventions did. In the industrialized countries
today, this is again manifested through it has become a rare disease in the
population in general but is getting more prevalent among certain minority
groups, as well as among homeless people, alcoholics and drug abusers (34).
Even if we see an increase of TB among some groups in industrialized countries,
the burden of TB is mainly carried by developing countries where 95% of all
cases of the disease and 98% of all deaths due to it occur (30). In Ethiopia,
majority of the population live in absolute poverty. This creates a favorable
condition for the increase of TB incidence in the country. As described earlier, the
burden of TB in Ethiopia is one of the highest in the world. At the center of the
problem is the back ward socio-economic development resulting in one of the
lowest standard of living (9).
D. Movement and migration of people
Population movement in the form of migration of labour, general migration,
armed conflicts and refugee movement is more common to take place now a
days. In recent years, TB has become confined to definable population groups,
such as disadvantaged populations; immigrants from countries with a high
prevalence of TB, refugees, the elderly, homeless, substance abusers, persons
in correctional facilities and nursing homes. A high incidence of the disease in
these groups is not unexpected because the rates are higher in lower socioeconomic groups. Poverty leads to bad and overcrowded housing or poor
conditions. These may lower defenses as well as making infection more likely.
People living in these conditions are often badly nourished, suffer from alcohol
abuse or drug addiction. The whole complex of poverty makes it easier for
M.tuberculosis to cause the disease.
As a result of poverty, the actual number of refugees as well as displaced people
in the world is increasing. Untreated TB spreads very easily in crowded refugeecamps, prisons or between groups of homeless living together under poor
conditions. Homeless usually live in poor conditions. In addition, it is difficult to
treat migratory and homeless groups, as treatment takes at least six months and
close supervision. According to the WHO, as many as 50% of the world’s
refugees may be infected with TB, and forced movements of immigrants and
refugees contribute to the spread. The increasingly global nature of trade, air
traveling and the rapid movement of people across the world represents
additional risks of spreading the infection (32).
According to the United Nations Higher Commission for Refugees (UNHCR) (31),
there were an estimated 20 million refugees,
displaced and needy people in 2003. Many refugees originate from countries with
high TB incidence rates. Poor nutrition and health mean that refugees are at
particularly high risk of developing TB. In Ethiopia, as a result of rural poverty
landless people are being displaced. Due to HIV and other socio-economic
factors the number of street children is increasing. Besides these, the country
had been in a civil war for a number of years as a result a number of people had
been displaced. These all have created a favourable ground for the increased
transmission of TB in the country.
F. TB and drug resistance
During the past 4 decades, NTCPs have failed to reduce TB transmission. Health
policies in most low and middle in-come countries have not given priority to TB
control. In adequately funded programs have led to an increase in the pool of
chronic infectious sources. The overwhelming problem with the treatment of TB
is that cure takes months of treatment. The great majority of TB patients in the
world have poor health care facilities. Therefore, patients do not complete their
treatment. Premature stop of the treatment for TB results in relapse and the
emergence of drug resistance (34).
Poor management of TB causes resistance to anti-TB drugs. From a public
health perspective, treatment poorly supervised or incomplete treatment of TB is
worse than no treatment at all. Widespread occurrence of multi-drug resistance
TB (MDR) would constitute a major threat to controlling TB in resource poor
countries (35). This is because TB patients with resistant organisms may not
respond to standard treatment; remain infectious for longer periods of time and
spread resistant organisms to others. Most patients will require expensive
second line drugs. And in settings where resources are already inadequate,
control will be further compromised. There is no mystery about the causes of
drug resistance. It is a man-made consequence of poor patient management,
including improper prescription, non-compliance, lack of control of drug
distribution and irregular drug supply (30).
Studies have been conducted on drug resistance in different countries of the
world. In 2000, an estimated 273,000 of the 8.7 million new TB cases (3.2%)
were multi drug resistant. In A drug resistance survey carried out in 64 countries
the highest MDR proportions among new cases were found mostly in Eastern
Europe, Russia and china. An estimated 70% of new MDR cases were found in
only 10 countries (36).
In Ethiopia, periodic surveillance of drug resistance is lacking.
Few studies
conducted have reported resistance to one or more anti-TB drugs that ranged
from 15% to 37% (37, 38).
2. 2.3 The global TB control
2.2.3.1 What is DOTS strategy?
In 1993 the World Health Organization declared TB a global emergency, and
created a framework for TB control (39). In 1994, the WHO together with the
International Union against Tuberculosis and Lung Disease (IUATLD) launched
the DOTS strategy to fight TB. This five-pillar strategy has been proven to be
cost effective in some studies (40). And it is now recommended world wide as a
solution to the “Global emergency”. From the time DOTS was introduced on a
global scale, over 10 million infectious patients have been successfully treated
(29).
The targets for global TB control by the year 2000, ratified by the World Health
assembly were to successfully treat 85% of the detected smear positive TB
cases and to detect 70 % of all such cases (41). However, these targets were not
achieved as planned and the target year has been re-set to 2005. The WHO
estimates that in the year 2000, 55% of the worlds population lived in countries or
parts of countries covered by DOTS. Global case detection of smear positive
cases detected under DOTS calculations of the cure rate show an 80 %
treatment success rate in DOTS areas and a 22% cure rate in non DOTS areas
(25). A recent prediction shows that at the current pace of case detection, the TB
control goals will not be reached until 2013 (42). The major challenge is for TB
endemic countries to accelerate case detection, while still maintaining high cure
rates.
DOTS is one of the most cost effective health interventions, compared to those
available for other diseases. As part of the DOTS strategy, health workers
counsel and observe their patients swallowing each dose of a powerful
combination of medicines. The health system is required to observe that all
patients take their medication, to monitor their progress, ensure that all bacilli are
gone, and to document that they are cured. The package has other components
in a five-point policy package. These components include the following (10),
1. Government commitment to sustained TB control activity
2. Case detection by sputum smear microscopy among symptomatic
patients self- reporting to health services
3. Standardized treatment regimen of six to eight months with directly
observed therapy (DOT)
4. A regular and un interrupted supply of all essential anti-TB drugs
5. A standardized recording and reporting system that allows assessment
of treatment results for each patient and of the TB control program
performance overall.
2.2.3.2 TB case detection
Case detection under DOTS refers to the proportion of TB cases that are
diagnosed and reported within a DOT program divided by the assumed TB
incidence. Since the true incidence of TB in a given population is rarely known,
calculations of case detection are based on estimates of the true incidence of TB.
Different methods are used for estimating TB incidence, including extrapolation
made from assumed annual risk of infection and information from sentinel studies
(43).
The way to reach the target of 70% case detection is through passive case
finding. Passive case detection refers to the absence of active initiation from
health care providers i.e. the patient reports him or herself to health care
providers as opposed to active case detection, where health care providers
actively screen for TB in the population (44). The success of passive case
detection is thus highly dependent on both the patient health seeking behavior
and the awareness among health providers of symptoms suggestive of TB and
the possibility to act on them (44).
On the other hand, if increased case detection is to have an effect on the TB
epidemic, high cure rates are necessary. The WHO recommends national TB
control programs to first ensure a sufficiently high cure rate level and after that
expanding the program in terms of case detection (45). The way to reach the set
target of 85% cure rate, once adequate chemotherapy is available is according to
the DOTS strategy, to ensue patient compliance by direct observed therapy. This
component recommends observation of each intake of TB medication at least
during the first two months of treatment (45).
2.2.3.3 TB suspects and passive case finding
The diagnostic methods recommended in the DOTS strategy focus on identifying
sputum smear positive cases of pulmonary TB. The WHO and IUATLD have
recommended that all individuals with cough lasting for more than three weeks
should be offered TB diagnostics, i.e. a sputum smear examination when seeking
health care in TB high prevalent setting (45). Thus, long-term cough together with
sputum production are key features of the TB suspect case. Other general
symptoms of pulmonary TB are fever, weight loss and night sweats together with
additional respiratory symptoms like haemoptysis, cough, chest pain or dyspnea
(45).
According to the guidelines of the national TB control program, examination of
sputum by direct microscopy for the presence of acid fast bacilli (AFB) in all self
presenting persons with symptoms suggestive of TB must be performed (10).
Also, an assessment of the close contacts of patients of a smear positive
pulmonary case should be done. Other important activities that must be carried
out to improve the effectiveness of passive case finding activity include; public
education on the importance of early self-reporting for examination and treatment
whenever there are symptoms suggestive of the disease, training of general
health staff on prompt recognition of the signs and symptoms of the disease &
making quality diagnostic and treatment services accessible to all communities in
the country (10).
2.2.4 The importance of diagnostic delay in TB control
According to Rieder (2000), to ultimately reduce the incidence of TB in a
community, the primary epidemiological aim of TB controls is to reduce the pool
of persons with TB infection. Without intervention future cases of TB will emerge
from this pool. Principally, there are two supplementary lines of action to
accomplish this objective. The first is the interruption of transmission from newly
occurring infectious cases of TB with appropriate chemotherapy as swiftly as
possible after their occurrence, and the second line of action is the prevention of
TB cases before they occur with preventive therapy of sub clinically infected
persons. The first line of action will reduce the incidence of infection and the
second will reduce the prevalence of infection (46).
Rieder further elaborated that, between the onset of transmissibility and its
arrest, there could be a delay of the patient in seeking medical attention and the
delay of health care provider in making the diagnosis and commencing
appropriate chemotherapy. These delays are variably attributable to the patients’
attitude towards symptoms and the health care providers’ ability to rapidly
diagnose TB (46). For the patient, delay can occur during the process of noticing
symptoms, determining if one is ill, assessing the need of professional care and
overcoming social, personal and physical barriers to obtaining that care. For the
health care system, the differential diagnosis can expand or become more
focused depending upon key pieces of information. For instance, a physician
who has a high clinical suspicion of TB and an AFB smear positive sputum result
will probably initiate treatment more quickly than one with low clinical suspicion
and an AFB smear negative result. Further more, the clinician may begin by
considering diagnoses other than TB (47).
Globally, delays in diagnosis have been studied in many countries in different
settings and many different findings have been observed. In the following,
detailed accounts of the different lengths and risk factors of diagnostic delays are
presented.
2.2.5 What do we know about diagnostic delays?
2.2.5.1 Differences in the definition of diagnostic delays
According to Rieder (2000) diagnostic delays refer to the delay period related to
the patient and the health care provider before diagnosis and commencement of
treatment. When it comes specifically to patients’ delay, various definitions might
be given (46). For example, in the study that was conducted in an urban health
center setting in the Gambia (19), patients’ delay was defined as the period from
onset of the major symptoms to first visit to a health provider. The delay period
diagnosing facilities’ delay. The health provider in this study included traditional
healers, market drug sellers, pharmacists, village health workers, friends and
relatives as well as medical staff. Whereas in the Ethiopian study which was
conducted in a similar setting, patients’ delay was defined as the interval
between the onsets of the major symptoms to the first consultation to a health
care facility (23). The delay period was divided again into three namely; patients’
delay, health services’ delay and total delay. In this study, unlike the Gambian
study, consultations with traditional healers and other forms of health providers
were not included. In the Ethiopian study, this implies that, the delay is related to
the patient unless he/she visits a modern health care facility either in the private
sector or publicly owned health care facilities. From the Gambian study, the
lesson is that, the patient should not be blamed as long as he/she visits anyone
of the health providers based on the above definition, i.e. the delay is because of
other providers not because of the patient.
As for the health systems’ delay, in most of the studies it was defined as the
period from first visit to a medical facility to initiation of anti-TB treatment (18, 23,
48). However, the Gambian study in this regard used health providers’ instead of
health systems’ delay to refer to the period from first contact to a health provider
to first initiation of treatment (19).
Regarding the cut off point for an acceptable patients’ and health systems’
delays, the studies reviewed had no standard cut offs. Most studies used a onemonth period of delay as an acceptable patients’ delay (18, 23, 48). But, one
study from New York used 2 months as an acceptable patients’ delay (47). Other
studies used the median delay as a cut off point to dichotomize the samples into
shorter or longer delays (16, 47). As for the health systems’ delay, in the majority
of the studies, the acceptable delay ranged from 10 days to 2 weeks (47, 23).
However, one study from Canada used 1 week as an acceptable delay (49). The
decisions on the various cut offs were made by a consensus among treating
physicians in the respective areas where the studies were conducted (47, 50).
In general, we can observe from the above examples of studies that, the
definitions and the cut offs used for patients’ and health systems’ delay were not
similar. This might be related with the settings in which each of the studies were
conducted.
2.2.5.2. Lengths of diagnostic delays
The different studies conducted in various areas of the world have shown
variability in the lengths of diagnostic delays. For example, studies conducted in
Botswana (18), Ethiopia (23) and Ghana (16) have shown a median patients’
delay of 3 to 8 weeks and a health systems’ delay of 1 to 5 weeks and the total
delay was 9 to 16 weeks. The longest median patient’ delay was recorded in
Tanzania, which was 23 weeks (50). The least 0.3 weeks was recorded in the
Gambia (18). As to the proportion of patient’ delay, among the studies reviewed,
the highest was seen in Tanzania in which 85% of the study subjects delayed for
more than one month (50) and the lowest 20% was recorded in Malaysia (51).
2.2.5.3 Reasons behind diagnostic delays
A. Lack of knowledge
It is well established that knowledge plays an important role in shaping the health
seeking behavior of individuals. Studies have shown that patients who do not
know the symptoms and treatment of TB had longer period of delays compared
to those who know (23, 50). In many places, the symptom of cough is not openly
recognized as possible TB until accompanied by more serious symptoms such
as haemoptysis and weight loss (52, 53). In Kenya for example, the patient's
main defining factor for TB was that, symptoms were persistent. Therefore,
making early recognition of the disease impossible (53), as a result TB was
confused with other conditions including asthma, pneumonia, cancer, malaria
and AIDS (53). In Colombia, TB symptoms were seen as part of a flue-like
condition until accompanied by haemoptysis or weight loss (52).
B. Alternative explanation of the symptoms of TB
In certain parts of the world, symptoms of TB, such as cough, could be attributed
to certain traditional folk conditions. For example in Malawi, possible causes of
cough were believed to be tsempo, mphumu or mdulo, which are traditional
conditions believed to cause cough, chest pain and weight loss either for the
patient or a member of their family. The cause of such conditions is believed to
be careless sexual behavior such as adultery or having sex in taboo situations
(54). TB, which is thought to be acquired by bewitchment or the breaking of
sexual taboos. In such instances it is believed only traditional healing could help
the patient. In Colombia, patients were found to attribute TB symptoms to flu
initially. When symptoms persisted, a folk complex called grippa pasmada was
the usual explanation. This grippa pasmada (unripened flue) could be caused by
exposure to sudden temperature changes or desmande (being drenched by rain)
(52). In the Philippines, children with TB symptoms are believed to have a folk
illness, piang, which is due to injury to the skeletal or muscular system, and is
treated by massage (55). In Mexico, coughing, fatigue, loss of weight and back
pain were all attributed to gripe, bronchitis or a folk illness called susto. Similarly
in Kenya, early symptoms were often overlooked or confused with malaria or a
common cold (53). In Vietnam, patients identified four types of TB. Hereditary
TB; affecting women and caused by worry. Physical TB; affecting men and
caused by hard work. And Lung TB; contagious and mainly affecting men (56). In
Ethiopia, TB symptoms were associated with bird (57).
C. Socio-demographic factors
Gender
In most areas of the world, more men than women are diagnosed with TB and
die from it. TB is the leading infectious cause of death among women. Studies
have reported gender differentials showing significant variation of patient and
healthy systems delays. For example, a study conducted in Ghana (16) showed,
females had increased patients’ delay compared to males. In over half of the
patients, the doctors’ delay exceeded the patients’ delay. Doctors’ delay was
significantly increased in females. Median doctors' delay was three times longer
for females than males. In a study that was conducted in Kenya, it was found
that, the mean patients’ delay among women was 5.4 weeks and among men 3.8
weeks (50). In Vietnam (58), a study showed doctors’ delay of 5.4 weeks for
women and 3.8 weeks for men. Evidence from Nepal suggests that, there are a
higher proportion of women than men with TB who remains undiagnosed in the
community (59). Women are reported to have longer delays than men between
onsets of symptoms and presenting for treatment, only doing so when their
symptoms severely interfere with their daily activities (60, 61). In most low- and
middle-income countries, the women are only one third of the total notified cases.
This could be explained by the following hypothesis: higher exposure to infection
among men and under diagnosis among women due to socio-cultural and
economic reasons (58).
Age
Previous studies (20, 48) have shown that, the age of the patient may affect
health-seeking behavior. For example, older age >45 years was a risk factor for
delayed presentation (44). In Ethiopia those within the age group 24-34 were
found to experience longer delays compared to the lower age groups (22).
Occupation
In some studies, the type of occupation of the patient was found to affect early
presentation. A previous study that was conducted in Ethiopia showed that, the
married ones, farmers and soldiers were reported to have been delayed
compared to students (20). Another study from Botswana showed a median
health systems’ delay of 5 weeks. One of the significant risk factors associated
with health systems’ delay was marriage (18).
Education
“Level of education” in some studies was found to affect the health seeking
behavior of patients. Individuals with no formal education had longer delay (22);
patients with education less than 9 years were significantly delayed (58). In
Tanzania (50), patients with education below primary level were characterized as
having a longer delay. In Malawi (62), 43% of the patients were only aware of
their diagnosis at the time of receiving their smear results, and lack of schooling
was a significant risk factor in this study.
Area of residence
In order to encourage early presentation for treatment, the treatment offered
must be accessible to the patient. A study conducted in an urban Ethiopian
setting in 1998 showed that, the smear negative patients who lived >1 hour
walking distance from the health center were at risk of delaying more than 30
days after the onset of symptoms (23). In Tanzania, those that lived > 10 Km
away from a health facility had longer delay compared to those that lived <10 Km
to a health facility (50). In a study that was conducted in Ghana (16), doctors’
delay was significantly increased in rural patients. The median doctors' delay was
3.9 times greater for rural patients compared to urban dwellers. Another previous
study from south Ethiopia showed that patients who lived in rural areas
presented late for treatment (22).
Stigma
Possibly stigma is contributing further to all the other factors for delayed
presentation for treatment. This stigma is primarily caused by the contagious
nature of the disease, leading to a certain amount of social isolation. TB patients
become ostracized by peers and also within families, for example, being made to
eat separately and with different utensils (60, 61). In Pakistan (60), India (61) and
Ethiopia (63) TB may lead to divorce. For instance, 29 % of divorces in Ethiopia
is said to be due to TB (64). For unmarried women, TB jeopardizes their
marriage prospects (59, 60).
Among the Zulus in Africa, the contagious nature of the disease paired with a
belief in witchcraft leads to increased social stigma. To suggest a person with TB
may spread the disease is said to be tantamount to identifying that person as a
witch or sorcerer, since only such people have the power to spread disease (55).
The association of TB with poverty adds to the stigma of the disease. In Vietnam
for example, TB is seen as a dirty disease caused by bad hygiene and TB
patients report a lack of respect from their peers (58). In some parts of Africa, TB
is becoming synonymous with a diagnosis of AIDS, contributing further to the
stigma of the disease. For example, in a study that was conducted in Zambia,
49% strongly agreed that coming to the clinic for TB makes other people think
that the person has AIDS. However, the fear was not associated with delay (64).
Health service factors
The quality of the health service given at health care facilities may have an
impact on health care seeking and the speed of diagnosis. Many studies have
evidenced diagnostic delays attributable to poor quality of health care. For
example in Zambia (64), poor perception of the health services (particularly
expectation of lack of drugs and previous experience of the clinic) was found to
be an important factor for delayed presentation. In Colombia (52), staffs at health
centers have been shown to share the same beliefs and definitions of TB as
patients. The symptom of back pain would not cause the doctor to investigate
respiratory symptoms. Nurses only invite patients with haemoptysis, cough,
weight loss and fever to attend TB clinics, and use signs of poverty in patients’
appearance as a useful case finding method. Most patients attended some
medical practitioner once they diagnosed grippa pasmada, and received
prescriptions for flue (52). TB diagnosis was delayed due to the narrow opening
times of the laboratory for delivery of sputum samples (52). In Kenya (53),
patients mentioned being incorrectly diagnosed at their first consultations with
health centers, hospitals and dispensaries.
In Ghana (16), there was an almost perfect correlation between median doctors’
delay and rates of failure to perform sputum microscopy. There was also a strong
correlation with low rates of diagnosis. The median doctors’ delay at rural
government clinics and private institutions was significantly longer than that of
the central hospital doctors’ delay. The rates of failure to perform sputum
microscopy at these institutions were much higher than for the central hospital.
In some studies, prior attendance to health posts and village health workers was
associated with longer health systems’ delays. For instance, a study done in
Gambia (19) showed a median health providers’ delay of 8.3 weeks and median
diagnosing facilities’ delay of 0.2 weeks. First contact with village health worker
was a risk factor in this study. Another study from Botswana (18) showed a
median health systems’ delay of 5 weeks (mean: 12.2 weeks). Delayed sputum
examination was common despite the prolonged productive cough duration
reported by patients. One of the significant risk factor associated with health
systems’ delay was, first visit to a health post and traditional healers or faith
healers. In Ghana (16), 65% of the study subjects consulted traditional healers
first. In Tanzania (50), > 38 % of the study subjects primarily consulted traditional
healers before presenting to a formal medical facility.
In Malawi (62), 70%
attended traditional healers first.
In some studies, first visit made to private medical providers was found to be
associated with longer delays in diagnosis. A study done in Kuala Lumpur,
Malaysia (51) found that TB was not considered in most patients when they
consulted their private practitioners and essential investigations such as sputum
examination and chest x-ray were often not done.
Reasons for patients presenting to private practitioners before public doctors are
(65):
1. Greater ease of access
2. Shorter waiting periods
3. Longer or more flexible opening hours
4. Better availability of staff and drugs
5. More sensitive health worker-client attitudes
6. Greater confidentiality in dealing with stigmatized conditions such as TB, more
compatible with people’s expectations and cultural beliefs.
Cost of health care
There is considerable cost to both the patient and to the health service in
implementing an efficient TB treatment program. The main costs to the health
service are generally: sputum examination, drugs (where paid for by health
service), inpatient care (where required), supervision and follow up and health
education. The main costs to the patient are; cost of seeking alternative
treatments before diagnosed with TB, loss of work, travel expenses, costs during
any hospital stay required and social costs such as divorce and removal of
children from school (66). In Uganda, a study showed that approximately half the
monetary costs to patients were incurred before diagnosis when patients were
seeking different forms of treatment. It is likely that this is the case in many
countries as initially self-medication and consultation with private practitioners
are common (66).
Generally, from the above studies we can understand that, delays in diagnosis
have been common problems among pulmonary TB patients in many countries.
It has been evident from these studies that, the choices of first health provider,
the time of health seeking, the speed of diagnosis at health care facilities and the
risk factors varied from one country to another. This may imply that knowledge of
country specific health seeking behavior of patients as well as socio-cultural and
health service information are vital for understanding the magnitude of diagnostic
delays.
WHO as stated previously has evaluated all the available information regarding
diagnostic delay at a consultative meeting that was held in Geneva in 2000 and
has came to the conclusion that, the already available information regarding
diagnostic delay is insufficient to address the problems of delay, and has
recommended operational research directed at generating additional information
regarding the health seeking behavior, patients’ and health systems’ delays (20,
67). Besides this, a joint TB and leprosy review that was conducted in
partnership with WHO in October 2002 in Ethiopia has recommended that,
increasing case detection remains a priority that must be tackled through a
combination of efforts (68). Therefore, our study was conducted in response to
these international and national calls in addition to the local problems addressed
earlier in this chapter, and we believe that, the findings of our study may
contribute in filling the gap in knowledge about diagnostic delays from the
Ethiopian perspective.
2. Research questions, Hypothesis & Objectives
Research question
1. What is the duration of patients’ health systems’ and total delay?
2. What are the predictors of delay, in particular, socio-demographic factors, lack
of knowledge of TB symptoms and treatment, preference to private health care,
social factors like HIV/TB associated stigma etc?
Hypothesis
1. There is a significant patients’ and health systems’ delay in the diagnosis of
pulmonary TB in Amhara region.
2. Socio-demographic factors are the main predictors of delay.
General Objectives
To investigate patients’, health providers’ and health systems’ delays in the
diagnosis of pulmonary TB in Amhara region, Northwest Ethiopia.
Specific objectives
1. To determine the time delay from onset of the major symptoms of TB to
first visit to a health provider,
2. To estimate the time delay from first health provider visit to first initiation
of treatment.
3. To estimate the time delay from onset of the major symptoms of TB to
first visit to a medical provider
4. To determine the time delay from first medical provider visit to first
initiation of treatment.
5. To identify the risk factors influencing the time delay among patients and
the health care system in the diagnosis of pulmonary TB in Amhara
region.
1
1
. Health providers
any person consulted by the patient about his /her sickness that gave or
prescribed some thing (what ever the form) for treatment. This does not include
the family
2. Medical providers
modern health care facilities, including health centers hospitals and clinics either
government or privately owned.
Chapter two: Subjects and methods
2.1 Study area (setting)
The study area was the Amhara regional state. The study was carried out in 5
hospitals and 15 health centers. All were governmental health facilities with
TBMUs. In the region, there is no a well-established referral system. Therefore,
TB patients can go to either a hospital or a health center to seek for health care
depending on their choice.
2.2 Study design
The design was institution based cross-sectional study. Cross-sectional surveys
aim at quantifying the distribution of certain variables in a study population at one
point in time and the measurement of exposure and effect are made at the same
time (69).
2.3 The study universe (Study population)
Here is how we defined our universe for the study.
Pulmonary TB patients in Ethiopia
Target Population: New smear positive pulmonary TB patients in Amhara region
Study population: New smear positive pulmonary TB patients presenting to
TBMUs in the region from September 1 - December 31/2003
During the study period a total 1092 smear positive pulmonary TB cases were
diagnosed in the region. We studied 384, which hold 35.2 % of the total
diagnosed cases in the region.
The inclusion criterion
Subjects were included in the study if they were new smear positive pulmonary
TB patients and above 15 years of age.
Exclusion criterion
Subjects were excluded from the study if they were smear negative, relapsed or
failed treatment cases.
2.4 Sampling procedure and sample size
In order to select representative sample of the study population, a multi-stage
sampling procedure was followed. First, we selected 6 zones randomly out of the
11 zones of the region. Then, we listed all hospitals and health centers that are
found in the selected zones, and among the listed health institutions, we
randomly selected five hospitals and fifteen health centers (a total of 20 TBMUs)
as the final study sites. Finally, we interviewed subjects right after diagnosis
consecutively until the intended sample size was achieved.
Sample size determination
The sample size was calculated using the formula required for determination of
sample size for estimating proportions described as follows (70).
n = z2 pq
d2
where q = 1-p
n is the sample size, z is the z value, which is 1.96, and P is the proportion, d² is
the margin of error. Therefore, by taking a previous study done on patients’ and
health service delay in Ethiopia, which showed 58% proportion of delay of more
than one month (22) and a 95% confidence interval and a margin error of 5%, the
sample size was calculated to be 373, and when 5% was added for nonresponses and other loses, the total sample size was 392, and these were
selected from the 20 health facilities in the study area.
2.5 Data collection procedure
2.5.1 Preparation for data collection
The first step in the data collection procedure was to secure ethical clearance
from the Ethiopian Science and Technology Commission. For this purpose, we
had to submit 6 copies of the research proposal and other required documents to
the commission. Then, we waited for some time until decision was made. After 1
month of submission of the project proposal, we got the ethical clearance letter
from the commission.
The second step was to communicate with the ANRSHB regarding our project.
To accomplish this, we went in person to the bureau at Bahirdar, which is 560
Km away from the capital Addis Ababa and discussed about the project with the
respective officials in the bureau. They were very much delighted with the project
and happy to help us with the available resources and gave us an official letter of
permission to conduct the study in the region.
The third step was to go to each of the six zones where the selected health
facilities are found. We went in person and did the same thing like we did in the
regional health bureau. The zonal health department heads were happy to
collaborate with our project and gave us letter of permission to conduct our study
in the health facilities that are under their control. To reach at the final study sites
(health facilities), we had to go to each of the woreda health offices where the
selected health care facilities are found. Finally, after we got permission from
each of the woreda health offices, we went to each of the selected health
institutions to commence the data collection activity.
The last preparatory steps were to recruit interviewers, conduct training and pretesting the data collection instrument. We selected a total of 22 data collectors
(health officers) who were working at the study sites. The data collectors were
trained for three days. After the training, pre-testing was conducted in 5 health
facilities to test the data collection instrument. After the pre-test, a discussion was
held among the data collectors and the researcher. Following the discussion, the
original questionnaire was shortened and modified slightly.
2.5.2 Data collection method
In order to collect the intended data for this study, a questionnaire was used.
Most of the questions were closed-ended. There were also some open-ended
questions. Generally, structured questions with closed-ended questions are
commonly used in cross-sectional studies. However, there are some limitations
in using it. Like for example, important information may be missed, because
spontaneous remarks made by respondents are not recorded or explored. On the
other hand, open-ended questions permit collection of in-depth information and
exploration of spontaneous responses by respondents. However, the interviewer
may inadvertently influence the respondents and open-ended data are qualitative
and thus are relatively difficult to analyze (69).
2.5.3 Description of data/data collection
For each patient socio-demographic variable, major presenting symptoms of
pulmonary TB, duration of major presenting symptoms and the date of first health
care visit were included. The major pulmonary symptoms asked were presence
of cough for more than 3 weeks, production of sputum, chest pain and
haemoptysis. Other closed-ended questions regarding knowledge of TB were
also included (See annex-1).
During the interview, if a patient had weakness for over a year, but was seeking
medical care for a cough of one month duration, the latter was taken as the
duration of illness. All smear positive cases in the selected health institutions
were studied until the representative sample size was achieved within the study
period. The actual data collection commenced on September 1, 2003 and ended
on December 31, 2003.
2.5.4 Variables
Dependent variables:
1. Patients’ delay
2. Health providers’ delay
3. Medical providers’ delay
4. Diagnosing facilities’ delay
5. Health systems’ delay
6. Total delay
Independent variables:
Socio- demographic variables: sex, age, marital status, religion, ethnicity
Socio-economic variables: occupation, educational status, income and distance
from health facility
Health service factors, formal health providers, non-formal health providers,
presenting symptoms
2.5.4.1 Operational definitions of variables
TBMU:
A health care facility where microscopy for AFB
is done and anti -TB chemotherapy is initiated.
Total delay:
The total time (measured in days) from
reported onset of major symptoms (cough,
haemoptysis) to commencement of anti-TB
treatment.
Health systems’ delay:
The period (measured in days) from first visit to
a medical provider to first initiation of anti-TB
treatment.
Medical providers’ delay:
The period (measured in days) from first visit to
a medical provider to reporting to a TBMU
Health seeking period:
The period (measured in days) from onset of
the major symptoms of TB to first visit to a
health provider
Patients’ delay:
The period (measured in days) from the onset
of the major symptoms (cough, haemoptysis,
etc) to first visit to a medical provider.
Health provider:
Any person consulted by the patient about his
/her sickness that gave or prescribed some
thing (whatever the form) for treatment. This
does not include the family.
Health providers’ delay:
The time (measured in days) from the first
contact to a health provider to the first time
anti-TB chemotherapy is initiated
Diagnosing facility’s delay:
From the time (measured in days) the patient
reported to a diagnosing facility till the first time
the patient starts anti-TB treatment.
Formal health providers:
Modern health care facilities; such as health
centers clinics, hospitals either government or
privately owned.
Non-formal health providers:
These include traditional healers, herbalists
and religious healers, (holy water) and drug
retail outlets.
.
Traditional health providers:
These are traditional healers, herbalist,
religious healer (holy water).
Drug retail outlets:
These are pharmacies, drug stores, rural drug
venders and open market drug sellers
Income:
Income was divided into 4 categories; no
income, irregular income, regular income 1-300
Birr and regular income above 301Birr.
Housewives, students and the unemployed were categorized
as no income group. Farmers are categorized in the irregular
income group and self-employed were categorized in either of
the two regular income group by calculating their total income
on monthly basis.
Knowledge:
knowledge is information or fact that an
individual is aware of. In this study, it was
defined based on the awareness of the patient
about the symptoms and treatment of TB.
Stigma:
Feeling
of
disapproval
that
TB
patients
experience due to their illness in their day-today life within the community.
2.5.5 Data quality
As described earlier, questionnaire was used for data collection. The original
English version was translated into Amharic for the actual data collection. The
Amharic version was back translated into English to check the consistency of the
translation. In general, Quality of data was assured through the following
methods;
 Careful design and translation of the questionnaire
 Pre-testing and standardizing of the questionnaire
 Proper training of interviewers
 Continuous check ups of data collection procedures through intensive
supervision
 Patient register cards and TB registration books and laboratory registries
were cross-checked
2.6 Data analysis
After the data collection was completed successfully, the data were entered into
a computer and routine checking and cleaning were preformed. The statistical
package Epidemiology Program Office (Epi-Info) version 6 and statistical
package for the social sciences (SPSS) version 11.0 were used for analysis.
Percentages and proportions were calculated to show the distribution of the
population by socio-demographic characteristics. To determine the lengths of the
patients’, health systems’ and total delay; medians, means, inter-quartile range
were applied.
When assessing the risk factors for patients’, health providers’ health systems’
and total delay, the median delay period was used to dichotomize the sample in
to either shorter or longer delay period. Group differences were compared using
Mann-Whitney, Kruskal-Wallis (more than two groups) and chi- square tests.
Ninety-five percent confidence interval and odds-ratio were used to assess the
associated risk factors of the different delays. A p-value of less than 0.05 was
considered statistically significant. Finally, after all the potential covariates were
first identified by univariant analysis, logistic regression analysis was performed
to assess the relative impact of predictor variables on the outcome variables.
When assessing knowledge of respondents about TB, six questions were posed,
and a score was calculated from the awareness part of the questionnaire.
Awareness regarding TB was assessed from two angles, i.e. their knowledge
about treatment of TB and the seriousness of the disease. In the treatment part,
subjects were asked three questions including whether TB is curable or not, fee
for treatment and duration of treatment. If they believed that TB can be cured, the
assumption is that they might be willing to seek treatment. Concerning the
seriousness of the disease, subjects were asked about causes of TB, risk of
patients and people around them if they were not treated. For each of the six
questions, a value one was given if responded correctly and a value zero if
responded incorrectly. Then, the mean and the inter-quartile scores were
calculated. Finally, the score was divided into high knowledge and low
knowledge. Respondents that fall in to the third quartile were given a value one
and considered to have high knowledge and the other given value two
considered to have low knowledge. Then it was cross-tabulated with the main
outcome variables for possible associations.
When assessing stigma associated with TB/HIV, six questions were again posed
to the respondents. Each question was given a value one if answered correctly
and a value zero if answered incorrectly. Then the mean and inter quartile scores
were calculated. Respondents that fall in to the third quartile were given a value
one and considered to have less stigmatizing experiences and the others given
value two and considered to have high stigmatizing experiences. Then, it was
cross-tabulated with the dependent variables to look for possible association.
2.7 Communication of results
The study result will be presented as a master’s thesis at the institute of general
practice and community medicine at the University of Oslo, Norway. One or two
articles presenting the results will be submitted to international journals and local
journals in Ethiopia, the results of the study will also be presented to the regional
TB control program in the Amhara Regional State Health Bureau.
2.8 Ethical consideration
The project proposal was evaluated by relevant Ethical Committee in Norway
and the Ethiopian Science and Technology Commission. Both bodies have
ethically cleared the project.
Before the interviewing was commenced, the purpose of the study was clearly
explained by the interviewers for every participant of the study including how the
interview was going to take place. Great respect was given to the study subjects.
The patients were fully empowered to decide on their willingness to participate in
the study. Moreover, the study subjects were assured that there would not be
any risk of participating in the study. Their willingness to participate in the study
was confirmed by taking their informed consent. Both written and oral consent
systems were employed depending on the level of education of the study
subjects.
For the purpose of confidentiality, during the analysis of the records, names and
identifying features were coded to protect their privacy and after an interview was
over, the questionnaire was kept in a locked cabinet. The entire interview was
conducted in a private room in the health care facility. Taking into consideration
how interviewing is tiresome for the patient, we were very much careful not to
use more than the intended time of 20-30 minutes. All of the patients recruited
for the study volunteered to participate in our study.
Chapter three: Results
In this chapter, we will start describing the findings of our study first by presenting
the socio-demographic characteristics of the study population and then, we will
mention how the subjects perceived their illness initially and the actions they took
on their own in response to the symptoms. Following this, we will look into the
different delay periods and the associated risk factors. This data is presented in
two ways. In the first part, all health providers are taken as a reference point to
calculate the health-seeking period and the health providers’ delay. In the second
part, only medical providers were considered to calculate the patient’s, medical
providers’, diagnosing facilities’, health systems’ and total delay. We believe that,
this structuring of the result section might give a better understanding of our
material to the reader.
3.1 Socio-demographic characteristics
In this study, a total of 384 new smear positive pulmonary TB patients were
interviewed from September 1 – December 31/2003. The socio-demographic
characteristics of the respondents are summarized in table 2. The proportion of
males slightly exceeds that of the females with a ratio of 1.19: 1. The mean age
was 29.8 ±10.52 SD years with a median age of 28 years, minimum 16 and
maximum of 70 years. The mean age for males and females was 30.1 and 29.6
years, respectively. Most, 95.9%, of the subjects were in their productive age
(15-54 years old).
Married group constituted the highest proportion compared to the others. There
was sex-related significant difference in marital status among the sample
population (² = (3) 42.2, P< 0.001). Eighty-five out of one hundred eighty two
(46.7%) females were married compared to 55 (27.2%) males. On the other
hand, 98 out of 202 (48.5%) males were single compared to 36 (26.9%) females.
This difference was again statistically significant (² = (2) P= < 0.001). The
majority (97.1%) of the sample population belonged to the Amhara ethnic group
and the proportion of christians was higher compared to the other religions put
together, and the difference was statistically significant (² = (2) P= < 0.001).
Table 2 Socio-demographic characteristic of smear positive pulmonary TB patients in
Amhara region
_____________________________________________________________________
Characteristics
Number
%
_____________________________________________________________________
Sex
Male
Female
202
182
52.6
47.4
127
155
61
25
13
03
30.1
40.4
15.9
6.5
3.3
0.8
134
89
140
21
34.9
23.2
36.5
5.5
373
11
97.1
2.9
270
137
70.3
29.7
157
145
72
10
40.9
37.8
18.7
2.6
170
104
59
51
44.3
27.1
15.4
13.3
104
86
59
35
55
45
27.1
22.4
15.4
9.1
14.3
11.7
Age
15-24
25-34
35-44
45-54
55-64
>65
Marital status
Never married
Divorced
Married
Widowed
Ethnicity
Amhara
Others
Religion
Christian
Muslim
Education
Illiterate
1-8 grade completed
9-12 grade completed
12+
Monthly income (Birr)
No income
Irregular income
Regular income1-300 Birr
Regular income >301 Birr
Occupation
Farmers
House wife
Civil servants
Students
Unemployed
Self-employed
Number of children
No children
164
42.7
1-3
197
51.3
4-6
16
4.2
>7
7
1.8
Distance
≤10Km
216
56.3
>10Km
168
43.8
________________________________________________________________________
In this study, we found that 78.6% of the sample population was below the level
of 8th grade (table 2). The distribution of educational status among the sample
population showed significant difference (² (2) = 25.4 P <0.001), and specifically
when education was analyzed against sex, the difference was significant with
females being more illiterate compared to males (table 3).
Table 3 Education and marital statuses compared with the sex of smear positive
pulmonary TB cases in Amhara region.
Variable
Male
Female
Total
P-
value
________________________________________________________________________
Education
Illiterate
69 (34.2%)
88 (48.4%)
88 (40.9) ² (2) =25.4 P < 0.001
th
1-8 grade
84 (41.6%)
61 (33.5%)
61 (37.8)
>9th grade
49 (24.3%)
33 (18.1%)
33 (21.3)
Marital status
Never married
98 (48.5%)
36 (19.8%)
134 (34.9%) ² (3) =42.2, P<
0.001
Divorced
45 (22.3%)
44 (24.2%)
89 (23.2%)
Married
55 (27.2%)
85 (46.7%)
140 (36.5%)
Widowed
4 (2.0%)
17 (9.3%)
21 (5.5%)
______________________________________________________________________
The findings also showed that, fifty six percent of the respondents resided within
10 km radius of a medical facility. As for the type of house used for dwelling,
39.1% lived in a hut and 60.9% lived in an ordinary corrugated sheet iron roof
house. The houses in both cases had an average room number of one. The
average family size was 5, and in 51.3% of the households, the number of
children ranged from 3-5. Among the total respondents, 44.3% did not have any
form of defined income. However, among those who had regular cash income,
the average monthly income was 250 Birr, which is equivalent to USD$ 29.0
based on the current market. In general, the distribution of income among the
sample population showed statistically significant difference (² (3) =146.3 P <
0.01), and specifically when respondents’ income was cross-tabulated with the
sex of the respondents, we found that more females were in the no income group
compared to the males. The proportion was 61% verses 36 % and the difference
was statistically significant (table 4).
Table 4 comparisons of the respondents sex with income among smear positive
pulmonary TB cases in Amhara region
_____________________________________________________________________
Variable
Male
female
P-Value
______________________________________________________________________
Income
No income
74
111
Irregular income
83
31(² (3) =146.3 P < 0.01)
Income 1-300 Birr
19
17
Income above 301Birr
26
23
______________________________________________________________________
In this study, female respondents were asked whether they could decide on their
own regarding where to go for help during their illness, 327 (85%) responded that
they could decide on their own.
Subjects were asked also to describe if they had ever smoked, consumed
alcohol or chewed khat and their response was cross-tabulated against the
duration of illness before seeking help from the medical providers. The result
showed that there was no statistically significant difference among these groups
with regards to patients’ delay (table 5).
Table 5 Chi-square test showing comparisons of patients’ delay with current habits
among smear positive pulmonary TB patients’ in Amhara region
_______________________________________________________________
Delay
No delay
Characteristics
≤ 30 days
> 31 days p- value
_______________________________________________________________________
Smoking
Yes
8
4
No
191
181
0.45
Drinking alcohol
Yes
18
12
No
181
173
O.45
Khat chewing
Yes
21
31
NO
178
154
0.10
______________________________________________________________________
3.2 Initial symptoms, perception of illness and first action
The major symptoms that patients experienced during the course of their illness
are presented in figure 1. As can be seen on the graph, cough was the most
frequent symptom, followed by tiredness. Figure 2 shows chief complaints by
patients. In 60.7% of the cases, cough was also the chief compliant for
presenting to health providers.
Figure (1): Graph showing the major presenting symptoms among smear positive
pulmonary TB patients in Amhara region.
120% 96.4 %
100%
80%
76.0 %
79.4 %
90.6 %
92.2 %
85.2 %
86.5 %
yes
3.6 %
no
13.5 %
ss
lo
a
of
e
pp
t
ea
ss
w
ts
s
os
in
pa
e
tit
sis
ty
op
e
dn
7.8 %
l
ht
t
es
14.8 %
g
ei
ch
er
m
ae
h
ug
v
Fe
H
co
9.4 %
e
tir
20.6 %
gh
ni
24.0 %
25.0 %
w
60%
40%
20%
0%
75.0 %
Figure (2): Chief complaints of smear positive pulmonary TB patients in Amhara region.
,
70%
60%
50%
40%
30%
20%
10%
0%
60.7%
25.8%
10.2%
0.5%
1.0%
0.5% 1.0%
0.3%
ss
dne
Tir
g
at in
we
ht s
nig
ss
t lo
igh
we
tite
n
pai
s
ysi
ppe
fA
so
Los
r
est
Ch
ve
Fe
opt
h
em
Ha
ug
Co
When subjects were asked to describe what might have caused the symptoms at
the onset of their illness, only 17.5% of the respondents attributed their illness to
TB. Most (82.3%) suspected that they had other diseases. Of these, the most
frequent suspected cause was wind blow (locally called nefas) (Figure 3). The
mechanism of causation was believed to be that the wind penetrates the chest as
one is exposed to it and then reaches the lungs causing TB.
Figure 3 Perceived self-diagnosis among smear positive pulmonary TB
patients in Amhara region
70%
60%
50%
40%
30%
20%
10%
0%
61.4%
17.5%
6.3%
5.2%
6.5%
2.3%
No
TB
Dx
iti s
ch
on
Br
ia
ar
al
M
s
fa
Ne
a
m
th
As
As to the first action taken during the onset of cough, 46.9% of the respondents
reported that they had tried self-treatment to cure their illness. They used
traditional homemade remedies to lessen their cough and enhance the smooth
expectoration of the sputum. The types of remedies used were, various plant and
animal products including steam inhalation (table 6). According to the
respondents, the duration of the treatment ranged from 5 to 8 days.
Table 6 Lists of local remedies used for treatment among smear positive pulmonary TB
Patients in Amhara region
________________________________________________________________________
Types of treatment
Number
%
________________________________________________________________________
Hot fluids (atmit, suf, telba)
97
25.3
Honey, row egg yolk, Garlic
49
12.7
Steam inhalation
28
7.2
Goat meat (fat), ocholoni
14
3.6
No treatment taken
204
53.1
3.3. Lengths and associated risk factors of the different delays
3.3.1. A. All health providers considered as a reference point
3.3.1. A.1 The choice of first health provider and the period of health seeking
After trial of home treatment and as the symptoms persisted, patients started
seeking health care from different health care providers. Of all the respondents,
61.7% initially visited non-formal health providers and 38.3% visited the formal
medical providers. The decision about where to go for help was influenced in the
majority (88%) of cases by close family members. Friends and health
professionals also took part in influencing 44 (11.3%) the patient. Almost all
patients had visited a health care provider in one-month time from the onset of
their symptoms. The type of the specific health provider visited during the initial
period of the illness is presented in figure 4.
Figure 4 Pie chart showing first health providers visited by smear positive pulmonary TB
patients in Amhara region
3.60%
9.90%
9.40%
27.10%
Traditional providers
Drug retailoutlets
HC
3.90%
Hospitals
PMP
15.10%
31%
Local injectors
Cli/HP
Key
PMP: private medical providers, CLi/HP: Clinic or Health Post, HC: Health Center
A general analysis was performed to assess the relationship of selected sociodemographic variables with the choice of first health provider. For this purpose,
two groups were formed, Formal and non-formal health providers. Those who
first visited medical providers were categorized under formal and those who first
visited non-formal health providers were categorized under non-formal health
providers, and these groups were cross-tabulated against the socio-demographic
variables. The result showed that students (ORadj=0.32, 95%CI 0.11, 0.90) and
those with educational status of 9th grade and above (ORadj=0.42, 95% CI 0.23,
0.81) were less likely to visit the non-formal health providers. Otherwise, the
choice of health providers did not vary according to other variables (table 7)
Table 7 Relationship of choice of health providers with socio-demographic characteristic among
smear positive pulmonary TB patients in Amhara region.
_____________________________________________________________________________
Visited formal
visited non formal Crude
Adjusted
Characteristics health provider
health service
OR (95%CI)
OR (95%CI)
_____________________________________________________________________________
Sex
Male
Female
Age
15-24
25-44
>45
Education
Illiterate
1-8grade
>9 grades
83
64
119
118
1:00
1.28 (0.85, 1.94)
1:00
1.09 (0.66, 1.81)
56
73
18
71
143
23
1:00
1.50 (0.98, 2.40)
1.00 (0.49, 2.01)
1:00
1.33 (0.82, 2.17)
0.83 (0.38, 1.78)
48
55
44
109
90
38
1:00
0.72 (0.44, 1.16)
0.38 (0.23, 0.66) *
1:00
0.78 (0.46, 1.32)
0.42 (0.23, 0.81) *
Residence
>10 km
≤ 10 km
Occupation
Farmers
Housewives
60
87
108
129
1:00
0.82 (0.54, 1.24)
1:00
1.07 (0.64, 1.79)
38
24
66
62
1:00
1.48 (0.80, 2.75)
1:00
1.2 3(0.49, 3.17)
Civil servants
30
29
0.55 (0.29, 1.06)
0.87 (0.30, 2.51)
Students
22
13
0. 34 (0.15, 0.75) *
0.32 (0.11, 0.90) *
Unemployed
19
36
1.09 (0.55, 2, 16)
1.00 (0.39, 2.50)
Self employed
14
31
1.27 (0.60, 2.69)
1.47 (0.55, 3.97)
Single
50
84
1:00
1:00
Divorced
34
55
0.96 (0.55, 1.67)
0.73 (0.40, 1.35)
Married
52
88
1.00 (0.61, 1.64)
0.71 (0.40, 1.25)
Marriage
Widowed
11
10
0.54 (0.21, 1.36)
1.02 (0.49, 2.01)
Income
No income
64
121
1:00
1:00
Irregular income
44
70
0.84 (0.51, 1.30)
0.71(0.33, 1.54)
Income 1-300Birr
13
23
0.93 (0.44, 1.97)
0.86 (0.33, 2.24)
Income above 301 Birr 26
23
0.46 (0.24, 0.88) *
0.49 (0.18, 1.36)
Knowledge
Low
51
109
1:00
1:00
High
96
128
0.62 (0.40, 0.95) *
0.79 (0.48, 1.27)
Stigma
Low
57
76
1:00
1:00
High
90
161
1.34 (0.87, 2.06)
1.41 (0.92, 2.24)
_____________________________________________________________________________
* Significant at 0.05
** Adjusted for socio demographic factors
In general, the median time from onset of cough to first visit to a health provider was 15
days, (IQR 25-75 days) and the mean was 17.3 days.
3.3.1. A. 2 Health providers’ delay
The median and mean health providers’ delay were 61 and 86.4 days respectively. IQR
was 31-116 days. The cumulative distribution showed that 9.6% of the respondents had a
median health providers’ delay of 15 days and for 50 % of the respondents, the median
health providers’ delay took 60 days (figure 5). We observed significant difference
between those that first visited the formal health providers and those that visited the nonformal health providers (Mann-Whitney test; P< 0.001) (Table 8). Moreover, details of
the influence of the type of health provider on health providers’ delay are presented in
table 9.
Table 8 Choice of first health provider and its influence on the health providers’ delay,
among pulmonary TB patients in Amhara region.
_______________________________________________________________________
Health providers
Median (IQR)
P-value
________________________________________________________________________
Formal
43 (80-159)
Non formal
80 (80-159)
< 0.001
_____________________________________________________________________
Table 9 Choice of first health provider and its influence on the health providers’ delay
among smear positive pulmonary TB patients in Amhara region.
_____________________________________________________________________
N
Median delay (IQR)
Health provider
______________________________________________________________________
Traditional health care
104
89.5(47-168)
(Herbalist, holy water)
Drug retail outlets
119
88 (38-148)
Health posts
58
54 (24-83)
Health centers
36
35 (21-81)
Hospitals
15
36 (17.5-61)
Private clinics
38
37(25-110)
Local injectors
14
78 (42-146)
______________________________________________________________________
A further detailed analysis was performed to look into the association of sociodemographic and health services factors with the median health providers’ delay
(table 10). The results showed that those who lived within 10 Km radius of a
medical facility (ORadj =0.42 95%CI, 0.24, 0.72), those who went to school 1-8th
grade (ORadj= 0.56 95% CI, 0.33, 0.97), those who were 9 th grade and above
(ORadj= 0.40 95% CI, 0.20, 0.81) and those who attended formal health
providers initially (ORadj=0.35 95%CI, 0.20, 0.81) were less likely to have longer
health providers’ delay. On the other hand subjects between the age group 25-44
had experienced longer health providers’ delay.
In the univariat analysis civil servants (ORadj=0.41 95%CI 0.21, 0.78), students
(ORadj=0.25 95%CI 0.11, 0.59), Self-employed (ORadj=0.48 95%CI 0.24, 0.99)
and those with income above 301 Birr (ORadj=0.39 95% CI 0.20, 0.76) seemed
to have lesser risk of increased health providers’ delay. However, when doing
multivariate (logistic regression analysis) these tendencies lost significance.
Table 10 The associations of socio- demographic and health service factors with health
providers’ delay among smear positive pulmonary TB patients in Amhara region.
Characteristics
Sex
Male
Female
Age
15-24
25-44
>45
Residence
>10Km
10Km
Occupation
Farmers
Housewives
Delay
>62 days
No delay Crude
≤61 days OR (95%CI)
1:00
1.39 (0.93, 2.08)
1:00
0.89 (0.51, 1.53)
80
97
17
1:00
0.20 (1.33, 3.27) *
2.40 (1.17, 4.92) *
1:00
2.04 (1.21, 3.4) *
2.02 (0.88, 4.60)
110
80
58
136
1:00
0.31 (0.21, 0.47) *
1:00
0.42 (0.24, 0.72) *
60
55
45
42
1:00
1.31(0.72, 2, 34)
1:00
0.87 (0.32, 2.44)
21
38
0.41(0.21, 0.78) *
0.45 (0.13, 1.53)
9
24
0.25 (0.11, 0.59) *
0.33 (0.10, 1.08)
Unemployed
27
23
0.71(0.37, 1.36)
0.78 (0.29, 2.09)
Self employed
18
27
0.48 (0.24, 0.99) *
0.45 (0.15, 1.3)
Single
59
75
1:00
1:00
Divorced
39
50
0.99 (0.57, 1.70)
0.89 (0.45, 1.6)
Married
85
55
1.96 (1.2, 3.17)
1.61 (0.87, 2.94)
14
0.64 (0.24, 1.67)
0.60 (0.19, 1.83)
55
80
59
1:00
0.43 (0.27, 0.69) *
0.21 (0.12, 0.37) *
1:00
0.56 (0.33, 0.97) *
0.40 (0.20, 0.81) *
94
100
1:00
0.31 (0.20, 0.47) *
1:00
0.35 (0.21, 0.57) *
Civil servants
Students
94
96
108
86
47
119
24
Adjusted
OR (95% CI)
Marriage
Widowed
7
Education
Illiterate
102
1-8th grade
65
9th and above
23
Health provider visit
Non formal
143
Formal
47
Income
No income
Irregular income
98
56
87
58
1:00
0.85 (0.54, 1.36)
1:00
0.65 (0.28, 1.54)
1-300 Birr
21
15
1.24 (0.60, 2.56)
2.11 (0.77, 5.7
>301birr
15
Medical provider
Clinic/HP
38
Health center
86
Hospital
25
Private medical provider41
34
0.39 (0.20, 0.76) *
0.79 (0.26, 2.41)
39
77
27
51
1:00
1.14 (0.67, 1.97)
0.95 (0.47, 1.92)
0.89 (0.45, 1.51)
1:00
1.08 (0.56, 2.06)
1.29 (0.56, 3.00)
1.26 (0.61, 2.60)
___________________________________________________________________________
* Significant at < 0.05
* * Adjusted for socio/demographic and health service factors
3.3.1. B only medical providers considered as a reference point
3.3.1. B.1 Patients’ delay
Considering only medical providers as a reference point, we estimated the
patients’ delay. Accordingly our finding showed that the median delay from onset
of cough to first visit to a medical provider was 30 days, mean 61days and IQR
15-90 days.
Figure 6 shows the cumulative distribution of patients’ first visits to medical
providers. As can be seen from the graph, 52% of the cases had consulted a
medical provider by 1 month and for 5% of the cases, it took them more than 6
months. The longest delay was reported to be 2 years.
Figure 6 Cumulative distribution of patients’ delay among smear positive pulmonary TB
patient in Amhara region
120%
95%
% of subjects
100%
81%
80%
69%
60%
40%
100%
52%
Cummulative
32%
20%
0%
2 w eeks
1 month
2 month
3 month
Duration in months
6 month
above 6
month
Group differences for significant patients’ delay were assessed taking a onemonth cut-off point for comparison (table 11). There were no significant
differences by sex, marital status and income of the respondents. However,
significant differences were observed among other variables. The median
patients’ delay for those who were illiterates was 60 days compared to 30 days in
those who were literates (Kruskal-Wallis test; P<0.001) The median patient’ delay
varied also with age. The age group 15-24 had shorter delay compared to the
older age group (> 45 years old) (Kruskal-Wallis test; P=0.007). We have also
observed that the median patients’ delay varied with the patients’ area of
residence. Those who lived within 10 Km radius of a medical facility reported
earlier compared to those living beyond 10 Km. The durations were 25 and 70
days, respectively (Mann-Whitney test; P<0.001) (figure 7).
Figure 7 Cumulative distribution of patient’s delay in relation to place of residence
among smear-positive pulmonary TB patients in Amhara region.
120 %
99,50 %
100 %
89,40 %
82,90 %
80 %
69 %
60 %
42,10 %
100 %
89,90 %
total
69,90 %
Above 10 km
52 %
40 %
Less than 10 km
49,40 %
32 %
20 %
81 %
66,20 %
95 %
33,30 %
19 %
0%
2 w eeks
1 month
2 months
3 months
6 months
> 6 months
P < .001
Patients that initially visited non-formal health care providers and those that
treated themselves at home had also longer median patients’ delay compared to
those who did not take any action prior to visiting the first medical provider
(Mann-Whitney test; P<0.001). The occupational statuses of the subjects had
also an effect on the median patients’ delay. Longer median patients’ delay was
observed among farmers, the unemployed and housewives compared to the
students, civil servants and self-employed (Kruskal-Wallis test; P=0.003).
Knowledge about the symptoms and treatment of TB was found to have an effect
on the median patients’ delay. Those categorized as having a higher knowledge
of TB reported in 30 days compared with 60 days for those categorized as having
lower knowledge (Mann Whitney test; P<0.001) (table 11).
Logistic regression analysis was performed to look for the possible associations
of the different variables with significant patients’ delay (Table 12). Those who
lived beyond 10 Km radius of a medical facility (ORadj= 3.81, 95%CI 2.21-6.57),
age>45 years (ORadj=2.62, 95% CI 1.13-6.02) and self-treatment (ORadj=1.69,
95% CI 1.04-2.75) were significantly associated with increased patients’ delay.
We have also observed that the risk of patients’ delay among those who did not
visit non-formal health provider prior to visiting medical provider was smaller
(ORadj=0.34 95%CI 0.20, 0.57)
In univariat analysis those with education above 9 th grade (COR=0.30, 95%CI
0.17, 0.53), civil servants (COR=0.42 95%CI 0.22, 0.82), and students
(COR=0.35, 95%CI 0.16, 0.79) seem to have a lower risk of patients delay.
However, when we tried to find out the most influential factors of patients’ delay
using logistic regression analysis, these tendencies lost significance (Table 12).
Table 11 Sub-group analysis showing median patients’ delay among smear positive pulmonary
TB patients in Amhara region
______________________________________________________________________________
Median
P-value
Characteristics
No
patients’ delay (IQR) in days
________________________________________________________________________________
Total n=384
Sex
Male
202
30 (15-90)
Female
182
35 (15-90)
0.27
Age
15-24
127
30 (15-60)
24-44
216
35 (15-90)
0.007
>45
41
60 (60-120)
Marital status
Single
134
30 (14-90)
Divorced
89
35 (15-75)
Married
140
42 (15-115)
0.08
Widowed
21
30 (14-60)
Education
Illiterate
157
60 (15-120)
< 8th grade
145
30 (30-75)
9th and above
82
22 (12-47)
<0.001
Occupation
Farmers
104
50 (15-90)
Housewives
86
35 (15-90)
Civil servants
59
30 (30-60)
0.003
Students
35
21 (15-45)
Unemployed
55
55 (15-75)
Self-employed
45
30 (12-60)
Distance
> 10Km
168
70 (12-120)
 10Km
216
25 (14-60)
< 0.001
Self-treatment
Yes
180
45 (15-90)
0.004
No
204
30 (15-75)
Health provider visit
Non formal
Formal
Knowledge of TB
Low
High
Income
No income
Irregular income
Regular income
1-300 Birr
> 301Birr
Haemoptysis
Yes
No
237
147
55 (15-100)
21 (14-60)
<0.001
160
224
60 (20-120)
30 (14-60)
<0.001
185
114
36
42 (15-90)
30 (15-90)
21 (14-60)
30 (15-60)
0.16
49
96
288
67 (18-120)
30 (15-71)
<0.001
Table 12 The associations of socio-demographic and health service factors with delay to
first visit to a medical provider among smear positive pulmonary TB patients in Amhara
region.
Delay
>31 days
Characteristics
Sex
Male
91
Female
94
Age
15-24
49
25-44
110
>45
26
Residence
>10Km
112
10Km
73
Occupation
Farmers
59
Housewives
44
Civil servants
21
Students
11
Unemployed
32
Self employed
18
Marriage
Single
59
Divorced
45
Married
74
Widowed
7
Education
Illiterate
91
1-8th grade
70
9th and above
24
Health provider visit
No delay Crude
≤30 days OR (95%CI)
Adjusted
OR (95% CI)
111
88
1:00
1.19 (0.80, 1.79)
1.00
1.01 (0.62, 1.91)
78
106
15
1:00
1.65 (1.08, 2.58) *
2.76 (1.33, 5.72) *
1:00
1.47 (0.86, 2.49)
2.62 (1.13, 6.09) *
56
14
3.92 (2.56, 6.00) *
1:00
3.81 (2.21, 6.57) *
1:00
45
42
38
24
23
27
1:00
0.79 (0.45, 1.42)
0.42 (0.22, 0.82) *
0.35 (0.16, 0.79) *
1.06 (0.55, 2.06)
0.51 (0.25, 1.03)
1:00
1.36 (0.12, 1.03)
0.61 (0, 17.2.19)
0.40 (0.12, 1.32)
0.96 (0.35, 2.66)
0.78 (0.26, 2.34)
75
44
66
14
1:00
1.30 (0.76, 2.22)
1.43 (0.89, 2.29)
0.64 (0.24, 1.68)
1:00
1.39 (0.72, 2.67)
1.30 (0.69, 2.42)
0.69 (0.22, 2.16)
66
75
58
1:00
0.68 (0.43, 1.07)
0.30 (0.17, 0.53) *
1:00
1.38 (0.67, 2.83)
1.47 (0.75, 2.87)
Formal
47
100
1:00
1:00
Non formal
138
99
2.97 (1.93, 4.57) *
0.34 (0.20, 0.57) *
Income
No income
100
85
1:00
1:00
Irregular income
54
60
0.77 (0.48, 1.22)
1.30 (0.43, 3.90)
1-300 Birr
14
22
0.54 (0.26, 1.12)
0.57 (0.16, 1.98)
>301birr
17
32
0.45 (0.23, 1.87)
0.49 (0.17, 1.46)
Self-treatment
Yes
121
59
1.75 (1.16, 2.62) *
1.69 (1.04, 2.75) *
No
110
94
1:00
1:00
Knowledge of TB
Low
100
60
2.72 (1.79, 4.14) * 1.89 (1.15, 3.10) *
High
85
139
1:00
1:00
Stigma
Low
67
66
1:00
1:00
High
118
133
0.87 (0.57, 1.33)
0.88 (0.54, 1.45)
___________________________________________________________________________
* Significant at <0.05
** Adjusted for socio-demographic and health service factors
3.3.1. B.2 Medical providers’ delay
The median delay from first visit to a medical provider to first reporting to a TBMU
was 15 days, mean 36 and IQR 0-53 days. The median medical providers’ delay
did not vary according to some selected socio-demographic factors. However,
those who first visited a health post or a private medical provider had longer
delay compared to those who visited a government health center (Kruskal-wallis
test; p< 0.001) (table 13).
Table 13 Sub-group analysis showing median medical providers’ delay among smear
positive pulmonary TB patients in Amhara region
________________________________________________________________________
Variable
N
Median delay (IQR)
P-Value
________________________________________________________________________
Sex
Male
202
57 (27-144)
Female
182
65 (37-118)
0.51
Age
15-24
127
10 (10-30)
25-44
216
20 (0-60)
0.089
>45
41
30 (0-59)
Education
12
Illiterate
157
15 (0-60)
1-8th
12
20 (0-56)
0.182
th
>9
82
10 (0-38)
Distance
>10 km
168
13 (0-60)
10Km
216
21 (0-52)
0.328
Health provider
Clinic/health post
59
30 (7-78)
Health center
146
8 (0-40)
0.001
Hospital
50
7 (0-44)
Private medical
76
32 (3-75)
providers
_____________________________________________________________________
In this study, subjects were found to have visited a considerable number of
medical providers before ending up in the final diagnosis. The median number of
medical providers seen prior to starting TB treatment was 2 (IQR1-3) and the
highest was 8. This is not taking in to account the number of visits made to the
same medical providers. For 86 (22.5%) of the subjects, the total number of
medical provider seen exceeded 4 (figure 8). We compared the frequency of
medical providers visit prior to the diagnosis of TB with the socio-demographic
factors. There was no effect of sex, age, area of residence, education, income or
occupation on the number of medical providers seen (Table 14).
Figure 8 Graph showing the frequency of medical providers’ visit prior to the
diagnosis of TB among smear positive pulmonary TB patients in Amhara region,
September-December 2003.
140
Frequency
120
100
80
60
40
20
0
0
1
2
3
4
5
6
7
8
Number of visits
Table 14 Comparisons of the socio-demographic factors with the frequency of medical
providers visit prior to the diagnosis of TB among smear positive pulmonary TB patients
in Amhara region.
_______________________________________________________________________
Variable
N
Median number of (IQR)
P-Value
of providers
________________________________________________________________________
Sex
Male
Female
202
182
2 (1-3)
2 (1-3)
127
216
41
2 (1-3)
2 (1-3)
2 (2-4)
157
12
2 (1-3)
2 (1-3)
0.16*
Age
15-24
25-44
>45
Education
Illiterate
1-8th
0.10*
0.95*
>9th
82
2 (1-3)
Distance
>10 km
168
2 (1-3)
10Km
216
2 (1-4)
0.53*
Monthly income (Birr)
No income
170
2 (1-4)
Irregular income
104
2 (1-3)
0.25* *
Income1-300 Birr
59
2 (2-3)
Income >301 Birr
51
2 (1-3)
Occupation
Farmers
104
2 (1-3)
House wife
86
2 (1-3)
0.51**
Civil servants
59
2 (2-4)
Students
35
2 (1-4)
Unemployed
55
2 (1-3)
Self-employed
45
2 (1-3)
_____________________________________________________________________
*Mann-Whitney test
**Kruskal Wallis test
The cumulative distribution of the median medical providers’ delay is presented
in figure (9). Forty percent of the respondents had a median medical providers’
delay of 7 days. However, for 20 % of the cases the medical providers’ delay was
more than 3 months prior to reporting to a TBMU. These were more likely to be
living more than 10Km 32/168vs 20/216, P= 0.009 to have visited health post
18/77 vs 34/273, P=0.006 and to be illiterate 29/157vs 4/82, P=0.014 (table 15).
Figure 9 Cumulative distribution of medical provider delay among smear-positive
pulmonary TB patients in Amhara region
100 %
80 %
80 %
52 %
60 %
40 %
20 %
40 %
62 %
Table 15 Comparisons of medical providers’ delay in those who reported within 3 and above 3
months with some socio-demographic factor among smear positive pulmonary patients in
Amhara region.
______________________________________________________________________________
_
Duration of illness
Variable
90 days
>91 days
P- value
Sex
Male
177
25
0.58
Female
155
27
Age
15-24
115
12
25-44
182
34
0.253
>45
35
6
Education
Illiterate
128
29
1-8th grade
126
19
0.014
> 9th grade
78
4
Income
No income
163
22
Irregular income
94
20
0.32
Regular income
1-300 Birr
30
6
Regular income
>301 Birr
45
4
Distance
>10 Km
136
32
0.009
 10Km
196
20
Medical provider
Health post
59
18
Health center
146
17
0.006
Hospital
50
2
Private
77
15
___________________________________________________________________________
3.3.1. B.3 Health systems’ delay
The median health systems’ delay was 21 days, mean 42 days IQR being 7-60
days. The cumulative distribution of health systems’ delay is presented in figure
10. From the graph we can see that from the time the subjects first visited a
medical facility, 42.2% started treatment within 2 weeks and for 24% of the
subjects, the median health systems’ delay was more than 2 months. These
were more likely to be living at a distance of more than 10 Km away from a
medical facility, to be illiterates and to be above the age of 25 years (table 16).
Figure 10 Cumulative distribution of health system’ delay among smear-positive
pulmonary TB patients in Amhara region.
120%
100%
93%
97%
100%
80%
76%
60%
40%
65%
42%
20%
0%
2 w eeks
1 month
2 months
3 months
6 months
> 6 months
Table 16 Selected socio-demographic factors associated with delay for more than three
months before commencing anti-TB chemotherapy among smear positive pulmonary TB
patients in Amhara region.
________________________________________________________________________
Duration of illness
Characteristics
 120 days
>121 days OR (95% CI)
________________________________________________________________________
Sex
Male
143
59
1:00
Female
120
62
1.25 (0.81, 1.92)
Age
15-24
102
25
1:00
25-44
139
77
2.26 (1.35, 3.79) *
> 45
22
19
3.50 (1.65, 7.48) *
Education
Illiterate
85
72
1:00
1- 8th grade
104
41
0.46 (0.28, 0.78) *
th
> 9 grade
74
8
0.12 (0.58, 0.28) *
Residence
>10 Km
93
75
1:00
10 Km
170
46
0.33 (0.21, 0.52) *
Income
No income
120
65
Irregular income
79
35
0.81 (0.49, 1.39)
Regular income
25
11
0.81 (0.37, 1.76)
1-300
Regular income
39
10
47 (0.22, 1.00)
> 301
________________________________________________________________________
* Significant at point < 0.05
Comparison among the various groups of respondents was made to look for
differences with regards to health systems’ delay (table 17). Significant
differences were not observed for most socio-demographic factors. But the
median health systems’ delay among the age group 15-24 was 14 days
compared to 27 days among the age group 25 and above years (Kruskal-Wallis
test; P=0.028) and those that visited private medical providers first had a longer
health systems’ delay compared to those that visited government medical
providers (P=0.022). The median health systems’ delay for those who went to a
health post was 39 days compared to 14 days in those that went to a health
center or hospital (Kruskal-Wallis test; P<0.001).
In logistics regression analysis, those who first visited a health post (ORadj=
3.50, 95% CI 1.86-6.57) or a private medical provider (ORadj=2.10 95% 1.18,
3.71) were significantly associated with increased health systems’ delay (Table
18).
Table 17 Sub-group analysis showing median health systems’ delay among smear positive
pulmonary TB patients in Amhara region
___________________________________________________________________________
Median health systems’
P-value
Characteristics
NO
Delay (IQR), in days
___________________________________________________________________________
Total n=384
Sex
Male
202
20 (7-60)
Female
182
22 (8-60)
0.59
Age
15-24
127
14 (6-43)
24-44
216
27 (8-43)
0.028
>45
41
27 (7-64)
Marital status
Single
134
24 (24-60)
Divorced
89
20 (20-50)
Married
140
21 (21-75)
0.79
Widowed
21
35 (5-58)
Education
Illiterate
157
22 (8-69)
< 8th grade
145
22 (7-61)
9th and above
82
20 (7-46)
0.31
Occupation
Farmers
104
19 (16-65)
Housewives
86
36 (14-79)
Civil-servants
59
14 (25-75)
0.12
Students
35
19 (6-37)
Unemployed
55
20 (7-57)
Self employed
45
21 (5-61)
Income
No income
170
23 (9-57)
Irregular income
104
20 (7-61)
0.38
1ncome 1-300 Birr
59
36 (6-80)
Income > 301 Birr
51
14 (6-53)
Distance
> 10Km
168
19 (7-64)
10Km
216
27 (8-58)
0.55
Health provider
Visit (general)
Private
92
36 (10-80)
Government
292
20 (7-57)
0.022
Health provider
Visit (specific)
Health post
77
39 (17-85)
Health center
163
14 (6-45)
<0.001
Hospital
52
14 (7-48)
Private
92
36 910-80
_________________________________________________________________________
Table 18 The associations of socio-demographic and health service factors with health
systems’ delay among smear positive patients in Amhara region
_________________________________________________________________________
Delay
No delay
Crude
Adjusted
Characteristics
>16 days
≤15 days
OR (95%CI) OR (95% CI)
Sex
Male
Female
Age
117
103
85
79
1:00
1:00
0.95 (0.63, 1.42) 0.73 (0.44, 1.21)
15-24
25-44
>45
Marital status
63
133
24
64
83
17
1:00
1:00
1.65(1.08, 2.58) * 1.62 (0.98, 2.61)
2.76 (1.33, 5.72* 1.30 (0.59, 2.90)
Single
Divorced
Married
Widowed
Occupation
Farmers
Housewives
Civil servants
Students
Unemployed
Self-employed
Income
79
52
76
13
55
37
64
8
1:00
0.97 (0.56, 1.68)
0.83 (0.51, 1.33)
1.13 (0.94, 2.91)
1:00
1.12 (0.61, 2.05)
0.91 (0.51, 1.64)
1.12 (0.38, 3.26)
46
26
31
17
23
21
58
60
28
18
32
24
1:00
1.80 (1.00, 3.33)
0.71 (0.37, 1.36)
0.84 (0.39, 1.80)
1.10 (0.57, 2.13)
0.90 (0.44, 1.82)
2.16 (0.84, 5.5)
0.74 (0.26, 2.17)
0.68 (0.24, 1.93)
0.92 (0.37, 2.31)
0.64 (0.24, 1.70)
No income
73
112
1:00
Irregular income
Income1-300birr
>301
Residence
>10Km
10Km
Education
Illiterate
1-8th grade
9th and above
Medical provider
50
14
27
64
22
22
0.83 (0.52, 1.33) 0.91 (0.43, 1.94)
1.0 0(0.49, 2.13) 1.62 (0.61, 4.18)
0.53 (0.28, 1.00) 0.54 (0.19, 1.48)
90
130
78
86
1:00
1.31 (0.87, 1.97)
1:00
2.01 (1.22, 3.48) *
90
85
45
67
60
37
1:00
1.06 (0.67, 1.67)
0.90 (053, 1.55)
1:00
1.00 (0.59, 1.69)
0.64 (0.33, 1.23)
Health center
79
84
1:00
1: 00
Health post
57
20
3.03 (1.67, 5.49) * 3.90 (2.06, 7.64)
*
Hospital
23
29
0.84 (0.45, 1.58) 0.82 (0.41, 1.62)
Private
61
31
2.32 (1.23, 3.55) * 2.32 (1.23, 4.23)
*
_____________________________________________________________________
* Significant at 0.05
** Adjusted for socio demographic and health service factors
3.3.1. B. 4 Diagnosing facilities’ delay
Several providers referred patients to the TBMUs for diagnosis and initiation of
anti-TB chemotherapy. In general, government health assistants, nurses or
doctors referred 271 (70.6%) of the patients. Private medical providers referred
92 (24.0%), 11 (2.9%) were self-referred, 2 (0.5%) were referred by pharmacists
and 8 (2.1%) were referred by friends.
The median diagnosing facilities’ delay from reporting to the TBMU to AFB
request, from AFB exam to notification and from notification to initiation of
treatment was 2 days, respectively. Overall, the median diagnosing facilities’
delay was 5 days, mean, 6.7 and IQR 4-8. But for 13 patients, the median delay
exceeded 15 days and the longest delay was reported to be 31 days.
In this study it was observed that all patients that were referred from private
doctors were required to be re-examined and submit sputum for AFB at the
TBMU despite having a referral paper and clear cut diagnosis of smear positive
pulmonary TB from the private medical doctor. It was also observed that the
TBMU expected every smear positive patient to fulfill one major criterion before
starting anti-TB chemotherapy.I.e., all patients were required to have some-body
(preferably a relative) with them who had a defined address and was willing to be
responsible for tracing the patient in case of default after starting treatment. This
procedure was a must; otherwise, patients were not entitled to start anti -TB
chemotherapy despite having a positive smear result. Among the 13 patients
whose median diagnosing facilities’ delay exceeded 15 days, 10 (86.7%) were
those who could not manage to bring a responsible person at the time of
diagnosis. These patients went back long distances to their residence area to
bring a relative and start their treatment.
All patients after being diagnosed and took the first anti-TB drug on the spot at
the TBMU were sent back to the nearest health care facility to their home for the
continuation of the rest of the treatment.
3.3.2 Total delay
In this study, the median and mean total delays were 80 and104 days,
respectively. The IQR was 44.2-129.8 days. The distribution of the reported
duration of symptoms prior to treatment is shown in figure 11. As can be seen
from the graph, only 9% of the total respondents were detected and put on
treatment within one month of the onset of their illness. For 121 (31%) of the
cases, the median total delay exceeded 4 months. These patients were more
likely to be older 19/41vs 102/343, (P<0.001), to live in a distance of more than
10 km away from a medical facility, 75/168 vs 46/216, (P<0.001) not to have
gone to school 72/157 vs 49/227, (P<0.005).
Figure 11 Cumulative distribution of total delay among smear-positive pulmonary TB
patients in Amhara region, August to December 2003
120 %
In this study, the median (IQR) total delay to treatment varied with the subjects’
area of residence. For those who live 10 Km away from a medical health
provider, the length of delay was 100 days (IQR 65-191 days) but for those that
live within 10 Km radius of a formal health care facility, the median delay was
shorter 65days (IQR 36-98days) (Mann-Whitney test; P<0.001) (table 19).
The subjects’ occupation appeared to influence the median total delay. Those
who reported shorter delay include self-employed 67 days (IQR, 38-112days),
civil servants 65 days (IQR, 35-98days) and students 51days (35-69days).
Where as longer delays were reported among housewives, 98 days (IQR, 65-172
days), farmers 97 days (IQR, 61, 188 days) and by the unemployed 78 days
(IQR, 45-155 days). It also varied with the patients’ educational level. Illiterates
had a median total delay of 98 days (IQR 65-186 days) and those with education
above the level of 9th grade, the median total delay was shorter, 48 days (IQR
34-83 days) (Kruskal-Wallis test; P=0.005).
The subjects’ marital status was found to affect the median total delay. Married
subjects were found to have the longest delay, 97days (IQR 62-172days)
compared to those who were never married, 67 days (IQR 36-126 days)
(Kruskal-Wallis test; P=0.019). Age also had an effect on the median total delay.
Those who were between 25 and 44 had longer delay compared to those below
24 years of age (P=0.016).
Patients who treated themselves at the onset of the initial symptoms at their
home had a longer total delay compared to those that did not try self-treatment.
The median total delay was 95 days (IQR 65-185 days) vs 65 days (IQR 36123days) (Mann-Whitney test; P=0.005). Also, patients with haemoptysis had
longer duration of total delay than those with out haemoptysis (median 125 vs
67days Mann-Whitney test; P=0.005)
Table 20 shows the association of socio-demographic and health services factors
with the median total delay. Accordingly the age group 25-44 (ORadj=1.85,
95%CI 1.06, 3.20) was significantly related with increased total delay compared
to the age group 15-24years. Marital and educational statuses of the study
groups were associated with increased total delay. The married group had
increased risk of delay compared to the singles (ORadj= 2.26 95% CI 1.14, 4.10)
and those with education above the level of 9 th grade had a smaller risk of total
delay compared to the illiterates (ORadj= 0.42 95%CI 0.19, 0.89). Besides these,
those who first treated themselves (ORadj=1.75, 95%CI 1.05, 2.93) and those
who went to the non-formal health providers (ORadj =2.52 95%CI 1.49, 4.23)
were characterized as having a higher risk of longer median total delay.
Regarding the knowledge of patients about TB, it was found that those with low
level of knowledge (ORadj=3.49 95% CI 2.01, 5.80) had a 3-fold risk of total
delay than those having lower level of knowledge about TB.
In univariat analysis age >45 years (ORadj=1.67 95%CI, 0.72, 3.80), civil
servants (OR=0.39, 95%CI 0.20, 0.76), students (OR=0.21, 95%CI 0.87, 0.50)
and self-employed (OR=047, 95%CI 0.23, 0.96) seem to have a smaller risk of
delay compared to the farmers. But when we analyzed the possible effects of the
interaction of the entire variables using multi-variat (logistic regression) analysis,
these tendencies lost significance.
Table 19 Sub-group analysis showing median total delay among smear positive pulmonary TB
patients in Amhara region
___________________________________________________________________________
Median total
Characters tics
No
Delay (IQR)
P-value
___________________________________________________________________________
Total n=384
Sex
Male
202
69 (38-125)
Female
182
93 (61-150)
0.095
Age
15-24
49
64 (35-100)
25-44
278
94 (62-147)
0.016
>45
57
95 (97-194)
Marital status
Single
127
67 (36-126)
Divorced
79
69 (39-124)
Married
164
97(62-172)
<0.001
Widowed
14
67(63-95)
Education
Illiterate
157
98 (65-186)
< 8th grade
145
69 (48-126)
<0.001
9th and above
82
48 (34-83)
Occupation
Farmer
104
97 (61-188)
Housewife
86
98 (65-172)
Civil servant
59
65 (35-98)
Student
35
51 (35-69)
<0.001
Unemployed
55
78 (45-155)
Self-employed
45
67 (38-112)
Distance
> 10Km
168
100 (65-191)
 10Km
216
65 (36- 98)
<0.001
Self-treatment
Yes
180
95 (65-185)
No
204
69 (36-123)
<0.001
Income range
No income
185
93 (50-159)
Irregular Income
114
84 (49-134
1-300 Birr
36
91 (45-126)
0.032
> 301Birr
49
49 (65-149)
Med pro visit
Private
92
68 (35-123)
0.078
Government
292
91 (49-149)
Health pro visit
Non formal
147
96 (64-184)
<0.001
Formal
237
64 (35-96)
Haemoptysis
Yes
96
110 (83-185)
No
288
67 (38-123)
<0.001
Knowledge
Low
160
112 (66-188)
High
224
65 (36- 96)
<0.001
_____________________________________________________________________________
Table 20 The relationships of socio-demographic and health service factors with late initiation of
anti TB chemotherapy among smear positive pulmonary TB patients in Amhara region.
______________________________________________________________________
Delay
No delay
Crude
Adjusted
Variable
> 81 days
≤80 days
OR (95% CI) OR (95% CI)
_______________________________________________________________________
Sex
Male
91
111
1:00
1:00
Female
83
99
1.33 (0.89, 1.99)
0.81 (0.48, 1.36)
Age
15-24
49
78
1:00
1:00
25-44
118
98
1.92 (1.23, 2.99) *
1.85 (1.06, 3.20)
*
>45
23
18
2.03 (0.99, 4.44)
1.67 (0.72, 3.80)
Marital status
Single
57
77
1:00
1:00
Divorced
38
51
1.01 (0.58, 1.73)
1.02 (0.52, 1.92)
Married
89
51
2.36 (1.45, 3.83) *
2.18 (1.14, 4.19)
*
Widowed
6
15
0.54 (0.19, 1.48)
0.47 (0.14, 1.55)
Occupation
Farmers
61
43
1:00
1:00
House wife
55
31
1.25 (0.69, 2.25)
0.84 (0.24, 1.93)
Civil servants
21
38
0.39 (0.20, 0.75) *
0.45 (0.12, 1.60)
Students
8
27
0.21 (0.87, 0.50) *
0.28 (0.07, 1.01)
Unemployed
27
28
0.68 (0.35, 1.31)
0.69 (0.25, 1.93)
Self employed
18
27
0.47 (0.23, 0.96) *
0.46 (0.15, 1.46)
Education
Illiterate
104
53
1:00
1:00
1-8grade completed
66
79
0.43 (0.27, 0.68) *
0.65 (0.37,
1.16)
9th grade and above
20
62
0.16 (0.09, 0.30) *
0.42 (0.19, 0.89) *
Income
No income
103
82
1:00
1:00
Irregular income
62
52
0.89 (0.56, 1.42)
0.68(0.27, 1.65)
Income 1-300 Birr
19
17
0.99 (0.49, 2.02)
1.48 (0.52,
4.19)
Income >301Birr
6
43
0.43 (0.22, 0.84) *
0.93 (0.29,
2.91)
Distance
>10km
109
59
3.0 (2.0, 4.7) *
1.80 (1.02, 3.17) *
<10Km
81
135
1:00
1:00
First health pro visit
Non formal
134
103
3.08 (2.02, 4.68) *
2.52 (1.49, 4.23)
*
Formal
56
91
1: 00
Self-treatment
Yes
103
77
1.80 (1.2, 2.7) *
1.75 (1.05, 2.93)
*
No
87
117
1: 00
1:00
Knowledge of TB
Low
114
46
4.80(3.1, 7.49) *
3.49 (2.01. 5.80)
*
High
76
148
1:00
1:00
Stigma
High
70
63
1:00
1:00
Low
120
131
0.82 (0.54, 1.25)
0.81 (0.48, 1.36)
______________________________________________________________________________
* Significant at 0.05
** Adjusted for socio demographic and health service factors
In general, taking all health providers and only medical providers as a
reference point separately, we can see variations in the length of the different
delay periods. In the first scenario (figure12) patients who first visited a
medical provider had a median delay of 30 days. In the second scenario
(figure 14) considering all health providers as potential venues of health
seeking, we can see that patients visit a health provider relatively early
compared to the first scenario. The health-seeking period is shorter. It took
them only 15 days to first visit a health provider. Overall the contribution of the
health-seeking period by patients to the total delay is smaller. As shown in
figure 14, the greater portion (81%) of the delay was due to the health
provider.
Figure 12 Graph showing the median delay periods taking only medical providers as a
reference point among smear positive pulmonary TB patients in Amhara region.
90
80
80
median in days
70
60
50
40
30
30
21
20
10
0
Patients’ delay
Health
systems’delay
Total delay
Figure 13 Graph showing the median delay periods taking all health providers as
a reference point among smear positive pulmonary TB patients in Amhara
region.
90
80
80
median in days
70
62
60
50
40
30
20
15
5
10
0
Health seeking
period
Health
providers’ delay
Diagnosing
facility delay
Total delay
Figure 14 Pie chart showing the contribution of health seeking period
and health providers’ delay to the total delay among smear positive
pulmonary TB cases in Amhara region
18.70%
81.30%
Health seeking
period
Health providers’
delay
Finally, as a summary we have presented a diagram showing the different delay
periods starting from onset of cough until the patient is put on anti-TB
chemotherapy. It also shows the patients’ possible choices of health providers.
(See figure 15)
3.4 TB diagnosis at the private medical providers
In this study, it was found that 92 (24%) of the total study subjects were
diagnosed and referred to the TBMU for treatment by private medical providers.
According to the national TB control program guideline of Ethiopia, all smear
positive pulmonary cases diagnosed at the private medical providers must be
referred to the government TBMU for initiation of chemotherapy. But in this study,
it was found that 14 (15.2%) of the subjects after being diagnosed at the private
doctors had prescriptions of anti-TB drugs. These patients directly started anti-TB
chemotherapy by purchasing drugs at the private pharmacies.
During the
interview the subjects reported that, they took anti-TB drugs for 1-2 month. The
reason that they came to the TBMU was that the pharmacies had run out of
drugs.
3.5 Stigma
TB was found to be stigmatized among the respondents. Two hundred eighty
five (75%) believed that TB is a social stigma and 270 (70%) responded that they
would not enter others social circle for fear of not being accepted by others.
Subjects also closely linked TB and HIV. Two hundred and five (53.4%) of the
respondents said that TB is associated with HIV and of these, 179 (47%)
believed that going to a medical provider for TB test can make other people think
that the person has AIDS. Forty-eight (12.5%) said that they had a fear of being
tested for HIV when they initially reported to the medical provider. However, we
did not find associations between stigmatizing attitudes to wards TB/HIV and
patients’ delay.
Chapter four: Discussion
4.1 The distribution of the sample population
In our study, the distribution of the study population by sex showed that the
proportion of males exceeds that of the females. This is quite similar with the
notification trend at national and regional levels (11). It is also similar with the
global trend. According to Rieder (1999) in virtually all countries, notification rates
among males are higher than among females (34).
The distribution of the
population by age also showed that the majority was in the productive age group.
The mean age in the study population was 29 years. This is also similar with the
trend in general in developing countries. In developing countries, TB peaks in
young adults and it is estimated that 75% of the TB cases notified are in their
productive age group (71). The higher proportion of the Amhara ethnic group
and Christians in the sample population follows the general pattern of population
distribution for the region (12).
In this study, 40.9% of our sample population were illiterate (especially females
being more illiterate), had no defined income and were sharing a single room
with an average family size of five. This clearly indicates a very poor socioeconomic condition among the study population. As Rieder (1999) described it,
TB and poverty are strongly associated and low socio-economic indicators tend
to result in conditions that are conducive to increased transmission of tubercle
bacilli, resulting thus in a generally higher prevalence of TB infection with
subsequent increased incidence of the disease. According to the World Bank
classification, 78% of the 22 countries with the highest TB burden in the world
are low-income countries and it is known that Ethiopia is in this group (13). In
general, the current TB situation in this sample population clearly confirms the
fact that TB is a disease of lower income and lower resource countries.
4.2.1 The health seeking period and health providers’ delay
In this study, we were very much surprised to observe that many of our subjects
visited the health providers to seek for health care quite early. The delay period
from onset of major symptoms to first visit to a health provider was only 15 days.
This is in fact the same as the result documented in the Gambian study (19),
which clearly indicates that, patients seek health care early but the type of health
providers they visit varies considerably. On the other hand, 81% of the delay was
attributed to the health providers. The median health providers’ delay was 61
days. This is higher than the result reported in the Gambia (19). The long health
providers’ delay in our study might be related to the fact that the majority, 61.7%,
of the subjects initially went to the non-formal health providers to seek for health
care, in which case the likelihood of being referred to the formal health providers
for diagnosis might be less. As a result, patients might spend longer time before
they get the correct diagnosis.
The logistic regression analysis performed to analyze the possible association of
the factors between the socio-demographic factors and the median health
providers’ delay showed that the literates in general, those who lived within 10
Km radius of a medical facility and those who had visited the formal health
providers initially had lower risk of increased health providers’ delay. This might
be related to the fact that being literate, subjects might have better knowledge of
TB so that they might frequently visit health providers till they get diagnosed.
Residing within 10 Km radius of a medical facility is also an advantage to seek
for health care and of course visiting a medical provider initially might help to get
the diagnosis in a relatively shorter period of time than visiting the non-formal
health providers. On the other hand, those who were between 25-44 years of age
had experienced longer health providers’ delay. The reasons might be related to
the fact that these are within the productive age group. They are the working
force in the community. Much of their time is usually allocated for work. As a
result they might fail to give priority for health care during their illness. They might
also choose the shortest option i.e. buying drugs from the drug retail outlets to
save time. This is also evidenced in this study by 31% of the respondents
primarily visiting the drug retail outlets at the onset of the present illness.
4.2.2 Patients’ delay
Taking only medical providers as a reference point, we found a median patients’
delay of 30 days. This finding is similar with other studies that were conducted in
Botswana (18), Ghana (16), Philippines (73) and Penang (74) that showed a
median patients’ delay of 3 - 4 weeks. On the other hand, our finding is much
lower compared to the previous two Ethiopian studies that showed median
patients’ delay of 179 and 60 days, respectively (22, 23).
The reasons for our relatively shorter patients’ delay compared to the previous
Ethiopian studies might be related to the fact that we considered all levels of
health care including the lowest health care facilities (clinics & health posts) as
relevant sites for first health seeking contact for our study subjects. This may
have shortened the patients’ delay, as health posts and clinics are relatively
closer to the community compared to the health centers and hospital, which are
concentrated in major towns. Health centers and hospitals are diagnosing
facilities in the region. The previous two Ethiopian studies considered subjects
coming to these facilities only.
This relatively short patients’ delay may also further be explained by the fact that
currently there is a rapid change of health care system in the country, where
there is an increase in the participation of the private sector and expansion of the
health service to the population (11). As a result of these facts, patients might
have a better access to health care than before. Hence this may have resulted in
a short duration of patients’ delay. Therefore, we should not be surprised at
observing longer patients’ delay in the two previous Ethiopian studies that
considered health centers and hospitals as the lowest level of health care contact
for patients, in which case, the likelihood of presenting late may be very high.
Because, these facilities were inaccessible for the majority of the population in
the previous times when the studies were conducted
On the other hand, even though our median patients’ delay seemed to be
shorter, 48% of the subjects were delayed for more than 30 days prior to
presenting to a medical provider. This delay was significantly associated with
older age and distance from a health care facility. These have proved to be also
important factors in other studies that were conducted in Zambia (48) and south
Ethiopia (22). In our case, the reasons might be related to the fact that old people
are usually dependent on other persons which makes it difficult for them to visit
health facilities early. There is also generally poor access to health care for the
regions’ population.
Low level of knowledge about the symptom and treatment of TB was associated
with patients’ delay. This is in accordance with the previous study done in
Ethiopia (23), Vietnam (58) and Tanzania (50). Patients who presented with
haemoptysis had also a longer patients’ delay. In this regard, similar observation
was made in south Ethiopia (22), which suggests that patients stay at home until
they observe an alarming symptom like haemoptysis.
We observed a significant association between self-treatment at home and
longer patients’ delay. Studies conducted in other African countries such as
Ghana (16), Botswana (18) and Kenya (53) also showed the same result. Selftreatment was also found to be a common practice in the previous unpublished
Ethiopian study (57). Patients usually start treating themselves with homemade
remedies during their early symptoms. It is when the symptoms get worse that
they start seeking help from medical providers. This may be related to poor
knowledge of TB symptoms and its treatment among the population. It may also
be related to poor access of medical care to the general population.
In the present study, we did not find an association between educational status
and patients’ delay and between occupational statuses and patients’ delay.
However, the study from south Ethiopia has documented that being illiterate, a
house wife and a farmer were associated with longer patients’ delay (22). In our
study, even though these factors seemed to be associated in the univariat
analysis, their effect disappeared in the multivariate (logistic regression analysis).
This indicates that education and occupational statuses did not turn out to be
potential predictors of patient’ delay.
Other studies have documented that females took longer time to seek for health
care compared to males (16, 58). This finding could not be confirmed in our
study. In our case, the presence of integrated health service at all levels of health
care that gives more emphasis to women and children, the continuous
campaigns on polio, measles and tetanus immunizations might have helped the
women to appreciate the benefit of medical care. Mothers usually visit health
care facilities for ante-natal care, family panning and for immunization service for
their children. During these times they attend health education sessions in health
institutions. This might have an effect on their health seeking behavior. It seems
also that women in our case do not have decision making problem for seeking
health care. As indicated in the results section, 85% of the married subjects
claimed that they could decide on their own about where to go for help during
their illness. Therefore, all these reasons in our case might have helped the
women to seek for health to the same extent as men.
TB and HIV seem to be closely linked in the peoples’ mind in Ethiopia. The
current study showed that 47% of the subjects believed that TB and HIV are
associated and said that, coming to a health care facility for TB symptoms can
make other people think that the person has AIDS. Other Studies in this regard
have shown that, there is discrimination that surrounds HIV and TB patients that
may prevent them from seeking health care by going to public health care
facilities (64). However, the current study was not able to demonstrate a
significant relationship between those who expressed their feeling about the
stigmatizing attitudes towards TB and HIV and delay to coming to medical
providers. This might be related to lack of openness among the subjects in
expressing their genuine feeling about stigmatizing attitudes during the interviews
or it might also be a true finding.
4.2.3 Health systems’ delay
With regard to the health systems’ delay, our result showed a median delay of 21
days. This is more or less similar with other studies conducted in Tanzania (46),
Penang (74), New York (47) and Japan (75) that showed a median health
services delay of 3 weeks to 1 month. On the other hand, a relatively shorter
health service delay of 6 days was observed in the previous Ethiopian study (23).
Our result shows a longer delay compared to this study. This may be related to
the study setting in which case the previous Ethiopian study (23) included
subjects who presented initially to a diagnosing facility, which makes it of course
shorter as these patient can be evaluated and diagnosed on the spot. Whereas
our study population included patients that were referred from clinics, health
posts and private medical providers without diagnostic facilities. This might make
the period of diagnosis and commencement of treatment longer as it takes
considerable period of time to reach the TBMU from the time of referral.
In this study, prior attendance to a health post/clinic was a risk factor for longer
health systems’ delay. Similar finding was observed in Botswana (18). Our
finding may be explained by the fact that, health posts and clinics are run by
health assistants and junior nurses whose primary training is not to diagnose
serious diseases but to concentrate on patient care and preventive activities.
Besides this, these facilities are not equipped with the necessary diagnostic
equipments like microscopes and others. As a result, subjects might be
misdiagnosed and mismanaged. This might cause prolonged delay before
diagnosis. Prior attendance to non-formal health providers was also significantly
associated with longer health systems’ delay. This finding is a little higher than
the results documented in the study done in Dabat district in Northwest Ethiopia
(76). The common reasons for not visiting formal health providers in our study
were that, illness was considered harmless followed by health institution being
very far from home and the feeling that self-treatment was sufficient. These
responses could be related to several issues including lack of knowledge of
symptoms of TB, the perception of the relatives on how long after the onset of an
illness it is proper for a patient to still go to health institutions, lack of confidence
in modern health care and poor access to medical providers.
In the current study, those who visited private medical providers had longer
health systems’ delay. Similar finding was observed in Penang (74), where
patients who first consulted a private practitioner were the least likely to be
diagnosed appropriately. The reason for long health systems’ delay in our case
might be related to the guideline of the TB control program of the Regional
Health Bureau that strictly forbids the private medical providers to treat TB cases.
According to the guideline (12), patients diagnosed as having smear positive
pulmonary TB must be referred to the government TBMU for the initiation of antiTB chemotherapy. Patients will be re-examined and sputum for AFB will be
requested for the second time at the TBMU. Therefore, there is no doubt that all
these procedure might take additional time for patients who visited the private
medical providers prior to diagnosis and starting treatment compared to other
patients that directly went to the TBMU.
Apart from the above significant risk factors, we did not find associations
between socio-demographic factors and longer health systems’ delays. This
finding is similar with other studies conducted in countries like Zambia (64),
Botswana (18) and Penang (74) but different from Ghana (16) where women and
rural residents had longer health systems’ delay and a previous Ethiopian study
(23) in which distance to health care facility was found to be a risk factor.
With regard to medical providers’ delay, long distance to the TBMU, being
illiterate and prior attendance to a health post were risk factors for being delayed
for more than 3 months in some of our respondents. This may be related to the
fact that diagnosing facilities are found in major towns. Therefore, for those living
in rural areas these facilities might not be easily accessible, as a result, these
patients might delay longer before reaching diagnosing facilities. Patients who
are illiterate might not also go to the higher level even though they are referred.
They might not take the referral seriously. Because the general knowledge about
the consequences of late presentation might be low. Therefore, they might not be
motivated to go to the next level of health care earlier compared to the literates.
With regard to the relation between prior visits to health posts and medical
providers’ delay, it might be explained by the fact that, health posts are not well
equipped with well-qualified health professionals and equipment to diagnose TB
compared to health centers and hospitals. Therefore, patients might be
misdiagnosed or mismanaged resulting in longer delays.
4.2.4 Diagnosing facilities’ delay
As for the diagnosing facility’s delay, the present study showed a median
diagnosing facilities’ delay of 5 days. This is a little bit higher than the Gambian
study that showed a median diagnosing facilities’ delay of 0.2 weeks (22). This
may be because of the fact that the Gambia is a small densely populated country
with 87% of the population having a good access to health care within a 3 Km
radius (19), unlike Ethiopia where the health service coverage is not beyond 50%
(3). But still, we have a feeling that, the diagnosing facilities’ delay observed in
this study is not that wide. We would say that patients get their diagnosis and
commence their treatment within a reasonable period of time as long as they
manage to reach the TBMU.
Patients in this study were shopping for treatment for a considerable period of
time prior to diagnosis. The average (mean) number of medical providers visited
was two. This is excluding repeated visits made to the same providers. Our
finding is different from the Gambia where patients visited 4 medical providers
prior to diagnosis. This might show that our patients are referred earlier to the
TBMU or patients might not frequently shop for treatment from different medical
providers, as the numbers of private providers are relatively small compared to
the Gambian study, or patients might stick all the time to the first private medical
provider till diagnosis or referral.
4.2.5 Total delay
The median total delay observed in this study was 80 days. This is different from
the previous south Ethiopian study (22) that showed a median total delay of four
months. However, a more or less similar finding was observed in other countries
like Gambia (19) Botswana (18), and Penang (74) that showed a median total
delay of 8.6 and 12 weeks, respectively. The reason for our relatively shorter
total delay compared to the previous south Ethiopian study may be related to the
increase in DOTS coverage in the region. Currently, 51% of the region has been
covered by DOTS unlike the previous years where DOTS coverage was very low
(12).
The risk of increased total delay was also higher in those with education less
than 9th grade and in married couples compared to those above 9 th grade and the
singles, respectively. In this regard, similar finding was observed in the previous
south Ethiopian study (19) and may be explained by the fact that subjects with
lower level of education might have poor awareness regarding the symptoms and
treatment of TB and married couples might have shortage of time to care or give
attention for themselves, as they are usually responsible for the entire family.
In this study, far distance to patients’ home and low-level knowledge about the
symptoms and treatment of TB were also associated with increased median total
delay. This result is consistent with the findings in Botswana (18), southern
Ethiopia (22) and Vietnam (58). As has been described in the results section, the
majority (57 %), of the patients at the onset of their illness related their symptoms
to other diseases. Moreover, most of the study subjects believed that, the
symptoms would disappear by themselves. This clearly shows a lack of
knowledge among our study subjects with perceptions and practices that might
delay the patient. Therefore, we were not surprised to observe this significant
association in our study. The same might be true for the association observed
between self-treatment and increased total delay.
In general, we have seen from the above discussion that delay in diagnosis has
been studied in many countries. In all of these studies, a range of conflicting
differences on the lengths and risk factors of diagnostic delays have been
documented. Likewise, the present study showed similarities and differences in
the choice of first health providers, and in the lengths and risk factors of the
different delays when compared to other studies. This may due to various factors
related to the study setting, the method of estimating the time from onset of
symptoms to seeking medical care and the characteristics of the study population
under which our study was conducted.
With regard to the choice of first health provider, in almost all the previous
studies reviewed, only first contact with a medical provider was taken as a
reference point when analyzing delays. However, one study from the Gambia
(19) incorporated all health providers in this regard. In the current study, all
health providers were considered as a reference point for analysis. This is
because, in Ethiopia, all health providers are assumed to be potential sources of
health care for TB patients.
4.3 The role of knowledge, perception and behavior in diagnostic delay
In the health seeking behavior model, the process of care seeking begins with
“symptoms recognition” (77). Likewise, in the present study, we observed an
alternative explanation for the symptoms of TB among the respondents. In the
initial period of the onset of cough, 61.4% of the respondents attributed their
cough to other conditions like nefas (bird). Nefas/bird in Amharic simply means
wind blown to the chest. It is also seen in relation to exposure to the cold (any
cold element, like the cold water). It is a traditional phenomenon but not a
scientifically explained disease. Similar finding was observed in a recent
unpublished qualitative study that was conducted in Addis Ababa the capital of
Ethiopia, which showed that the first symptom of TB (cough) was often not
directly related to TB. The patients’ belief was that they had bird (57). Other
studies conducted in Colombia, attributed TB symptoms to flue (52). In Malawi
TB symptoms were attributed to tsempo, mphumu or modulo which is a
traditional folk condition believed to be caused by careless sexual behavior or
adultery (54).
In Ethiopia, there is a strong belief that nefas /bird causes samba nekersa
(pulmonary TB). Especially a narrowly opened window (while traveling in a car or
sitting in a room) is believed to be dangerous as a sharp wind could come
through it with a power enough to penetrate the chest and then directly to the
lung causing TB. It is a common phenomenon to observe many people taking
preventive action against nefas/bird. For example, when people are traveling by
a taxi or a bus, windows are usually closed. My own experience confirms this. As
I was frequently traveling for supervision purpose during the data collection
period of this study, I some times used public transport like bus. In the bus, we
were sixty traveling 470 Km together. From the time we departed till we reached
at our destination, all the windows were closed. As I suffered from sever
headache and suffocation, I tried to open the window once, every body shouted
at me saying that, "You guy! nefas is coming! Shut the window! Please! Please!"
then I immediately closed. The only time we got fresh air was when the bus
stopped for breakfast and lunchtime. This clearly shows that, the wrong
perception among the people is causing them to behave in the wrong way. All
this may be related to lack of awareness regarding the causes of TB among the
population.
According to the health seeking behavior model, the first step in symptoms
recognition includes also identifying the causes and the severity of symptoms
(77), in the present study, we found that patients with haemoptysis had longer
duration of illness compared to those with out haemoptysis. It seems that
patients wait for long time until they recognize sever symptoms like
(haemoptysis). The reason for this may be related to the subject’s perception of
severity of diseases. Patients may assume that, when the cough gets severe, like
accompanied with haemoptysis or dyspnea, it is an indicator that the nefas/bird
has penetrated the lung, at this time they may be motivated to take one step
forward in the health seeking behavior, i.e. they might immediately go to a
medical facility. As severe weight loss and severe cough were strongly related
with TB in other countries (52), haemoptysis might have been considered as the
major sign of TB not cough alone by some of our respondents.
Following the health seeking behavior model (77), the next step was consulting
the symptoms with laypersons and making a decision about treatment. Likewise,
our result showed that the majority (88%) of the subjects consulted family
members regarding what to do in the next step. They also decided to use selftreatment (home made) like variety of hot fluids and steam inhalation. The
practice of self-treatment in response to the initial symptoms is also evidenced in
the recent un published Ethiopian study where patients were taking different
homemade remedies to relieve their cough (57). Studies conducted in other
African countries such as Ghana (16), Botswana (18) and Kenya (49) showed
also the same result. Other studies from Pakistan (74) and Malawi (62) reported
that beliefs about the etiology of TB were associated with the health seeking
behavior. For example, people who believe that TB is caused by supernatural
forces would seek care from folk and traditional healer (62). According to
Kleinman, this seems a universal phenomenon in which case the response to
early symptoms of disease as well as their action upon it is within “the popular
sector” of the health care system (77).
Kleinmans (1980) described health care as a local cultural system consisting of
three overlapping parts; the popular, the professional and the folk sector. The
popular sector is the largest part of the system, consisting of a matrix containing
several levels; the individual level, the family level the social network and the
communities’ beliefs and activities. It is within this sector that, illness is first
defined and different health care activities initiated. It is also within this sector
that a large percent of illness episodes are managed. Self treatment by the
individual and his or her family is the first therapeutic intervention people make
use of in a wide range of cultures, and when people turn to folk medicine, and/or
modern western medicine, their choices are often based on the belief and the
value orientation of the popular sector (77).
Generally, from the above explanation, we can see that, initially patients had
wrong perceptions regarding the causes of TB. As a result, they attributed their
illness to other diseases and stayed at home taking self-treatment. Some of them
even stayed till they noticed an alarming symptom like haemoptysis. This has
resulted in a considerable delay before diagnosis and was clearly shown in
findings section by the association between self-treatment and patients’ delay
being significant.
4.3. The contribution of the different health providers in diagnostic
delay
4.3.1 Drug retail outlets
In this study, drug retail outlets were very much utilized among TB patients in the
early period of their illness. The result showed that 31% of the study subjects
used self-medication at the onset of their symptoms. Buying drugs from drug
retail outlets might indicate a preference for the more convenient way of getting
medicine. Previous studies from Northwest and southern Ethiopia reported a
higher prevalence of self-medication with a proportion of 24 and 27.6%,
respectively (79). Other studies in Mexico (75), India (80) and China (81) showed
30%, 34.5% and 32.5% prevalence of self-medication, respectively. However,
the current study might not be directly comparable with these studies as one
disease entity is investigated while the other studies considered all diseases
symptoms. On the other hand, the major symptoms that led patients to selfmedications in those studies were headache, fever and cough which are also
often symptoms experienced by TB patients
For self-medication, the study subjects reported that they used antibiotics like
ampicillin capsules and penicillin injections and said that they got improvement
with their cough after taking these drugs. Other studies (62) have noted that
respiratory symptoms in patients with microbiological confirmed TB can
temporarily subside after a course of antibiotics. This may be due to some
antibiotics having a short mycobacteriostatic action or because of bacterial super
infection. Whatever the reason may be, symptomatic improvement after a course
of antibiotics may contribute to a delay in diagnosis as has been found in other
parts of sub Saharan African countries (62).
Currently in Ethiopia, following the new health sector reform, quite a number of
drug retail outlets have been opened (3). Therefore, it is relatively easier to buy
drugs from drug retail outlets rather than going to a medical facility, which in fact
may cost additional money including transportation cost. One can find different
kinds of antibiotics in the drug retail outlets. Sometimes, even anti-TB drugs
might also be found (12) indicating the common practice of selling drugs without
prescription. Even though there is a law that forbids the selling of such drugs
without prescription. It seems that the guideline of the regional health bureau is
not being respected. As WHO noted, self-medication provides a cheep
alternative for people who cannot afford to pay a medical practitioner. Thus selfmedication is often the first response to illness among people with low income
(83) and all these might contribute to patients’ delay.
4.3.2 Traditional health care providers
Traditional health care providers were among the sources of health care visited
by the study subjects. The findings showed that 27% of the subjects initially
visited traditional health care providers. This is nearly similar to the finding of the
study done in Malawi (62) where 30 % of the study subjects initially visited
traditional health care providers, but lower from Tanzania where the proportion of
first visit to traditional health providers was 39% (50).
In Ethiopia, modern health service utilization appears to be generally low. An
earlier study which summarized the health profile of 52 districts reported that the
per capita annual number of visits was 0.23 visits over all, with the mean for
urban double that of the rural district (84). The vast majority of the Ethiopian
population, therefore, still depends on traditional medicine and its practitioners.
The 1982- 1983 rural health survey revealed that more than half of the health
service seekers relied on traditional healers. In Addis Ababa, which is one of the
highly urbanized centers of the country and where modern health services are
relatively accessible, 26% of the representative populations were shown to have
used traditional medicine (9). According to the 1999 World Bank report, more
than 80 % of the people use herbal remedies as their first choice for the day
today health care needs (85).
Traditional medicine remains of paramount importance to the Ethiopian people
and
Commands a great deal of acceptance among the majority of the population. The
widespread use of traditional medicine in the country among both rural and urban
population could be attributed to the following major factors (9).
1.
Acceptability: Use of medicinal plants constitutes part of the cultural
heritage representing the identity and the uniqueness of our society.
Traditional medicine is a component of the local culture. People resort to it
even when there is demonstrably better alternative care.
2
Accessibility and affordability, as compared to modern drug. Medicinal
plants are often within easy reach and affordable both in terms of financial
resources and time when compared to modern drugs dispensed in
remotely located health institutions
Moreover, in Ethiopia, it is a common phenomenon that patients who have visited
traditional health providers normally do not seek formal health care from medical
providers till they finish the ordered herb/other remedy by the traditional health
provider for a given period of time. There is also a cultural belief that, the
herb/other remedy given by the traditional health provider would not work if one
took injections or tablets from the modern medicine at the same time. This and
the above mentioned reasons might delay patients for a considerable period of
time before seeking health care from the formal health providers for diagnosis.
4.3.3 Private medical providers
In the present study, 24% of the subjects had their diagnosis from the private
medical providers and were significantly delayed compared to those directly
diagnosed in the TBMU. Even though TB treatment is offered exclusively in the
public sector, many studies have revealed that patients tend to be under private
care for a considerable length of time before TB is diagnosed and patients are
referred to the TB service. For example, in Sao Paulo city (86) where TB care
largely takes place in the public sector, an analysis of the place of first diagnosis
and the extent of delay in diagnosis showed that in about 20% cases the
diagnosis was first made in the private sector. The mean delay in diagnosis was
12.5 weeks. In the Kenyan study (88), 90 % of TB suspects claimed that they
had attended private health care facility yet 65% had neither a chest radiograph
taken nor their sputum examined. A study of TB patients and practitioners in
private clinics in India (89) showed median delay in diagnosis of about 2 to 3
weeks among urban and rural patients after they sought help at private clinics.
About 33% of the urban patients and 36% of the rural patients had not been
diagnosed even after 4 weeks of seeking help. Another study in Vietnam (89)
showed that patients who had first turned up to a private physician were more
likely to have a long provider delay compared to people who had first turned to
the national TB control program. This might show that private providers follow
poor diagnostic practices leading to long delays in diagnosis.
In the present study, it was also revealed among some patients that, private
medical providers instead of referring suspected/confirmed cases of pulmonary
TB to the TBMU, they prescribed anti-TB drugs and informed the patient to
directly purchase the drugs from private pharmacies. This practice is clearly
against the guideline of the national TB control programs, which indicates that
there might be poor control of the private medical providers by the district, zonal
or regional health bureau. The availability of anti-TB drugs in the private
pharmacies might lead to irrational use of drugs, which ultimately can result in
the emergence of drug resistant TB in the region that will make the TB control
program unsuccessful (12).
4.3.4 Local injectors
The study showed that considerable number (3.6%) of the subjects visited local
injectors during the onset of their illness. According to the ANRSHB (2002) there
exists a practice both among the private practitioners as well as the local
injectors to give injections like penicillin, vitamins and saline water for patients
with nefas/bird. Similar observation was made in the previous unpublished
Ethiopian study where saline water was extensively given as injections (57). The
use of injection is also high in other sub-Saharan African, Middle East and South
East Asian countries by the informal private providers (90).
Local injectors in Ethiopia are part of the health care system both in the urban
and rural areas. They may or may not have medical education but they
administer injections to patients presenting to them. They are not legally allowed
to practice as a local injector in any way. The procedure is usually performed
behind closed doors.
Ethiopian patients especially in rural areas strongly prefer injections to tablets.
This may be related to the belief prevailing among the population that, “injections
radically remove the disease compared to oral medications.” Patients might
understand the pain that they feel during the injection procedure as a sign that
the disease is gone forever. Many patients are dissatisfied if medications are not
given while diagnostic tests are pending or the illness does not necessarily call
for medication (91). Therefore, due to the strong belief in injection among the
population, considerable numbers of people might go to local injectors for their
illness. As a result a placebo effect may cause delay in diagnosis among TB
patients.
Strengths of the study
1. Relatively large sample size was taken
2. We were able to meet the intended sample size within the study period
3. Very close supervision was conducted and the data collection activity was
successfully accomplished
4. We did additional analysis on other variables besides our original
objectives
Weaknesses of the study
1. We were not able to collect data on sputum grading. Because, most of the
TBMUs were not doing it during the study period. Therefore, we were not be able
to analyze the infectivity versus the duration of illness
Limitations of the study
There are limitations to our study. One of the limitations is related to the
interviewers. We used health professionals to conduct the interviews. In this
regard, we have a suspicion that subjects might underestimate the duration of
stay at TBMUs for fear of being mismanaged by health professionals during
subsequent visits.
The second one is related to selection bias. We included patients presenting to
government health care facilities. Other pulmonary TB patients who might
probably go to private medical providers and who stayed at home during the
study period were not included in our study. Here it might be difficult to consider
our study result as representative of all smear positive TB patients at national or
regional level. Because, the nature and behavior of patients that were not
included in our study might vary. However, we have a strong belief that, our
sample is representative of the smear positive pulmonary TB patients presenting
to TBMUs in Amhara region as we managed to select the representative health
facilities. We were also generally able to interview 35% of the total diagnosed
cases in the region during the study period.
The other problem is related with the recall of the duration of illness. We
interviewed our subjects retrospectively to tell us what happened during the initial
period of their illness. Therefore, when we see it from the angle of validating the
duration of illness, it may suffer from recall bias in some of the respondents as
they might not be able to tell us the exact date of onset of their illness. However,
we have put in our maximum efforts to minimize this problem. We specifically
asked the onset of the major symptoms and how long after these symptoms they
consulted a health provider. As described earlier 96.4% had cough that is likely
to be remembered by the subjects. Moreover to estimate the date of onset of
symptoms, we have used local calendar listing the main religious and national
days. As Christianity is the predominant religion in the study area, it is expected
that the people might remember these days. As shown earlier in our results
section, the length of recall period for the majority (69%) was below 2 months.
Therefore, we might say that, the possibility of recall bias is very much reduced
though it is admittedly difficult to eliminate it altogether.
As a data collection tool, we used structured questionnaires. We had also some
semi-structured questionnaires. We believe that the tools were appropriate in
gathering the information for our research questions. These methods are the
most commonly employed methods used to gather information for crosssectional studies where the numbers of respondents are usually large (92).
However, there are some disadvantages of using these tools. Like for example,
the interviewer may inadvertently influence the respondents, important
information may be missed, because spontaneous remark by respondents is
usually not recorded or explored, and open-ended questionnaires are difficult to
analyze. To control these problems, all the interviewers were instructed to take
all the necessary care during interviewing to make the respondents as free as
possible with regard to responding as fully as they felt, the interviewers
comprised also both males and females (30% of the interviewers were females).
All were from the same ethnic group who were well aware of the socio-cultural
issues in the study area, they were also local residents who spoke the native
language, and in analyzing the open ended questions, after the data were
collected, we went through all the possible responses and carefully categorized
them for analysis.
Chapter 5: Conclusions & Recommendations
Generally, our study showed that there was a significant delay in the initiation of
anti-TB chemotherapy among smear positive pulmonary TB cases in Amhara
region. This delay was to a large extent attributed to the long health providers’
delay. Eighty one percent of the delay was due to the health providers, and the
overwhelming majority (61.7 %) of pulmonary TB patients in the region attended
non-formal health providers as their first preference when symptoms initially
started.
To our surprise we found that patients seek health care relatively early and the
type of health provider they visit vary greatly. By saying this, we are not totally
denying the contribution of the patients’ delay to the total delay, as 48% of the
subjects took more than 30 days prior to reporting to the medical providers. The
major factors associated with the patients’ delay were related to the wrong
perception regarding the causes and symptoms of TB and related behaviors
(self-treatment), lower access to medical providers and prior attendance to the
non-formal health providers. On the other hand, the major factors associated with
the health systems’ delay were prior attendance to the health posts and private
medical providers. These were the potential risk factors affecting patients’ and
health systems’ delay in the diagnosis of pulmonary TB in Amhara region. The
median diagnosing facilities’ delay observed in this study is relatively short
though it still needs to be reduced further. It indicates that the TBMUs are doing
an encouraging job in the region.
Over all, considering the high magnitude of delay in the region, the abovementioned factors should be an area of focus for the regional health bureau to
start acting on them so as to lower down the current unacceptable long duration
of pretreatment period and reduce transmission of TB in the community.
Therefore, the following recommendations are made based on our findings.
Recommendations
1. There should be an access for a simple and rapid diagnostic test for TB at
the lowest health care facilities (health posts/clinic) so as to reduce the
health systems’ delay.
2. A mechanism has to be created to work closely with all non-formal health
providers including drug retail outlets, traditional healers, herbalists and
religious healers in the region on how to identify TB suspects and instant
referral. This could be done through workshops, seminars, conferences
and trainings organized by the RTLCP.
3. It is important that health workers working at the peripheral health care
facilities be more alert to the possibility of pulmonary TB in patients with
respiratory symptoms. So that it can be diagnosed early and treated
promptly to reduce patient morbidity as well as to limit its spread in the
community. Efforts should be made to improve the diagnostic skill and the
awareness of TB among all health workers particularly, nurses and health
assistants since most patients first seek treatment from them. Education
on the clinical identification of suspects, public health aspects of TB and
the importance of referral should be intensified at undergraduate level in
the nursing schools. There should also be continuing medical education
about TB in the form of lectures, conferences or seminars to other health
workers such as health officers and medical doctors working at the
diagnosing facility level to maintain a high index of suspicion for TB and
perform appropriate diagnostic tests. These all might be organized by the
RTLCP, NGOS and professional organizations working in the region
4. Well-organized and integrated information, education and communication
(IEC) program has to be put in place to raise the awareness of the
population in general on the symptoms and treatment of TB and facilitate
prompt utilization of the available health service. Using the available
media such as the regions radio and newspaper for the dissemination of
health information to the general population should be given due
emphasis.
5. Increased knowledge of patients’ health seeking behavior and their selfperception of disease is useful for health workers and should have
implications for health education messages
6. In this study, far distance between home and health care facility has
affected the early initiation of treatment. Therefore, efforts should include
improving easy access of diagnostic facilities to the population by further
decentralizing the TB diagnostic and treatment services to the periphery
are necessary. Besides this, there should be a mechanism to collect
sputum samples from the remote areas. In this regard, incorporating the
community health workers might be important.
7. The regional TB control program has to device a system for the private
sector to effectively participate in TB control activities. This could help in
reducing health systems’ delay. Moreover, it is important to give training to
the private medical providers about the clinical and public health aspects
of TB.
8. Regular and intensive supervision including the government and the
private medical providers should be strengthened to assure the quality of
care given to TB patients. The supervision should also include all drug
retail outlets aiming at controlling the availability of anti-TB drugs in the
private pharmacies.
9. In this study, we observed that due to the wrong perception of the causes
and symptoms of TB, patients were treating themselves for a considerable
period of time prior to presenting to medical providers. Besides this, the
health service coverage in the region is low. Therefore, with only using
passive case finding, it might be difficult to reach as many pulmonary TB
patients as possible. Therefore, we believe that it is important to
incorporate active case finding, like contact tracing in the current TB
control system in the region.
4.12 Further research implications
1 Further study should be conducted to see the relation between
longer pre-treatment delays and its effect on treatment outcome on
the already studied patients.
2 The magnitude of individuals having suspected symptoms of TB but
did not seek treatment should be explored to better understand the
impact of diagnostic delay in the case finding activity in the region.
3 As described in our introduction section, the report of the regional
state health bureau has revealed that the case holding activity in
the
region
has
currently
encountered
challenges
in
its
implementation. Some of the challenges include poor recording and
reporting, poor patient follow-up, high staff turn-over and in general
poor management of DOTS. Therefore, looking into the quality of
TB control in the region might help to understand the underlying
problems and improve the TB control program in the region.
4 The role of private medical providers in TB diagnosis in the region
needs to be assessed. This will help to generate information that
can be used for designing better cooperation between the
government and the private sector in TB control in the region.
5. In this study we have observed that some of the respondents were
able to access anti-TB drugs from various drug retail outlets. We
know that this is against the guideline of the NTCPs as it can lead
to irrational use of anti-TB drugs. Therefore, we think it is wise to
conduct a baseline survey for assessing anti-TB drug resistance in
the region.
6. Information regarding TB and HIV co-infection is lacking in the
region. In the present study we found 47% of the TB patients
associating TB with HIV. Therefore, looking into the magnitude of
HIV/TB co-infection in the region might be useful in generating
information that can be used to plan a coordinated intervention
strategies for both diseases.
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Appendix 1
Questionnaire for patients
This is a questionnaire prepared for assessing patients’ and health systems’ delay in the
diagnosis of pulmonary TB in Amhara region Northwest Ethiopia. It will be used as a
tool for our research which is part of the partial fulfillment of the master of philosophy
degree in international community health at the University of Oslo, Norway.
We will be asking you about socio-demographic and health services issues which are
related with your present illness. In this regard, your honest answers are very valuable
and will help to improve the TB control program in Amhara region. It is not bad or
embarrassing if your answer is I do not know or I do not remember, since we need to find
out what the people know not yet know in order to improve the TB control program in
the region.
Solomon Abebe, M Phil 2nd year student
Department of General Practice and Community Medicine,
Section for International Health
University of OSLO, Norway
Participant number___________________Date of
interview________________________
Date of interview_____________________ Name of the health
facility___________________
Name of the interviewer_____________________
A. Personal and socio demographic information:
1(GENERAL)
1.1 Age in years:_____________________ 1.1.1 Address: __________________
1.2 Sex:
1.
1.3 Literacy:
Male
□
□
2. Female
1.Unable to read and write
□
3. Secondary (9-12)
□
2.Primary (1-8)
□
4. College
□
5. Other, please describe______________________
1.4 Occupation: _____________________________________
1.5 Marital status:
Widowed
1. Never married
□ 2.Divorced □ 3.Married□ 4.
□
1.6 Religion:
1. Christian
□
.
2 Muslim
□
3.Other________________
1.7 Do you have children?
1. Yes
□
2. No
□
If yes, how many? _____________________________________
1.8 Can you take decisions on your own where to go for help during your illness (for
women)?
1. Yes
□
2. No
□
1.8.1 If no, whom do you consult in the family? ______________________________
1. 9 Distance from home to the health center/hospital______________ Km/Hrs of
walking distance
1.10 Type of house used for dwelling
1. Hut
□ 2. Corrugated sheet iron roof □
3. Other, please describe_______________
1. 11 Number of rooms in the
house____________________________________________
1.12 Number of people living in the
house_______________________________________
1.13 Income
1.Regular
□ 2. Irregular □
If regular, how much per month? ___________________________Birr
For those who are self-employed ask the average earning per month and take this
average as an average monthly income.
B. Current habits:
2. Do you smoke cigarettes?
1. Yes
□ 2. No □
If yes, how long have you smoked? __________________________Years, months
3. Do you drink alcohols?
1. Yes
□
2. No
□
3.1 If yes, how long have you drunk__________________________________
4. Do you chew khat?
1. Yes
□
2. No
4.1If yes how long have you chewed__________________________Years, months
C. Current illness/ health provider visit:
5. Date of onset of the present illness: _____________________________
6. Which of the following symptoms did you suffer?
Symptoms
Yes
No
Duration of
□
symptoms in (days/
Weeks/months/years
Cough
haemoptysis
Fever
loss of appetite
chest pain
Tiredness
weight loss
Night sweating
Other symptoms, please specify_____________________________________________
6.1 Which of the above symptoms most urged you to seek for medical care?
________________________________________________________________________
6.2 What did you think of the type of disease you have?
_______________________________
6.3 If the answer to question number 6.2 is nefas /or bird, do you think nefas causes TB?
1. Yes
□
2.No
□
6.3.1 If yes, how does it cause TB? Please describe
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
________
6.4 Did you consult a person about what to do/where to go for help at the onset of the
present illness?
1. Yes
□
2. No
□
6.4.1 If yes, whom did you consult? Please
describe_________________________________________________________________
To the interviewer: If the patient can not remember the name of the drug, please ask the
color and shape of the
drug._______________________________________________________
6. 5. Did you first try to treat the illness (cough) by your own using home made
remedies?
1. Yes
□
2. No
□
6.6 If yes, how did you try to ease the symptom (cough)? Please, describe
________________________________________________________________________
________________________________________________________________________
6.6.1 How long did you take these remedies? ___________________________days or
weeks
6.6 Did you first buy any drug from any drug retail outlet to cure your illness by your
own
1.Yes
□
2.No
□
6.6.1 If yes, what kind of drug did you take?
Please describe___________________________________________________________
6.6.2 Did you get improvement after taking this drug?
1.Yes
□
2.No
□
7. Which of the following health providers did you first visit?
Public health care facilities
Yes
Date of first
Duration of
visit
cough from
date of onset to
first visit in
Number
(days, weeks,
month/year)
7.1
Clinic /health post
7.2
Health center (Government)
7.3
Hospital (Government)
7.4
Lower level clinic (private)
7.5
Mid level clinic (Private)
7.6
High level clinic (private)
7.7
Local injectors
7.8
Pharmacies, drug stores, open market
drug sellers, others
7.9
Traditional health providers (herbalists,
religious healers, holy water, wodaja,
others.
For 7.8 and 7.9 please underline the specific health provider.
8. If the patient took more than 3 weeks before he/she visits a medical provider, what was
the most important reason (as perceived by the patient) for taking such a time?
1. Illness considered harmless
□
5. Lack of money
□
2. The health care facility is far
□
6.Cold weather
□
3. Self-treatment considered sufficient
□
7. Fear of being tested for HIV
□
4. Fear of being diagnosed as TB
□
8. Lower belief in modern medicine
□
Other, please
describe_______________________________________________________
9. How many times have you visited a government medical provider for your symptoms
before it was confirmed to be TB?
□ 2.Twice □ 3.Three times □ 4. Four times □ 5. Five times □ 6. More
than five□.
1. Once
9.1Were the above visits with the same or different medical providers?
□
1. Same
2.Different
□
9.2 Did the doctor ordered investigations for you at that time of illness? 1. Yes
□2.No
□
9.3 If yes, which of the following investigations were done?
Sputum examination
Chest x- ray
□
1.Yes □
□
2. NO □
3. I do not remember□
1. Yes
2.NO
10. How many times have you visited a private medical provider for your symptoms
before it was confirmed to be TB?
□ 2.Twice □ 3. Three times □ 4. Four times □ 5.five times □ 6. More
than five□.
1. Once
10.1Were the above visits with the same or different private medical providers?
1. Same
□
2. Different
□
10.2 Did the physician at the private medical provider ordered investigations for you at
that time of illness?
1.Yes
□
2. NO
□
10.3 If yes, which of the following investigations were done?
□
1.Yes □
Sputum examination
1.Yes
Chest x-ray
□
2. NO □
2. NO
□
I do not remember
11. Where did it become for the first time clear that the disease is TB?
1. TBMU
2. Private medical provider
□
□
D. If the diagnosis of TB was made at the private medical
providers
12. What did the doctor/ the health worker at the private medical provider do when he/she
confirmed that your illness was TB?
□
□
□
1. He/she referred me to the TBMU with slides
2. I was referred with out slides
3. I was given a prescription and sent to a pharmacy to buy anti TB drugs
Other, please describe________________________________________________
12.1 If given prescription,
Did you get the drugs in the private pharmacy?
1. Yes
12.2 If yes, did you purchase?
□
2. No
□
□
2.No
□
1. Yes
If no, why not?
1. It was expensive
2. I thought it was fake
□
□
3. Other Please describe ______________________
13. How long did it take from the time you were referred by the private medical provider
till you first reported to the TBMU?_______days/weeks.
12.4 When you reached at the government (TBMU) with your referral, what did they do?
1. Re examined me
2. Requested AFB
3. They accepted my slides and started me on treatment
4. Other, please describe________________________________
□
□
□
14. How long did it take from the time you first reported to the TBMU till you first
started anti-TB drugs? ____________days/weeks
15. How long did it take from the time you were referred by a medical provider till you
first started taking the anti TB drugs?_________________________days/weeks.
E. Diagnosis made at theTBMU
16. Date of first visit to the TBMU? __________________________________________
17. How did you decide to visit the TBMU? __________________________________
1. Referred by HP/clinic
□
Date Referred________________
2. Self-Referred
□
Date referred_________________
3. Referred by private
□
Date referred_________________
4. Others, please specify, ___________________________________________________
18. How long did it take since you came to the TBMU till you were first seen by the
doctor/ health worker? _________________________ days/weeks
19. Date the patient was first seen by the doctor /health worker
checked__________________
20. How long did it take from the time you were first seen by the doctor/ health worker
till you first received the sputum request for AFB? ___________days/ weeks
21.1 Date first sputum for AFB /x-ray was requested
checked_______________________
21.2. Date the patient gave the sputum for
AFB___________________________________
21.3. Date sputum Result was registered in the laboratory registration book
checked______________________________________________________________
22. Grading of sputum (Lab. register) scanty
1.+1
□
2. +2
□ 3. +3 □
23. How long did it take from the time you gave sputum for examination till you received
the
results?_________________________________________________________________
23.1. Date the patient first received results checked_____________________________
24. How long did it take from the time you were notified to have TB (received AFB
result) till you started the first Anti- TB regimen? ______________________ days/weeks
24.1 Date Anti-TB treatments were ordered checked (from the patient card)
____________________________________________________________________
24.2 Date of registration for treatment (from district registry book)
Checked_____________________________________________________________
25. How long did it take from onset of the present illness till you first started anti TB
chemotherapy? ____________________________ (days, weeks, month)
26. How much money did you pay for all the consultations & medications from onset of
cough till the diagnosis of TB? _____________Birr.
E Knowledge of TB:
27. Have you heard, known something about pulmonary TB? For example, TB causes
chronic cough? Haemoptysis?
1. Yes
□
2. No
□
27.1. If yes, where has the information come from?
□ 2. Neighbors □
5. Media □
1. Family
3. Friend
□
4.Health workers
5. Books (reading)
□
□
Other, describe_________________________________________________
28. If TB is treated, can it be cured?
1. Yes
29. What do you think are causes of TB?
Possible causes
No
Witchcraft
Poverty
Bacilli
hard work
Sexual overindulgence
Malnutrition
Unventilated home
Living together with
untreated TB patient
HIV
other causes
□ 2. No□
3.I do not know
yes
31. Do you know any danger if a TB patient is not treated? 1.Yes
□
I do not know
□
2. No
31.1 If yes, what is it?
For the patient, ____________________________________________
For the people around, ________________________________________
□
32. Do you know that the drugs are available free? 1. Yes
□
□ 3. I don't know
2.No
□
33. How long is TB treated?
1. 1-year
□
6-8 months 2.
□
I do not know
□
3. Other, please describe__________________
F. Stigma:
34. Do you feel TB is a social stigma?
□
1. Yes
□
2. No
35. Before you came to this health facility, was there any fear in your mind that you
would be tested for HIV?
1. Yes
□
2. No
□
36. Do you think people will avoid your company because you are a TB patient?
1. Yes
□
□
2. No
37. In your opinion going to the health center for TB test can make other people think
that you have HIV/AIDS?
1. Yes
□
2.No
□
1. Yes
□
2.No
3. I do not know
□
38. Does TB has an association with HIV?
□
3. I do not know
□
39. Do you fear not to enter others social circle in fear that they will not accept you?
Yes
Thank you!!
□
□
No