Amref Health Africa International Conference
24-26 November, 2014
Nairobi, Kenya
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Assessment of Health Management Information
System (HMIS) Performance at Health
Facilities of Afar Region, 2013
Presenter: Mesfin Ayeta
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Presentation Outline
1. Background
2. Methods
3. Result and Discussion
4. Conclusion
5. Recommendation
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Background
 In developing countries, the collection, compilation,
analysis and utilization of health data remains to be
practically major problem.
 In Ethiopia, the HMIS is characterized by burdensome
data collection and inadequate staff skill and also the
information flow is fragmented (WHO, 2007).
 This resulted in redundant and conflicting reports and
poor quality of data in terms of accuracy and timelines.
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 In Afar region, despite some improvements were
observed; the problems on HMIS performance is still
there.
 However, there are not scientific evidences showing
the possible determinants of HMIS performance in the
region.
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Objectives
General Objective
 To assess the status of HMIS performance at health
facilities level and identify its determinant factors.
Specific Objectives
 To assess the status of HMIS performance at health
facilities
 To find out challenges and best lessons of HMIS
performance in health facilities
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Methods
Study Design
 A cross-sectional study design was carried out.
Data Source
Study Unit
 Health facilities
 Service providers
 Patients/Clients records
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Sample Size Determination
The Sample size is calculated based on the study unit:
Health facility:
 Rule of thumb sampling method was used. The rule
states, if the number of units are less than 50, take a
30-50% sample.
Record Review:
 Single Population Proportion formula was used. 384
Individual records were reviewed.
Health Professionals:
 All the selected health facilities health workers.
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Data collection instrument/Tools
 Interview using questionnaire
 Observation using checklist
 Record review
 Self-administrative Questionnaires
 In-depth Interview
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Data analysis
 SPSS version 20 was used to analyze quantitative data.
 Tables, figures and frequencies
 Logistic regression
 Thematic analysis for qualitative data
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Results and Discussion
Description of Respondents
Variables
Frequency
Respondent’s qualification
MD/HO
clinical nurse/midwife
Para medicals
4 (3.2%)
80 (63.5%)
42 (33.3%)
Responsibilities of Respondents
Head of facility and units
Clinical health service providers
Para medicals
15 (11.9%)
79 (62.7%)
32(25.4%)
HIMIS Training
Received
Not received
40 (31.7%)
86 (68.3%)
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Existence of Performance Monitoring Team (PMT) and
HMIS guideline
69%
69%
80%
60%
40%
31%
31%
20%
0%
Present
PMT
HMIS guideline
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Presence of HMIS focal person and Supervision at health
facilities
80%
71%
65%
60%
29%
35%
40%
20%
Not exist
0%
Exist
HMIS focal
person
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Supervision
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HMIS process and practice at Health facilities
Frequency
Variables
Yes
Checking reports before
sending to the next level?
41.7% 35.4%
22.9%
Use standardized set of
indicator
29.2% 41.7%
29.2%
Send HMIS Report based
on scheduled
12.5% 87.5%
Health facilities received
written feedback on HMIS
performance
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No
20.8% 39.6%
I do not Know
37.5%
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Knowledge, attitude, practice and motivation of the health
personnel on HMIS performance
Knowledge
14.3%
Adequate knowledge
Inadequate
knowledge
85.7%
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Knowledge, attitude, practice and motivation of the health
personnel in HMIS performance
Motivation
11.1%
Better Motivated
Not motivated
88.9%
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Data quality of patent’s record
88.2
90
81.5
80
68.2
70
65.8
62.1
60
50
40
37.9
34.2
31.8
30
18.5
20
11.8
10
0
Data quality Status
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 Health professionals culture of information use was
found to be 37.3%.
 Study in Jimma (2011) shows that utilization of health
information was 32.9%.
 In Tanzania (2011), 42% did not use the collected data for
decision making process.
 Study in Malawi (2005) revealed that that data is
incomplete as there are gaps in the data collection tools.
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Factors associated with information use for decision
making process
 Health professionals who work in Health facilities which
established PMT were 2.83 times more likely to use
information.
 Health care providers who had positive attitude were
2.79 times more likely to use information.
 Motivated Health professionals were 3.5 times more
likely to use information than not motivated.
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 Study conducted in Nigeria (2012) shows motivated health
professionals were more likely to use information for decision
making process.
 Similarly, India in 2007 shows establishment of PMT had
showed significant association with health professional
information use.
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Conclusion
 Data quality of HMIS tools were found to be very poor.
 Information use habit of health workers for decision
making were found to be very low.
 Establishment of performance monitoring team,
motivation and attitude health care providers were found
to be significantly associated with information use.
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Recommendation
 The regional health bureau needs to design in-service
trainings on information use culture and data quality.
 The regional and district health offices should regularly
give supportive supervision and technical assistants to
health facilities
 Regional and district health offices shall encourage,
train and follow up health care providers to establish
performance monitoring team.
 Motivating health care providers and providing training
on moral and ethical issues is recommended to improve
information use for decision making.
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THANK YOU!
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