Access to Health Services
Ty Borders, Ph.D.
Assistant Professor
Health Services Research & Management
Texas Tech School of Medicine
Objectives for today
• Define access
• Discuss the organization and types of
health services organizations
• Describe trends in access in the U.S.
• Describe major conceptual models of
access
• Describe the possible determinants of
service use and health outcomes
Andersen’s definition
• “Actual use of personal health services
and everything that facilitates or impedes
the use of personal health services”
– Visiting a physician / volume of visits
– Hospitalization / no. of nights hospitalized
– Visiting an ER
Donabedian’s definition of access
• Socioorganizational fit (whether
organizational attributes match societal
needs)
– Whether providers speak Spanish
– Whether office hours are convenient
• Geographic fit (geographic distribution of
facilities, providers, and services)
Why should we care about access?
• To predict utilization at the population
level (forecast demand)
• To explain and understand why persons
access services (market research)
• To encourage the appropriate use of
services to improve health
Andersen’s dimensions of access
•
•
•
•
•
•
Potential
Realized
Equitable
Inequitable
Effective
Efficient
Potential access
• Structural characteristics of health
system
– Capacity (physician/pop. ratio, hospital
bed/pop. ratio)
– Organization (% of population in managed
care)
• Enabling characteristics
– Personal resources (income, insurance)
– Community resources (rural/urban
residence)
Realized access
• Actual use of health services
– number of visits, number of days in
hospital, whether visited a physician,
whether visited a psychologist
• Characterized in terms of….
– Type (e.g. ambulatory, inpatient, dental)
– Site (e.g. physician office, hospital)
– Purpose (e.g. primary, secondary, tertiary)
Equitable / inequitable access
• Equitable - use determined by need for
care
– No differences in service use according to
need
• Inequitable - use influenced by social
and enabling factors
– Differences in service use according to race,
ethnicity, occupation, insurance coverage
Effective and efficient access
• Effective - Use improves health
outcomes, including health status and
satisfaction with care
• Efficient - Health services use improves
health outcomes at minimum cost
Utilization statistics for Texas
Inpatient
beds
1997
55,759
1995
57,178
1993
58,157
admissions
2,126,610
2,029,050
1,963,869
days
11,355,612 11,366,956 11,811,104
alos
5.3
5.6
from AHA Guide, 1999. Includes nursing home units.
6.0
Andersen & Aday’s Behavioral Model
Environment
Health
care
system
External
environment
Population
Characteristics
Predisposing
Enabling
Need
Behavior
Personal
health
practices
Use of
health
services
Outcomes
Perceived
health status
Evaluated
health
status
Consumer
satisfaction
Environmental factors
• Hypothesized to have the most indirect
influence on access to care
• Health system factors
– availability of physicians
– availability of hospitals
• External environment
– level of community’s economic development
– pollution control
Predisposing factors
• Fairly immutable
• Examples
– Demographics (gender, marital status, race)
– Social structure (education, ethnicity, social
integration)
– Beliefs (e.g. beliefs about the effectiveness of
medial care)
Enabling factors
• More mutable
• Examples
– Income
– Health insurance status (whether have
insurance)
– Type of insurance coverage (Medicare or
Medicaid)
– Transportation (whether have a car)
Need factors
• Perceived need
– Subjective health status (Health-related quality
of life)
– Symptoms
– Discomfort
• Evaluated need
– Health care professional’s judgement about
your health status
– Diagnosis
Health behavior / service use
• Personal health practices
– Exercise
– Wear a seat belt when driving in car
• Use of health services
– Visit a physician
– Stay over night in a hospital
– Visit a psychologist
Types of outcomes
• Perceived health status
– Health-related quality of life
• Evaluated health status
– Health professional’s judgment
• Consumer satisfaction
– Satisfaction with technical and interpersonal
aspects of care
Health Belief Model (Rosenstock)
• A social-psychological theory
– Focuses on evaluative, cognitive variables
that motivate an individual to practice
preventive health behavior (Rosenstock,
1974)
Health Belief Model (Rosenstock)
• 4 factors influence health behavior
decisions
– Perceived susceptibility to diseases
– Perceived severity of disease, including
emotional concern about potential harm
– Relative benefits and costs associated with
a treatment
(Rosenstock, 1974; Maiman and Becker, 1974;
Janz and Becker, 1984)
Health Belief Model (Rosenstock)
• Cue to action may also be necessary
– media
– advice from family
Health Belief Model
Individual
perceptions
Modifying factors
Demographics
Sociopsychologocical
Structural variables
(knowledge about
disease)
Perceived
susceptibility
to disease X
Perceived threat of
disease
Perceived
seriousness
Cues to action
Likelihood
of action
Perceived
benefits
minus
Perceived
barriers
Likelihood of
taking
recommended
action
Hispanic Ethnicity, Rural Residence,
and Satisfaction with Access to Care
Results from the Texas Tech 5000
Overview
• TT5000
– Sample of 5,000 elders residing in west Texas
– Survey of health status, demographics, health care
accessibility and quality
• Including satisfaction with access to prescription drugs
and specialists
– Relatively large % of Hispanics and rural residents
– Key personnel
• James E. Rohrer, P.I.
• Ty Borders, Barbara Rohland, Tom Xu, co-investigators
Access measures in TT5000
• Numerous items derived from CAHPS
• Satisfaction with ability to get prescription
drugs when needed
• Satisfaction with access to specialty
physician services
TT5000 Methodology
• 65,000 household telephone listings
– 10 replications of 6,500 numbers
• Household screened for elderly person
– If more than 1, most recent birthday chosen
• Informed consent obtained
• MMSE administered to screen for dementia
TT5000 Methodology, continued
• Participation rates:
– Excluding eligible respondents who failed
cognitive screener: 72%
– Accounting for 361 telephones not answered: 75%
• Potential biases
– Hispanics and other races potentially slightly
under-represented
– Females probably slightly over-represented
Independent Variables
• Predisposing
– Gender
– No. persons in household (proxy of social support)
• 1 other person
• 2 other person
–
–
–
–
Age category
Educational status
Marital status
Ethnicity/race
• Hispanic, non-Hispanic white, other
Independent Variables (cont.)
• Enabling
– Household income category
– Employment status
– Health insurance coverage
• Medicare only
• Medicare plus private or other gov’t
• Medicaid only or Medicaid plus other, private only or
gov’t only
• Private only
– Urban / Rural residence
• (rural defined as county with fewer than 50,000 persons)
Independent Variables (cont.)
• Need
– SF-12 PCS and MCS
– Self-reported diseases and conditions
(hypterension, coronary heart disease, myocardial
infarction, stroke, arthritis, asthma/emph/chronic
bronchitis, and diabetes)
– Need help with ADLs
– Need help wit IADLs
Dependent Variables
• Derived from Consumer Assessment of Health
Plans Study (CAHPS)
– How often did you see a specialist when you
needed one?
• Never, sometimes, usually, always, didn’t need to
– How much of a problem, if any, have you had
getting prescription medications?
• Big problem, small problem, no problem, have not had
any
Profile of ethnicity by county of
residence (%)
Overall
3.9
Urban
residents
Rural
residents
11.6
84.5
80.0
4.8
2.8
15.2
6.9
90.4
NonHispanic
Whites
Hispanics
Other
Races
Other Races
Hispanics
8th grade or less
Some HS
Non-Hispanic
Whites
Urban residents Rural residents
HS graduate/GED
1-3 yrs college
Bachelor's or more
22
.
17 8
.2
33
.5
13
.8
12
.8
20
.
13 8
.5
36
.7
13
.3
15
.7
31
.
24 0
.
19 4
.9
14
.
10 2
.5
25
.
19 1
.3
6.3
12
.7
6.6
4.2
13
.9
9.4
10
.5
20
.4
21
.5
25
22 .7
.0
36
.5
66
.0
Education level of respondents (%)
Overall
% of respondents with
any insurance who have
private coverage
Overall
68.7
Rural residents
69.3
Urban residents
68.3
Non-Hispanic Whites
Hispanics
Other Races
75.4
27.5
52.1
% of respondents who did not visit a doctor
Overall
21.6
Rural residents
Urban residents
Non-Hispanic Whites
24.9
19.0
20.6
Hispanics
Other Races
29.0
19.9
% of respondents hospitalized
Overall
12.2
Rural residents
12.1
Urban residents
12.2
Non-Hispanic Whites
11.9
13.9
Hispanics
Other Races
12.4
% of respondents who
had no problem getting
prescription medications
Overall
85.6
Rural residents
86.1
Urban residents
85.2
Non-Hispanic Whites
86.3
Hispanics
82.1
Other Races
81.4
% of patients who always or
usually saw a specialist when they
needed one
69.2
Overall
Rural residents
66.9
Urban residents
71.0
Non-Hispanic Whites
70.8
Hispanics
Other Races
56.0
70.9
Multivariate logistic results:
Predisposing factors (p<0.10)
Variable (comparison group)
Ethnicity
Hispanic (white)
Other race (white)
Urban (rural)
Gender
Number persons in household
1 other
2 or more other
Age category
age 71 to 75 (65 to 70)
age 76 to 80
age 81+
Prescript. Drugs
OR 95% C.I.
Specialists
OR 95% C.I.
n.s.
n.s.
n.s.
n.s.
1.33
n.s.
0.81
n.s.
1.01, 1.75
n.s.
n.s.
0.75
0.70
0.58, 0.97
0.55, 0.90
0.77
n.s.
n.s.
0.63, 0.93
0.84
0.64
0.48
0.68, 1.04
0.51, 0.82
0.36, 0.64
0.70, 0.95
Enabling factors (controlling for predisposing)
Variable (comparison group)
Educational status
High school grad (less HS)
Some college
College grad
Religiousness
Income
Income > $30,000 (<$30,000)
Income missing
Insurance coverage
Medicare only (none)
Medicaid
Private only
Medicare plus
Prescript. Drugs
OR
95% C.I.
Specialists
OR 95% C.I.
0.88
0.83
1.09
0.66, 1.01
not included
0.82
n.s.
0.53
0.84
0.56
0.65
0.85
0.86
0.69, 1.04
0.71, 1.05
n.s.
n.s.
n.s.
n.s.
0.70, 1.12
0.64, 1.08
0.81, 1.47
0.44, 0.72
0.52, 0.80
n.s.
0.83
n.s.
0.79
0.41, 0.70
0.72, 0.98
0.61, 1.01
0.61, 1.01
Need (controlling for predisposing and enabling)
Variable (comparison group)
Hypertension
Coronary heart disease
MI
Stroke
Arthritis
Respiratory disease
Diabetes
Need help with ADLs
Need help with IADLs
SF-12 Physical Score
SF-12 Mental Score
Prescript. Drugs
OR
95% C.I.
Specialists
OR 95% C.I.
n.s.
1.43
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
0.97
0.97
n.s.
0.59
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
1.02
n.s.
1.38, 1.79
0.96, 0.98
0.96, 0.99
0.48, 0.74
1.01, 1.03
Implications - Access to Medication
• Vast majority of persons who received
prescriptions do not have problems getting
them
– Insurance coverage not associated with problems
• Expanding insurance may not make a difference
• Even Medicaid (which typically has better benefits) was
not associated with fewer problems getting medicine
• The bureaucracy of insurance plans may inhibit getting
medicine (gov’t insurance in Texas known for this)
Implications - Access to Medication
• Hispanic ethnicity not associated with ease of
access to prescription drugs
• Rural residence not associated with ease of
access to prescription drugs
Implications - Access to Specialists
• Approximately 30% of elders had a problem
seeing a specialist when they needed to
– Hispanics are less satisfied with ease of access to
specialty doctors
• Perhaps Hispanics under-use primary care (they have
fewer doctor visits overall)
• If so, they may need to be directed to primary care,
rather than specialty care
• Perhaps the health system discriminates against
Hispanics (this is supported by previous literature).
• Hispanics may not be as knowledgeable about how to
navigate system
Implications - Access to Specialists
– Rural residents less satisfied with ease of access to
specialists
• Issue of availability?
• Issue of distance?
– Number of persons in household associated with
ease of access to specialists
• Issue of instrumental support?
e.g. Transportation problems
Place / site of utilization
• Most persons go to doctor’s office
• Among the poor, a higher % go to
hospital outpatient dept.
Place / site of utilization
• Most persons go to doctor’s office
• Among the poor, a higher % go to
hospital outpatient dept.
Rise of ambulatory care
• Before WWII, most care provided in
the home
– medicine not technical
– docs could carry most equipment
• After WWII, care moved to the
physician’s office
– incredible advances in technology
– increased demand for medical care
Types of ambulatory care orgs.
• Physician office or clinic
– Solo or group
• Community health centers
• Freestanding emergency rooms
• Freestanding amb. care center
• Clinical labs
Types of ambulatory care (cont.)
• Ambulance services
• Renal dialysis
• Trauma centers
• Ambulatory surgery centers
• Hospital-based
– Clinics
– Freestanding outpatient hospitals
Types of hospitals
• Government
– Local, state, government
• UMC is a county owned hospital
• Private, not-for-profit
– Owned by private non-government groups
• Religious affiliated hospitals, such as Covenant
• University hospitals, such as Duke
• Private, not-for-profit
• Hospital Corporation of American (HCA)
Rise of hospitals in the U.S
Site of care in 1790s
Type of patient
Almshouse (poorhouse)
Non-paying, acute
Chronic
Mental disorders
Jail
Mental Disorders
Pest houses
Contagious disease
Billeting in private homes
Merchant seamen,
military veterans
Rise of hospitals in the U.S.:
the 18th and 19th centuries
• Medical care was secondary to housing
• First voluntary (community) hospitals
in late 1700s, early 1800s
• European trained physicians led the
way for voluntary hospitals
Rise of hospitals in the U.S.:
the 19th and early 20th centuries
• Advances in medical science
–
–
–
–
–
–
–
Anesthesia (Ether used by Long in 1842)
Germ theory
Steam sterilization in 1886
Antibiotics in 1940’s
X-rays in 1896
Blood types in 1901
Nursing care
Rise of hospitals in the U.S.:
the early twentieth century
• Role of the social elite
• Role of physicians
– Promoted voluntary, community hospitals
because feared gov’t. regulation
• Fragmentation of hospital system
– Religion
– Race
– Income
Rise of hospitals in the U.S.:
the mid 20th century
• Hospital Survey & Construction Act
– Referred to as Hill-Burton Act, 1946
– Between 1947 and 1971, government paid
$3.7 billion to expand community and
regional hospitals (Levey, 1996)
• Medicare and Medicaid, 1965
– Increased demand for hospital care
Regulation
• Without gov’t. control, hospitals had to
self-regulate
– American College of Surgeons the 1st
– American Hospital Association 2nd
– Comprised to form JCAHO
• Self-regulation may have led to higher quality
(Stevens)
Teaching & Academic Hospitals
• Teaching hospitals
– Graduate medical education (residency
programs)
• Academic medical centers
– Graduate medical education
– Supports research
Organization of AMCs
• University owned
– Duke University Hospital
– University of Iowa Hospitals & Clinics
• University affiliated
– Mass General and Brigham & Women’s /
Harvard University
– UMC / Texas Tech University HSC
Organization of AMCs (cont.)
• University affiliated, for profit
– Tulane University sold most of its hospital
to Columbia/ HCA
– University of Minnesota sold it’s hospital
to Fairview Health System
Organization of AMCs (cont.)
• An alternative
• University owned, but not university
governed
– University of Kansas Med. Ctr.
– University of Wisconsin Med. Ctr.
– Governed by a state appointed board, not
the University nor the state itself
Critical Access Hospitals
• In response to BBA of 1997
• Limited to max. 15 beds, additional 10
swing beds
• Patient stay limited to 96 hours
• 24 hr. emergency care required
• Cost-based reimbursement
Reasons for rising hospital costs
• Aging population
• General inflation
• Technology
• Unnecessary surgery
• Unnecessary admissions
• Excess capacity
– too many inpatient beds, services
Cost control mechanisms
• Government regulation
– Certificate of need (CON)
– Rate regulation
– Peer review organizations (PROs)
• Competition
– Business coalitions
– Vertical integration
– Horizontal integration
Health Systems
• Vertical integration
– Expansion of organization into new fields
• e.g. Hospitals expanding into primary care,
nursing home care, etc.
• Horizontal integration
– Expansion of organization with own field
• e.g. A hospital merges with other hospitals