Access to Health Services Ty Borders, Ph.D. Assistant Professor Health Services Research & Management Texas Tech School of Medicine.

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 1997 1995 1993

beds 55,759 57,178 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 6.0

from AHA Guide, 1999. Includes nursing home units.

Andersen & Aday’s Behavioral Model

Health care

system

External environment

Predisposing Enabling Need

Environment

Personal health

practices

Use of health

services

Perceived health status

Evaluated health status

Consumer satisfaction

Population Characteristics Behavior Outcomes

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

Modifying factors

Demographics

Sociopsychologocical

Structural variables (knowledge about

disease)

Cues to action

Likelihood of action

Perceived benefits

minus

Perceived barriers

Likelihood of taking

recommended action

Perceived threat of disease

Perceived susceptibility to disease X

Perceived seriousness

Individual perceptions

Health Belief Model

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 (%)

90.4

80.0

84.5

2.8

4.8

3.9

6.9

11.6

15.2

Ruralresidents

Urbanresidents

Overall Non-HispanicWhitesHispanics

OtherRaces

Education level of respondents (%)

Other Races Hispanics Non-HispanicWhites

Urban residents Rural residents Overall

8th grade or less Some HS HS graduate/GED 1-3 yrs college Bachelor's or more

% of respondents with any insurance who have private coverage

52.1

27.5

75.4

68.3

69.3

68.7

Other Races

Hispanics

Non-Hispanic Whites

Urban residents

Rural residents

Overall

% of respondents who did not visit a doctor

19.9

29.0

20.6

19.0

24.9

21.6

Other Races

Hispanics

Non-Hispanic Whites

Urban residents

Rural residents

Overall

% of respondents hospitalized

12.4

13.9

11.9

12.2

12.1

12.2

Other Races

Hispanics

Non-Hispanic Whites

Urban residents

Rural residents

Overall

% of respondents who had no problem getting prescription medications

81.4

82.1

86.3

85.2

86.1

85.6

Other Races

Hispanics

Non-Hispanic Whites

Urban residents

Rural residents

Overall

% of patients who always or usually saw a specialist when they needed one

70.9

56.0

70.8

71.0

66.9

69.2

Other Races

Hispanics

Non-Hispanic Whites

Urban residents

Rural residents

Overall

Multivariate logistic results: Predisposing factors (p<0.10)

Prescript. DrugsPrescript. Drugs Specialists Specialists

Variable (comparison group) OR 95% C.I. OR 95% C.I. Ethnicity

Hispanic (white) n.s. 1.33 1.01, 1.75

Other race (white) n.s. n.s.

Urban (rural) n.s. 0.81 0.70, 0.95

Gender n.s. n.s.

Number persons in household

1 other n.s. 0.75 0.58, 0.97

2 or more other n.s. 0.70 0.55, 0.90

Age category

age 71 to 75 (65 to 70) 0.84 0.68, 1.04 0.77 0.63, 0.93

age 76 to 80 0.64 0.51, 0.82 n.s.

age 81+ 0.48 0.36, 0.64 n.s.

Enabling factors (controlling for predisposing)

Prescript. DrugsPrescript. Drugs Specialists Specialists

Variable (comparison group) OR 95% C.I. OR 95% C.I. Educational status

High school grad (less HS) 0.88 0.70, 1.12 0.82 0.66, 1.01

Some college 0.83 0.64, 1.08 n.s.

College grad 1.09 0.81, 1.47 0.53 0.41, 0.70

Religiousness not included 0.84 0.72, 0.98

Income

Income > $30,000 (<$30,000) 0.56 0.44, 0.72 0.85 0.69, 1.04

Income missing 0.65 0.52, 0.80 0.86 0.71, 1.05

Insurance coverage

Medicare only (none) n.s. n.s.

Medicaid n.s. 0.83 0.61, 1.01

Private only n.s. n.s.

Medicare plus n.s. 0.79 0.61, 1.01

Need (controlling for predisposing and enabling)

Prescript. DrugsPrescript. Drugs Specialists Specialists

Variable (comparison group) OR 95% C.I. OR 95% C.I. Hypertension n.s. n.s.

Coronary heart disease 1.43 1.38, 1.79 0.59 0.48, 0.74

MI n.s. n.s.

Stroke n.s. n.s.

Arthritis n.s. n.s.

Respiratory disease n.s. n.s.

Diabetes n.s. n.s.

Need help with ADLs n.s. n.s.

Need help with IADLs n.s. n.s.

SF-12 Physical Score 0.97 0.96, 0.98 1.02 1.01, 1.03

SF-12 Mental Score 0.97 0.96, 0.99 n.s.

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.SSite of care in 1790s Type of patientAlmshouse (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