Evidence-based Synthesis Program Department of Veterans Affairs

Health Services Research & Development Service Evidence-based Synthesis Program 

Interventions to Improve

Veterans’ Access to Care:

A Systematic Review of the Literature

Department of Veterans Affairs

Health Services Research & Development Service

January 2011

Investigators:

Principal Investigator: 

Shannon M. Kehle, PhD

Co-Investigator: 

Nancy Greer, PhD

Research Associate:

Indulis Rutks, BS

Prepared for:

Department of Veterans Affairs

Veterans Health Administration

Health Services Research & Development Service

Washington, DC 20420 

Prepared by:

Evidence-based Synthesis Program (ESP) Center

Minneapolis VA Health Care System

Minneapolis, MN

Timothy J. Wilt, MD, MPH, Director
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

PREFACE

Health Services Research & Development Service’s (HSR&D’s) Evidence-based Synthesis 

Program (ESP) was established to provide timely and accurate syntheses of targeted healthcare 

topics of particular importance to Veterans Affairs (VA) managers and policymakers, as they 

work to improve the health and healthcare of Veterans. The ESP disseminates these reports 

throughout VA. 

HSR&D provides funding for four ESP Centers and each Center has an active VA affiliation. The 

ESP Centers generate evidence syntheses on important clinical practice topics, and these reports 

help: 

• develop clinical policies informed by evidence, 

• guide the implementation of effective services to improve patient outcomes and to 

support VA clinical practice guidelines and performance measures, and 

• set the direction for future research to address gaps in clinical knowledge.

In 2009, an ESP Coordinating Center was created to expand the capacity of HSR&D Central 

Office and the four ESP sites by developing and maintaining program processes. In addition, the 

Center established a Steering Committee comprised of HSR&D field-based investigators, VA 

Patient Care Services, Office of Quality and Performance, and and Veterans Integrated Service 

Networks (VISN) Clinical Management Officers. The Steering Committee provides program 

oversight and guides strategic planning, coordinates dissemination activities, and develops 

collaborations with VA leadership to identify new ESP topics of importance to Veterans and the 

VA healthcare system.

Comments on this evidence report are welcome and can be sent to Nicole Floyd, ESP 

Coordinating Center Program Manager, at nicole.floyd@va.gov.

Recommended citation: Kehle SM, Greer N, Rutks I, and Wilt TJ. Interventions to 

Improve Veterans Access to Care: A Systematic Review of the Evidence. VA-ESP 

Project #09-009; 2011

This report is based on research conducted by the Evidence-based Synthesis Program 

(ESP) Center located at the Minneapolis VA Health Care System, Minneapolis, MN 

funded by the Department of Veterans Affairs, Veterans Health Administration, Office of 

Research and Development, Health Services Research and Development. The findings 

and conclusions in this document are those of the author(s) who are responsible for its 

contents; the findings and conclusions do not necessarily represent the views of the Department of Veterans Affairs or the United States government. Therefore, no statement 

in this article should be construed as an official position of the Department of Veterans 

Affairs. No investigators have any affiliations or financial involvement (e.g., employment, 

consultancies, honoraria, stock ownership or options, expert testimony, grants or patents 

received or pending, or royalties) that conflict with material presented in the report.
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

TABLE OF CONTENTS

Executive Summary............................................................................................................................................. 1

Background.................................................................................................................................................... 1

Methods......................................................................................................................................................... 1

Results ........................................................................................................................................................... 1

Conclusions ................................................................................................................................................... 2

Introduction .......................................................................................................................................................... 3

Methods

Topic Development........................................................................................................................................ 4

Search Strategy.............................................................................................................................................. 4

Study Selection.............................................................................................................................................. 5

Data Abstraction ............................................................................................................................................ 5

Quality Assessment ....................................................................................................................................... 5

Data Synthesis............................................................................................................................................... 5

Peer Review................................................................................................................................................... 5

Results ..................................................................................................................................................................... 6

Literature Flow .............................................................................................................................................. 6

Key Question 1.............................................................................................................................................. 7

Key Question 2............................................................................................................................................ 12

Summary and Discussion.................................................................................................................................. 19

Conclusions ................................................................................................................................................. 19

Limitations................................................................................................................................................... 20

Recommendations for Future Research....................................................................................................... 21

References............................................................................................................................................................ 23

Figures

Figure 1. Analytic Framework...................................................................................................................... 4

Figure 2. Literature Flow Diagram for Key Questions ................................................................................ 6

Appendix A. Search Strategy ...................................................................................................................... 27

Appendix B. Peer Review Comments......................................................................................................... 28

Appendix C. Evidence Tables

Evidence Table 1. Studies Examining Variation in Outcomes Associated with Variation in Access......... 31

Evidence Table 2. Studies Examining the Efficacy of Interventions Designed to Increase 

 Access for Veterans....................................................................................................... 40
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

EXECUTIVE SUMMARY

BACKGROUND

Recently, researchers within the Department of Veterans Affairs (VA) have begun to develop an 

updated conceptualization of access which takes into account the impact of new technology on 

access and places a greater focus on outcomes beyond increased access.1 Specifically, the new 

conceptualization acknowledges post-access outcomes such as satisfaction, symptom levels, 

and functioning. As such, we sought to conduct a review of the literature that would clarify the 

current state of knowledge regarding the link between access to healthcare and system-level 

(e.g., utilization, satisfaction with care) and patient-level (quality of life, symptoms, mortality) 

outcomes. Given VA’s continuing commitment to improving access for veterans,2,3 we also 

examined the efficacy of interventions designed to improve access, with a focus on access, 

system-level, and patient-level outcomes (Figure 1).

The Key Questions addressed in this review are:

KEY QUESTION #1: What is the evidence that variation in veterans’ ability to obtain needed 

health care (i.e., access) contributes to variation in system level (e.g., utilization, satisfaction) or 

patient level (e.g., quality of life, functional ability, mortality) outcomes?

KEY QUESTION #1A: Does the effect of access on system and/or patient level outcomes 

differ by patient (e.g., demographics, overall health, illness severity), treatment (e.g., mental 

health, physical health), or setting (e.g., rural, urban, community, VA) characteristics?

KEY QUESTION #2: What interventions have been successful in improving access for patient 

populations with reduced health care access?

KEY QUESTION #2A: Have interventions that have improved health care access led to 

improvements in system level and patient level outcomes?

METHODS

We searched OVID MEDLINE, CINAHL, and PsycINFO for English language articles related 

to access and veterans’ care published in peer-reviewed journals from 1990 to June 2010. Data 

were abstracted from 23 articles related to Key Question #1 and 26 related to Key Question #2. 

We constructed evidence tables with patient characteristics, outcomes, and study quality for each 

study included. Due to heterogeneity in study design, patient characteristics, and outcomes, 

pooled analyses were not feasible. 

RESULTS

KEY QUESTIONS #1 and #1a: We identified 23 studies that focused on the association between 

access and system-level or patient-level outcomes. Most commonly studied was the association 

between distance from a VA facility and utilization, primarily outpatient health and/or mental 

health service use. Across a variety of patient needs (e.g., treatment for substance abuse or spinal 

cord injury, primary care), we found fair to good evidence that increased distance from a VA 
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

facility was associated with decreased utilization. Other factors studied in relation to outpatient 

utilization included ability to pay for care, social support, and comorbidities. Distance, ability 

to pay for care, and comorbid conditions also influenced utilization of inpatient care including 

choice of VA or non-VA facilities. Five studies reported patient-level outcomes including two 

that addressed mortality. We found limited evidence that increased distance from a VA facility 

(one study) and longer wait time for an appointment (one study) were associated with increased 

mortality. We found fair evidence from six studies that identified significant interactions with the 

majority focused on distance and other explanatory variables such as age and diagnosis.

KEY QUESTIONS #2 and #2a: We identified 26 articles (24 unique studies) that examined 

the efficacy of interventions designed to increase access. Only five were randomized trials. 

We categorized these interventions as Community Based Outpatient Clinics, Mental Health 

Integration into Primary Care, Intensive Case Management, Telehealth, Outreach, CoPayments, 

and Other. Changes in medication copayments had the strongest evidence base with four studies. 

We found fair strength of evidence that increases in medication copayments decreased access 

/ adherence to needed medications. Community Based Outpatient Clinics and Primary Care 

Mental Health Integration were evaluated in 6 studies each, but the studies were of low quality. 

There were fewer studies that evaluated other interventions (e.g., primary care mental health 

integration, intensive case management, telemedicine, outreach). Nineteen studies reported 

system-level outcomes, most often satisfaction with care and use of primary care. The majority 

of studies that reported satisfaction found veterans were more satisfied with care following the 

intervention. All but one of the studies on primary care and general medical visits found that 

the intervention was associated with increased utilization. Six studies reported patient-level 

outcomes: three found that access did not impact outcomes and one found that veterans with 

increased access had worse outcomes. 

CONCLUSIONS

The data suggest it is possible to improve access to healthcare, although there was a lack of 

high quality evidence supporting the efficacy of any one intervention. There was fair evidence 

that increases in medication copayments decrease access / adherence to needed medications. 

However, future research is needed to determine if decreasing copayments increases access/ 

adherence. There was fair evidence of a relationship between improved access and better 

system-level outcomes (satisfaction and primary care utilization). There was a lack of data 

regarding the link between access and patient-level outcomes. Future research should focus on 

the quality and appropriateness of care and patient-level outcomes.
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

INTRODUCTION

Access to healthcare has been identified as a critical issue, both by the Department of Veterans 

Affairs (VA) and the larger medical community.4-7 Access has been broadly defined as “the timely 

use of personal health services to achieve the best health outcomes” and has been hypothesized 

to have three discrete steps: 1) gaining entry into the system, 2) getting access to sites of care 

where patients can receive needed services, and 3) finding providers who meet the needs of 

the patient and with whom a productive working relationship can form.4,6 Historically, VA has 

focused on the first two steps (getting access to the system and sites of care) and has adopted 

Demakis’s5 conceptualization of access as an individual’s ability to obtain the healthcare they 

need within an appropriate time frame.7

Recently, researchers within the VA have begun to develop an updated conceptualization of 

access which takes into account the impact of new technology on access and places a greater 

focus on outcomes beyond increased access.1 Specifically, while the definition of access remains 

limited to the ability to connect with needed care, the reconceptualization acknowledges postaccess outcomes such as satisfaction, symptom levels, and functioning. As such, we sought to 

conduct a review of the literature that would clarify the current state of the knowledge regarding 

the link between access to healthcare (both objective and perceived access) and system-level 

(e.g., utilization, satisfaction with care) and patient-level (quality of life, symptoms, mortality) 

outcomes. Further, the VA has continued its commitment to improving access for Veterans,2,3 and 

has implemented several programs designed to improve access to care for all veterans. Examples 

include the establishment of clinics located in areas distant from VA facilities (CommunityBased Outpatient Clinics or CBOCs), mobile clinics, and increased use of telecommunications 

(telephone, internet, or videoconferencing). As such, we also examined the efficacy of 

interventions designed to improve access, with a focus on access, system-level, and patient-level 

outcomes (Figure 1).

The key questions addressed in this review are as follows:

Key Question #1: What is the evidence that variation in veterans’ ability to obtain needed health 

care (i.e., access) contributes to variation in system level (e.g., utilization, satisfaction) or patient 

level (e.g., quality of life, functional ability, mortality) outcomes?

Key Question #1a: Does the effect of access on system and/or patient level 

outcomes differ by patient (e.g., demographics, overall health, illness severity), 

treatment (e.g., mental health, physical health), or setting (e.g., rural, urban, 

community, VA) characteristics?

Key Question #2: What interventions have been successful in improving access for patient 

populations with reduced health care access?

Key Question #2a: Have interventions that have improved health care access led 

to improvements in system level and patient level outcomes?
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

Figure 1. Analytic Framework

Access

System Level Outcomes:

-Utilization

-Satisfaction

-Receipt of evidence-based care

-Others

Patient Level Outcomes:

-Quality of life

-Functional ability

-Change in condition status

-Mortality

-Others

Potential Moderators:

- Patient Characteristics (e.g., demographics, 

overall health, illness severity)

- Treatment Characteristics (e.g., type of treatment)

- Setting Characteristics (e.g., community 

access vs. VA access)

Interventions to 

improve access

KQ1

KQ2 KQ1

METHODS

Topic Development, Technical Expert Panel

This topic was nominated by the Planning Committee for the 2010 VA Health Services 

Research & Development State of the Art (SOTA) Conference on “Improving Access to VA 

Care” in consultation with the VA HSR&D Evidence Synthesis Program. John Fortney, PhD, 

Maurilio Garcia-Maldonado, MD, and Bonnie Wakefield, PhD, RN, agreed to serve on the 

Technical Expert Panel (TEP) for the project. The TEP members and the investigators from the 

Minneapolis VA Evidence-based Synthesis Program (ESP) collaborated to identify and refine the 

key questions.

Search Strategy

We searched MEDLINE (OVID), CINAHL, and PsycINFO for studies published from 1990 to 

June, 2010. To focus the search on Veterans, we used the following MEDLINE search terms: 

Health Services Accessibility, access, Veterans, United States Department of Veteran Affairs, 

and Hospitals, Veterans (see Appendix A). Similar search terms were used in the CINAHL and 

PsycINFO searches. We limited the searches to articles involving human subjects ages 18 and 

older published in English language. All publication types were included. Additional references 

were identified by searching the reference lists of articles identified for inclusion.
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

Study Selection

Titles and abstracts identified from the search were reviewed by the investigators to identify eligible 

articles likely related to one or more of the key questions. Exclusion criteria were as follows:

1) Not English language

2) Not United States veteran population

3) Not published from 1990 to present

4) Not about access to health care

5) Not about outcomes of interest

6) Not peer-reviewed (including meeting abstracts and presentations).

Data Abstraction

For Key Question 1, investigators abstracted data on study design, patient characteristics, 

dependent and explanatory variables included in analyses, impact of access on system-level and 

patient-levels outcomes, and interaction terms. For Key Question 2, investigators abstracted data 

on study design, patient characteristics, intervention, and impact of the intervention on access, 

system-level, and patient-level outcomes. 

Quality Assessment

Randomized control trials (RCTs) and cohort studies were assigned a rating of good, fair, or 

poor using the United States Preventive Services Task Force criteria.8 Observational studies 

were rated in the domains of participant selection (e.g., appropriate recruitment of subjects/

choice of database, response rate, representativeness), outcomes assessment (e.g., valid and 

reliable measures, no differential or overall high loss to follow-up), and analysis (e.g., potential 

confounders equally distributed or adjusted for in analysis). If all three of the three criteria were 

rated as adequate, the study received an overall rating of fair. All other observational studies were 

rated as poor. For Key Question 2, all intervention types also received a strength of evidence 

rating (in regards to impact on access, not system- and patient-level outcomes). Interventions 

for which 80% or greater of the studies received a fair or good quality rating were rated as fair. 

All other interventions were rating as poor strength of evidence; interventions with two or fewer 

studies were also rated as poor.

Data Synthesis

We constructed evidence tables showing the study characteristics and results for all included 

studies, organized by key question and, for Key Question 2, by intervention. We compiled a 

summary of findings for each key question and developed conclusions based on qualitative 

synthesis of the findings. We did not conduct pooled analyses due to marked heterogeneity in 

study design, patient characteristics, and outcomes assessed. 

Peer Review

A draft report was reviewed by our TEP members, by participants at the 2010 “Improving Access 

to VA Care” State of the Art (SOTA) Conference, and by invited peer-reviewers. Reviewer 

comments and author responses are summarized in Appendix B.
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

RESULTS

Literature flow

The OVID MEDLINE search yielded 209 references with 10 duplicates for a total of 199 

unique references. The CINAHL search yielded 212 additional references and the PsycINFO 

search yielded 252 additional references. When the results from these searches were combined 

there were 663 titles and abstracts for review. From the 663 titles and abstracts, 553 references 

were excluded. The full text of 110 references was then reviewed and another 74 references 

were excluded. By hand searching reference lists from relevant articles we identified another 4 

references and 9 articles were identified by a TEP member or reviewer. A total of 49 articles were 

included. Figure 2 details the exclusion criteria and the number of references related to each of 

the key questions.

Figure 2 Literature Flow Diagram (for Key Questions 1 and 2)

13 articles added from 

hand search or TEP/

reviewer suggestion

49 articles included

23 for KQ1

26 for KQ2

74 articles excluded:

1 not veteran population

34 not about access

37 no outcomes of interest

2 not peer-reviewed

553 articles removed: 

25 not veteran population

372 not about access

115 no outcomes of interest

40 not peer-reviewed

1 duplicate

110 articles retrieved for 

full-text review

Abstracts and/or titles 

reviewed

663 unique articles identified in 

searches of MEDLINE, Cinahl, and 

PsycINFO 
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

Key Question #1: What is the evidence that variation in veterans’ 

ability to obtain needed health care (i.e., access) contributes to variation in system-level (e.g., utilization, satisfaction) or patient-level (e.g., 

quality of life, functional ability, mortality) outcomes?

We identified 23 studies representing 22 datasets that looked at the impact of access on systemlevel or patient-level outcomes (see Appendix C, Table 1). There were 9 cohort studies and 14 

cross-sectional studies. Four studies were of good quality,9-12 13 were of fair quality,13-25 and six 

were of poor quality.26-31 Sample sizes in the 23 studies ranged from 109 to 3,424,699. Twenty 

studies enrolled veterans exclusively. In one study, 98.5% of the patients were veterans,18 in a 

second study 30.5% of the participants were veterans,31 in a third study 17% were veterans.26

Twenty-two studies reported gender. Four of those studies included only males. In the remaining 

18 studies, 93% to 98% of the participants were male. Twenty-one studies also reported age. 

Mean age in 11 studies that enrolled patients 18 years and older ranged from 43 to 59 years. In 

two studies from the same dataset that enrolled only patients 65 years and older, the mean age 

was 78 years. Two studies reported median age with a median of 75 years in a study that enrolled 

only patients age 65 and older and a median of 34 years in another study. Six studies reported 

number of participants in specified age intervals. Race or ethnicity data were reported in 18 

studies. One study included only Native American veterans. In the remaining studies, 29% to 

88% were Caucasian (reported in 13 studies), 9% to 54% were African-American (13 studies), 

3% to 28% were Hispanic (4 studies), and 1% were Native American (1 study). Between 1% and 

92% were reported as Other (4 studies), and 7% and 10% were Unknown (2 studies). One study 

reported Hispanic and non-white race/ethnicity by age and VA use categories.

Many factors can impact veterans’ ability to obtain needed care. Distance to VA facilities, wait 

times for appointments, ability to pay for care (considering income, disability, and service 

connection), social support, severity of illness/comorbid conditions, and access to other care (via 

Medicare or private insurance) have all been investigated. In the following sections we report 

the evidence regarding the impact of these factors on system-level and patient-level outcomes 

organized by clinical service area.

System-level Outcomes:

System-level outcomes, including utilization, admission, and readmission, were reported in 

22 studies including 8 cohort studies and 14 cohort studies. Fifteen of the studies (14 datasets) 

analyzed data from national VA datasets or surveys. Three studies were of good quality, 13 were 

of fair quality, and 6 were of poor quality.

Outpatient services: Data from a national survey of veterans highlighted decreased use of 

outpatient services as distance from a VA facility increased.13 The greatest decrease in utilization 

was noted for distances up to 60 miles with little change beyond. For veterans who chose to use 

the VA for some outpatient services, distance from the facility had a smaller additional effect 

on the number of visits. Increased use of VA physical and mental health services was noted for 

Vietnam veterans living on American Indian reservations located closer to VA facilities (in the 

Northern Plains region) compared to veterans living on a reservation located further from VA 

facilities (in the Southwest region).29 In a nationwide study of 8,983 veterans with spinal cord 
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

injuries and disorders, use of VA outpatient services decreased as distance from a VA facility 

increased. Increased age, non-white race, and a history of major illness were associated with 

increased utilization.20 Non-metropolitan VA patients between 18 and 44 years old were more 

likely (p<0.005) to report that they needed to see a doctor but could not because of cost than 

metropolitan VA patients or non-VA patients, or non-veterans of the same age. Among 45 to 64 

year olds, VA patients, regardless of residence, were more likely to report cost as a factor than 

non-VA patients or non-veterans.31

Veterans and non-veterans with human immunodeficiency virus (HIV) reported problems with 

transportation time (greater than 1 hour [17%] or greater than 30 minutes [55%]) and location 

(34%). In addition to travel barriers, patients with HIV also reported problems with office hours 

(48%), wait time for urgent appointments (greater than 2 days [23%] or greater than 1 day 

[50%]), office wait time (greater than 2 hours [32%] or greater than 1 hour [54%], and cost of 

care (49%).26

Homeless veterans in 9 states who had serious mental illness were more likely to use VA 

services if they resided in cities with VA medical centers or hospitals, if they had serviceconnected disabilities, or if they received non-service connected VA pensions.27 A regional 

study that enrolled homeless veterans found increased use of VA services among those living 

in metropolitan areas and among those receiving financial support though the Department of 

Veterans Affairs.28

Patients who were discharged following treatment for acute myocardial infarction (MI) were 

less likely to receive outpatient care within 30 days or within 90 days if they lived more than 

20 miles from the admitting hospital. The analysis was based on data from over 4,000 veterans 

nationwide. Other factors associated with increased likelihood of receiving outpatient care within 

30 days were service connected disability, age over 55 years, comorbid conditions, discharge 

from a teaching hospital, and revascularization procedure while a history of alcohol abuse was 

associated with decreased likelihood. A similar pattern was seen for the likelihood of one or more 

visits within 90 days except that alcoholism, type of hospital, and comorbidity were not related.10

Three large studies (2 that used data from national datasets, 1 that used data from 33 VA 

treatment programs) evaluated use of VA care following inpatient treatment for alcoholism, 

psychiatry, and / or substance abuse.9,14,25 Patients who lived closer to VA facilities were more 

likely to attend an aftercare appointment9,25 and were more likely to use outpatient medical 

services.14 Urban residing (with distance held constant) and unmarried patients were less likely 

to attend aftercare for alcohol dependence.9 Patients receiving VA compensation payments, those 

with a psychiatric diagnosis (as opposed to substance abuse), and those who had mental health 

follow-up within 30 days of discharge were also more likely to have received outpatient medical 

services following an inpatient stay for psychiatry or substance abuse.14 Older age, married 

status, service-connected eligibility, psychiatric comorbidity, substance use disorder, and being 

a patient at a teaching hospital were associated with increased likelihood of receiving aftercare 

following inpatient substance abuse care; medical comorbidities were associated with decreased 

likelihood.25

Three studies presented data on patients receiving mental health care. In a study that enrolled 

veterans receiving mental health services at 2 VA mental health centers, increased outpatient 
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

use of mental health services was associated with fewer reported access problems and no social 

support although the greatest predictor of use was clinical need.16 Among patients (nationwide) 

with bipolar disorder, schizophrenia, or other psychoses, the number of psychiatric and nonpsychiatric outpatient visit days decreased as distance from the VA outpatient service increased. 

Patients who had initial contact at a non-psychiatric clinic, a higher comorbidity rating, 

or resided in a rural area had fewer outpatient psychiatric visit days while those who were 

older, married, female, rural, had an initial visit at a non-psychiatric facility, or had a higher 

comorbidity rating had more outpatient non-psychiatric visit days.21 In a similar population, an 

increased risk of a 12 month gap in VA health system utilization was associated with residence a 

greater distance from a VA facility, homelessness, and a recent inpatient stay while a decreased 

risk of a 12 month gap was associated with residence in a county with greater availability of 

VA inpatient beds, older age, female gender, married status, VA service connection, higher 

comorbidity score, and a diagnosis of schizophrenia. An increased risk of a 12 month gap in 

mental health services was associated with residence a greater distance from VA psychiatric 

services, increased age, female gender, homelessness, higher comorbidity score, and recent 

inpatient stay. A decreased risk of a gap in mental health services was associated with married 

status, VA service connection, and a diagnosis of schizophrenia.22

Use of VA or non-VA health and mental health services was the focus of three additional studies. 

In one study, with data from over 1.4 million outpatients, there was an increase in the exclusive 

use of a VA facility as distance from the facility decreased. There was also greater exclusive use 

of outpatient VA facilities among patients with a higher VA priority designation and those living 

in counties with a higher level of poverty. Urban residents and those living in counties with a 

higher number of hospital beds were less likely to rely exclusively on VA care.19 A second study, 

with over 20,000 survey respondents, reported increased use of VA outpatient health and mental 

health services among those younger, unmarried, unemployed, and lacking health insurance. 

Greater use of VA health services (but not mental health services) was also associated with VA 

disability rating and poorer physical health. Non-VA health visits were associated with older 

age, female gender, college education, unemployment, disability rating and poorer physical and 

mental health. Non-VA mental health visits were associated with younger age, female gender, 

college education, unmarried status, unemployment, urban residence, and poorer physical and 

mental health.15 The third study, with data from over 1.9 million veterans, reported increased 

reliance on VA care (outpatient and overall) if the differential distance (distance from residence 

to VA facilities and non-VA facilities) was lower. There was also greater reliance on VA care by 

veterans with disability or low income priority classifications and those with mental health or 

substance abuse conditions.24

Inpatient services: One study focused on facility wait time for care and admission for an 

ambulatory care sensitive condition (ACSC) such as asthma, diabetes, or chronic obstructive 

pulmonary disease. Hospitalization for an ACSC would likely be avoided if the patient were to 

receive appropriate outpatient care in a timely manner. The analysis included data from 33,431 

veterans age 65 and older who visited a geriatric outpatient clinic. The probability of admission 

for an ACSC was significantly greater (p<0.05) for veterans who visited facilities with wait times 

of 29 days or more compared to visits to facilities with wait times of less than 22.5 days. Age, 

previous ACSC hospitalization, higher comorbidity index, and diagnosis of cancer or endocrine, 

heart, or pulmonary disease were also associated with increased risk of hospitalization.12
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

Patients who presented for emergency psychiatric care at one VA facility were more likely to 

be admitted for treatment if they lived more than 60 miles from the facility. Age greater than 

65 years and lower score on the Global Assessment of Functioning (GAF) were also associated 

with increased likelihood of admission.17 A study based at 2 VA mental health centers found that 

increased inpatient hospitalization for mental health services was associated with homelessness 

although the greatest predictor was clinical need.16

Veterans with spinal cord injuries and disorders had lower inpatient utilization if they lived a 

greater distance from the facility while history of major illness was associated with increased 

inpatient utilization.20

The impact of access to care on readmission was reported in two studies. Increased distance, 

expressed as “close,” “medium,” or “far,” from the county where the VA admitting facility 

was located, was associated with a non-significant, incremental, 18% increase in the risk of 

early (within 30 days) readmission. The veterans enrolled in this study were discharged from 

the internal medicine, surgery, intermediate care, or neurology services. The probability of 

readmission was also increased if the patient had two or more surgeries or their readmission risk 

was rated above “very low.”18 Using national VA databases, distance to care was not associated 

with an increased risk of readmission following treatment for MI. Age greater than 65 years, 

comorbid conditions, and receipt of any VA ambulatory care within 90 days were associated with 

increased risk of readmission.10

Three studies explored choice of VA or non-VA inpatient services. An analysis of data from 

over 400,000 veterans with inpatient admissions yielded results similar to those observed for 

outpatient utilization notably decreased exclusive use of VA services as distance to the VA 

increased. Age, urban residence, VA priority level, and poverty level were also factors associated 

with choice of inpatient services.19 A study of over 2 million hospital admissions for any of 14 

high-risk elective surgeries among veterans 65 years or older found that 89% of heart surgeries, 

85% of vascular surgeries, and 79% of cancer resections were performed in non-VA hospitals 

with little difference based on place of residence. The study also differentiated high performing 

from low performing hospitals and reported that, regarding travel time to high performing 

hospitals, urban residents had the least travel burden.31 Data from over 1.9 million veterans 

suggested that patients with transplant and amputation aggregated condition categories (ACCs) 

were more likely to rely on the VA for inpatient care. Other ACCs associated with inpatient VA 

care included infectious and parasitic disorders, substance abuse, mental health disorders, and 

eye disorders.24

Pharmacy utilization: One study evaluated use of VA pharmacy services. The nationwide 

study included veterans enrolled in both VA and Medicare programs. Enrollment in a Medicare 

plan with pharmacy benefits, age over 65 years, income of $20,000 or greater, female gender, 

VA priority status requiring copayment for medications, Medicare state buy-in, resident of a 

metropolitan statistical area, and being a patient at a teaching hospital were associated with 

decreased likelihood of using a VA pharmacy. Veterans of Hispanic race and of poorer health 

status were more likely to use the VA pharmacy.23
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

Patient-level Outcomes:

In contrast to system-level outcomes, patient-level outcomes, including mortality, perceived 

health, and quality of life, were only reported in 5 studies. Three were cohort studies (two of 

good quality, one of fair quality) and 2 were cross-sectional studies (both of fair quality). 

Two nationwide studies evaluated mortality.10,11 Patients discharged following hospitalization for 

MI and living more than 20 miles away from the admitting hospital had a significantly higher 

risk of dying within 1 year compared to individuals living within 20 miles. Age greater than 55 

years and presence of comorbid conditions were also associated with increased risk of mortality 

while undergoing revascularization or receiving VA ambulatory care within 90 days after the 

index visit was associated with decreased risk of death.10 Based on the dataset of veterans 65 

years of age and older who were seen for outpatient geriatric services at VA medical centers 

(Prentice, 2008), patients who visited facilities with wait times of 31 days or longer had a higher 

risk of death within 6 months than those who visited facilities with wait times of less than 31 

days. Other factors significantly associated with increased risk of mortality included increased 

age, 50% or greater service connected disability, preventable hospitalization, higher comorbidity 

index, or diagnosis of cancer or endocrine, neurological, psychiatric, pulmonary, or “other” 

disease. Female gender was associated with decreased risk of mortality.11

Two smaller studies examined the impact of access on either quality of life in individuals with 

human immunodeficiency virus (HIV) or mental health among patients receiving mental health 

services. In 205 veteran and non-veteran patients with HIV, better overall health related quality 

of life (HRQOL) was associated with better perceived access to care (p<0.01). Included in the 

perceived access measure were affordability, availability, and convenience of care along with 

accessibility of specialists. The relationship between HRQOL and temporal access (transportation 

and waiting times) was not significant26. In another study, treatment access was not associated with 

mental health outcomes (Global Assessment of Function or Behavior and Symptom Identification 

Scale-24) among 421 patients receiving mental health services at 2 VA sites.16

Self-reported health and days of poor health in the preceding 30 days were reported in one study of 

over 45,000 veterans and non-veterans. The poorest health was reported by veterans currently in VA 

care, in particular, non-metropolitan residents age 45 and older. Veterans in VA care, regardless of 

residence, reported a higher number of days of poor health (physical, mental, or limiting activities) 

in the past 30 days when compared to veterans not in VA care or non-veterans.30

Key Question #1a: Does the effect of access on system and/or patient level outcomes differ by patient, treatment, or setting characteristics?

Six studies evaluated the effect of interactions on system level factors.9,13,21,24,26,28 All but one of 

the studies26 included either a national sample of veterans13,21,24,28 or veterans treated at multiple 

sites.9 There were two cohort studies (one of good quality and one of fair quality) and four crosssectional studies (two of fair quality and two of poor quality).

The effect of distance on the number of outpatient visits, both psychiatric21 and nonpsychiatric13,21, as well as reliance on VA care24 was greater for older patients. Patients with a 
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

diagnosis of schizophrenia were also more affected by distance than those with bipolar disorder.21

Among patients scheduled to attend an aftercare appointment within 30 days following an 

inpatient alcohol dependency program, older patients and those with a rural residence were 

more negatively impacted by distance.9 On a scale of 0 (worst possible access) to 100 (best 

possible access), the access scores for transportation time to appointment were lower for patients 

infected with HIV and who had VA insurance compared to those who had California Medicaid 

insurance (p<0.05). The access scores for covering cost of care and availability of hospital care 

were higher for VA patients than for uninsured (non-VA) patients while the scores for office 

wait time and availability of emergency care were higher for VA patients than for uninsured or 

California Medicaid patients (all p<0.05).26 Among homeless veterans, the effect of metropolitan/

non-metropolitan status on use of VA facilities varied based on age, military service era, monthly 

income, time homeless, and past alcohol or drug dependency.28

Key Questions #2 and #2a: What interventions have been successful in improving access for patient populations with reduced health

care access? Have interventions that have improved health care access

led to improvements in system level and patient level outcomes?

We identified 26 articles (24 unique studies) that assessed interventions designed to improve 

veterans’ access to healthcare (see Appendix C, Table 2). We only included articles that provided 

data regarding the intervention’s impact on actual access (observable, measurable dimensions), 

perceived access (self-reported, subjective dimensions), or satisfaction with access.1 During 

abstraction, we found that the articles reported on six distinct types of interventions. The results 

are grouped by those interventions.

Community Based Outpatient Clinics (CBOCs):

Detailed Description

In order to increase access to primary care for veterans living in rural or other underserved 

geographical areas, the VA began opening satellite primary care clinics, known as CBOCs. Four 

of the articles32-35 utilized quasi-experimental designs to examine the impact of the opening 

of CBOCs on access factors. All four studies found that the opening of CBOCs had a positive 

impact on geographic accessibility as evidenced by the CBOCs attracting more users new to 

the VA than VA Medical Centers (VAMCS), a decrease in travel distance to the closest VA 

facility for those in CBOC catchment areas, and higher rates of accessing VA medical services 

in counties with a CBOC. A number of system-level outcomes were also identified. It was 

found that CBOC patients had more primary care visits and that decreases in travel distance 

significantly predicted increases in the number of primary care encounters. 

Findings regarding the utilization of specialty care were mixed. Fortney et al.32 found that CBOC 

patients had fewer specialty care encounters, while Fortney et al.33,34 found that those in CBOC 

catchment areas had more ancillary and extended care physical health visits. Finally, in counties 

with CBOCs that offered specialty mental health services, more veterans accessed mental 

health services. Importantly, CBOCs did not have a significant impact on a number of access 

and system-level outcomes (e.g., days between discharge and outpatient follow-up, hospital 

admissions, inpatient days) and the impact on some system-level outcomes were small and may 
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not be clinically significantly. For example, Fortney et al.33 reported that those in the CBOC 

catchment area only had 0.5 more primary care visits in the 18-months post-implementation than 

pre-implementation. None of the studies provided data on patient-level outcomes. 

It is important to note that while these studies found that CBOCs had a positive impact on 

geographical access, a vast majority of veterans residing in catchment areas (approximately 85%) 

still did not receive VA care.35 However, data suggest that high priority groups (those with serviceconnection or chronic diseases) may be experiencing greater benefits from the opening of CBOCs. 

For example, veterans in CBOC catchment areas with alcohol-related and hypertension diagnoses 

attended more primary care visits, while those with diabetes attended more mental health and 

ancillary services than veterans not in a CBOC catchment area33. Further, Rosenheck et al.35 found 

that veterans who were service-connected for any disorder (7.6% increase for those with no new 

CBOCs; 9.6% increase for those with new CBOCs) and those who were service-connected for 

non-mental health problems (7.3% increase for those with no new CBOCs; 9.4% increase for those 

with new CBOCs) had a significant increase in VA services. Finally, three studies found that CBOC 

veterans differ from VAMC veterans on demographic factors; those at CBOCS were found to be 

older, more often male, more often Caucasian, less often African American or Hispanic, more often 

married, and less often service connected than veterans seen at the parent VAMCs. 

Two studies examined veterans’ satisfaction with access and other aspects of care at CBOCs. 

Borowsky et al.36 reported that veterans using CBOCs reported better access / timeliness and 

were more likely to report waits of less than 20 minutes than veterans getting care at VAMCs. 

Further, veterans using CBOCs more often reported having good or excellent visits and reported 

fewer problems with their visits. Morgester et al.37 examined differences in veterans who 

received care from a CBOC, those who lived in a CBOC catchment area who did not use VA 

care, and those who received care from a VAMC. All three groups reported few access problems; 

they had few problems finding the clinic, found the hours of operation convenient, and were 

satisfied with care. Although no statistical comparisons were conducted, differences between the 

three groups were small. No patient-level outcomes were reported for either study.

Summary of findings

We identified six studies that examined the impact of the opening or use of CBOCs on veterans’ 

access to health care. None of the studies were randomized trials, although four utilized quasiexperimental designs in which cohorts were compared both pre- and post-implementation. 

Overall, the sample sizes were large, with one being VA-wide. Four of the studies were of fair 

quality, while 2 were poor quality. The overall strength of the evidence was poor.

All six studies found that CBOCs had a positive impact on various measures of access; four 

studies found an association between the opening of CBOCs and objective measures of access 

to primary care while two studies found that veterans were satisfied with CBOCs’ accessibility. 

Five of the studies reported system-level outcomes. Overall, increased access was associated 

with increased primary care use, while findings regarding specialty care were mixed. No studies 

reported patient-level outcomes. 
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

Primary Care Mental Health Integration:

Detailed Description

Two articles examined the impact of integrating mental health services into a primary care clinic, 

with the specific goal of improving access and outcomes for veterans with depression.38,39 Watts 

et al.39 conducted a quasi-experimental study examining a primary care clinic before and after 

the PCMH integration at a VAMC and associated CBOCs. The mental health services involved 

co-location of mental health services in the primary care clinic, collaborations between the 

primary care and mental health staff, advance or open access to mental health providers within 

the primary care clinic, and the use of standardized instruments for the assessment of mental 

health conditions. After PCMH integration, they found that more veterans at the VAMC received 

care for depression and fewer veterans received no depression treatment. Further they found 

that more veterans received care in mental health clinics and wait times for an appointment in 

the mental health clinics decreased substantially. None of these differences were significant 

at the CBOCs. In regard to systems outcomes, more veterans at the VAMC received “optimal 

depression treatment” following integration. No patient-level variables were reported. Shiner et 

al.38 reported on the effect of implementing five differing models of PCMH integration at one 

VAMC and four CBOCs. At the VAMC, the PCMH integration model was the same as described 

above. CBOC-A offered walk-in access one day per week, assessment by both a psychotherapy 

and psychopharmacologically oriented provider, and standardized assessments. CBOC-B 

had a psychotherapist on the primary care team and had back-up telepsychiatry services by 

appointment. CBOC-C did not have PCMH integration, but had a mental health clinic onsite. CBOC-D did not offer mental health services. Following implementation, the VAMC and 

CBOC-A had nearly identical results, with both experiencing increases in the number of veterans 

receiving mental health care in four days and 30 days, and the number of veterans receiving 

optimal care. The less intensive CBOC-B also had an increase in the number of veterans 

receiving care within 30 days and the number of veterans receiving optimal care. There were no 

differences for CBOC-C or CBOC-D. No system- or patient-level outcomes were assessed.

Two articles examined implementing primary care clinics into existing mental health / 

substance use clinics.40,41 Druss et al.40 conducted a randomized trial to examine the efficacy of 

implementing a primary care in the mental health clinic. In regard to access, veterans randomized 

to PCMH integration reported significantly better satisfaction with access to care. The two 

conditions also yielded significant differences on a number of systems-level variables; those 

in PCMH integration had more primary care visits, fewer ER visits, received more preventive 

services, and reported greater satisfaction across a number of domains. Finally, in regard to 

patient-level outcomes, veterans assigned to PCMH integration had better physical component 

SF-36 scores at one-year post randomization; there was no difference on the mental component 

score. Saxon et al.41 conducted a similar study in which they randomized veterans receiving care 

in a substance use clinic to receive primary care from a clinic located within the substance use 

clinic or through a medical clinic (treatment as usual). The integrated condition fared better on 

measures of access, including length of wait for initial primary care visit, odds of attending a 

rescheduled initial visit, and the likelihood of attending at least one primary care visit. However, 

there was no difference on the likelihood of attending the initially scheduled appointment. In 

regard to system-level outcomes, those assigned to PCMH integration condition were more likely 

to attend return primary care visits and had more primary care visits during the study period, 
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were less likely to seek non-VA care, and were more likely to remain engaged in substance use 

treatment at 60 days (although not at 6 or 12 months). Mean days in substance use treatment did 

not differ. There were no sustained differences in ER visits or hospital admissions. There were 

no group differences on patient-level outcomes, including the SF-36 (both physical and mental 

composite scores) or substance use disorder outcomes.

Finally, one study reported on the effort to integrate primary care, mental health, and services for 

homeless veterans.42,43 The quasi-experimental design compared homeless veterans with substance 

use problems and serious mental illness both before and after the opening of the integrated clinic. 

Within the integrated clinic, veterans were evaluated in a screening clinic and quickly referred 

to other services, all of which were housed within the same building. The goal was to have the 

primary care appointment occur on the day of screening. The intervention did result in shorter wait 

times for an initial primary care appointment; the PHMC integration group had, on average, less 

than a day lapse, while the usual care group waited approximately 2 months for their initial visit. 

In regards to system-level outcomes, the PCMH group received more preventive services, had a 

higher number of primary care visits, and had lower levels of ER use. There were no differences in 

rates of admission, inpatient days, or the number of veterans receiving primary care. There were no 

significant differences in the patient-level variable of physical health status. 

Summary of Findings

We identified six articles (five unique studies) that examined the impact of primary care mental 

health (PCMH) integration on veterans’ access to health care services. Two studies examined the 

integration of primary care into mental health clinics; two examined the integration of mental 

health into primary care clinics; and one study (two articles) examined the integration of mental 

health, primary care, and homeless services. Two of the studies were randomized trials, the 

others were quasi-experimental. The overall strength of the evidence was poor; one study was of 

high quality, two of fair quality, and three were low quality. 

All five found that integration led to improvements in objective or self-reported access. Two studies 

specifically examined access to optimal treatments and found that PCMH led to more veterans 

receiving optimal depression care. Three studies found associations between increased access and 

more primary care visits. Three studies reported on patient-level outcomes; results were mixed.

Intensive Case Management:

Two studies (one good, one poor quality) examined the effect of intensive case management 

on access.44,45 The overall strength of the evidence was poor. Both intensive case management 

programs had a number of goals, including increasing access to needed services for veterans 

already within the VA system who had high levels of health care needs. Ritchie et al.44 examined 

the impact of the Coordination and Advocacy for Rural Elders (CARE) program, which was 

designed to improve the health and functioning and to extend the length of independent living for 

elderly rural veterans. This is done, in part, through increasing access to health services. Veterans 

in the care program received multiple, standardized assessments through which a provider 

identified problems, developed a care plan, and tracked the resolution of problems. In regard to 

access, it was found that over 56% of veteran received a medical referral or linkage following the 

assessments. No system- or patient-level outcomes were assessed. 

Weinberger et al.45 conducted a randomized trial in which hospitalized veterans with diabetes, 
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chronic obstructive pulmonary disease, or congestive heart failure, who did not have ongoing 

primary care, were assigned to either treatment as usual or an intensive primary care program. 

The primary care program was designed to increase access to primary care through both inpatient 

and outpatient components. While the veteran was still in the hospital, a primary care doctor and 

nurse each made visits to assess current functioning and post-discharge needs, and the primary 

care nurse made an appointment for the veteran to visit the primary care clinic within one week of 

discharge. Following discharge, the nurse called the veteran within two days to assess any problems 

and to remind the veteran of his upcoming appointment. Appointment reminders were sent and 

missed-visit protocols were implemented as needed. During the first primary care appointment, 

both the nurse and doctor reviewed and updated the treatment plan. In regard to access, the data 

showed that the median time from hospital discharge to primary care was shorter and self-reported 

satisfaction with access was higher for the intervention group. The two groups differed on systemlevel outcomes, with intervention veterans being more satisfied with care, more likely to visit a 

general medicine clinic, and less likely to visit specialty care. Surprisingly, those in the intervention 

condition were more likely to be readmitted to the hospital, readmitted sooner, and have more days 

of rehospitalization. There were no differences on patient-level outcomes (SF-36). 

Telemedicine:

Detailed Descriptions

Two studies (a cohort study and a RCT) examined the efficacy of using telemedicine as a 

method for patients to communicate with existing providers.46,47 Barnett et al.46 examined the 

use of telehealth messaging in older, at-risk, veterans with type two diabetes, while Hopp et 

al.47 conducted a randomized trial to determine the impact of telehealth messaging on veterans 

receiving home care services. Both telehealth programs involved the veteran updating the nurse 

on current symptoms and problems via the telehealth device, which transmitted both video and 

sound. In the Hopp et al.47 study, some units also had monitoring devices (e.g., blood pressure 

cuffs), which would directly transmit data to the nurse. During the telehealth sessions, the nurse 

could have discussed concerns with the veteran, provided disease management suggestions, 

made referrals as appropriate, and reminded the veteran to continue with his treatment plan 

(e.g., take medication, exercise). The telehealth programs appeared to have a positive impact 

on access; Hopp et al.47 reported that contacts with VA providers increased and Barnett et 

al.46 found that care-coordinator initiated primary care visits increased by 8.9% following the 

implementation of telehealth. However, the findings regarding outcomes were less promising. 

Hopp et al.47 did not find any group differences in system-level outcomes (e.g., satisfaction, 

utilization variables); neither did Barnett et al.46 after controlling for baseline A1c levels. Hopp 

et al.47 did find that the intervention group had better scores on the mental component summary 

of the Health Related Quality of Life Scale as compared to the treatment as usual group; no other 

patient-level variables were significant (e.g., physical component score).

The other two telemedicine studies examined the utility of telemedicine in receiving specialty 

care consultations from off-site providers. Wakefield et al.48 examined the use of telehealth to 

receive a variety of specialty consultations from specialists at a VAMC for veterans in a long 

term care facility, while Wilkins et al.49 evaluated the feasibility of using telehealth to receive 

consultation from a multidisciplinary wound care team for veterans at a VAMC without such a 

team. In both studies, the veterans reported that telemedicine was easier and more convenient 
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

than travelling to meet with a specialist and a large majority of veterans were satisfied with 

telemedicine. No system- or patient-level outcomes were assessed.

Summary of Findings

We identified four studies that examined the use of telemedicine. Two studies were of fair quality 

and two were of poor quality, leading to an overall rating of poor. Two studies examined the 

efficacy of using telemedicine as a method for patients to communicate with existing providers,46,47

while two studies examined the use of telemedicine to consult with off-site specialists.48,49 One of 

the studies was an RCT of fair quality, the other three were non-experimental designs. Two studies 

found that veterans found telemedicine to be as, or more, convenient than in person appointments 

and two found that the use of telemedicine was associated with increased access / referrals to 

providers. One study47 (the RCT) examined patient-level outcomes; the intervention had a positive 

impact on the mental component of the health-related quality of life scale.

Outreach:

One fair-quality RCT examined the impact of outreach efforts on veterans’ access to health care. 

McFall et al.50 conducted a randomized trial in which Vietnam veterans who were service-connected 

for posttraumatic stress disorder (PTSD) were either randomized to the outreach intervention or to 

a no-intervention control. Those in the intervention condition received a mailing which included 

information regarding PTSD treatment services and contained a letter from the director of the PTSD 

program inviting them to seek care and providing them with three options for responding (return a 

postcard, call the study coordinator, or come to the walk-in clinic). The second component of the 

intervention was a direct phone call to the veteran by the study coordinator. The primary purpose of 

the call was to inquire about barriers to seeking care, but the study authors deemed it as part of the 

intervention because during the phone call, veterans could ask about services, discuss and address 

barriers to care, or schedule an appointment. The outreach did have a positive impact on access; 

more veterans in the outreach condition scheduled (19% vs. 7% of the intent-to-treat sample) and 

presented (approximately 15% vs. 7%) for an intake session. In addition, they were more likely to 

attend at least one follow-up session. No patient-level outcomes were assessed.

Copayments:

Detailed Descriptions

While the VA is generally considered an open-access healthcare system in which cost does not 

present a significant barrier, an increase in medication copayment rates from $2 to $7 provided a 

unique opportunity to examine the impact of copayments on access to needed medications within 

the VA. We identified four cohort studies that examined the impact of the copayment increase 

on (a) veterans with prescriptions for diabetic, hypertensive, or hyperlipidemic medications,51

(b) veterans with a diagnosis of schizophrenia or schizoaffective disorder,52 (c) veterans on lipidlowering medications53, and (d) a random sample of VA pharmacy users.54 Maciejewski et al.51

found that while adherence was similar between veterans with and without a copayment prior to the 

cost increase, afterward, veterans with a copayment were significantly less adherent than veterans 

without a copayment (60% vs. 69% for those with diabetes and 76% vs. 80% for those with 

hypertension at the end of the study). Similarly, among veterans using lipid-lowering medications, 

while lipid-medication use decreased overall during the course of the study, the decrease was 

more pronounced in those with a copayment53. Zeber et al.52 found that copayments had a negative 
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impact on adherence. For total prescriptions (medical and psychiatric) and medical prescriptions, 

while both the copayment exempt and non-exempt groups increased their use of medications 

over the study period, the non-exempt group did so at a significantly slower rate. For psychiatric 

medications, those exempt from copayments increased their use throughout the study period, while 

those with a copayment decreased their use nearly 25% following the price increase. Further, 

veterans with a copayment were 5% more likely to have a psychiatric admission following the price 

increase. Finally, Stroupe et al.54 found that among a random sample of VA pharmacy users, those 

with a copayment received 8% fewer 30-day refills than those without payments.

Summary of Findings

We identified four studies that examined the impact of the copayment increase on veterans’ 

adherence to medications. All four studies were of fair quality and the overall strength of evidence 

was fair. All of the studies found that increases in medication copayments led to decreases in 

medication adherence. One study52 examined system-level outcomes and found that following 

the price increase, veterans with a copayment had a greater increase in the rate of psychiatric 

hospitalization than copayment exempt veterans. No studies reported patient-level outcomes.

Other Access Interventions:

We identified three additional studies that examined the effect of intervention on access. All 

three studies were of poor study quality. Two of those examined access to specific medical 

services: treatment for hepatitis55 and specialty rehabilitation care following a lower-extremity 

amputation.56 Hagedorn et al.55 implemented a Healthy Liver Program (the goal of which was 

to increase access to the prevention, identification, and treatment of hepatitis) into a substance 

abuse clinic. The intervention included testing for all veterans at the time of intake, scheduling 

veterans who were entering the clinic into an educational healthy liver group, administration 

of vaccinations, and referrals to the hepatitis clinic as necessary. Following the intervention, 

testing for hepatitis increased significantly and 94% of appropriate veterans started a vaccine 

series. Approximately 86% of veterans complied with a 1-month booster requirement and 60% 

complied with the 6-month booster. In regard to system-level outcomes, 78% of those who 

learned they had hepatitis attended their intake at the hepatitis clinic.

Bates et al.56 examined differences in rates of referral and outcomes for veterans with a lowerextremity amputation who were at VAMCs with and without Specialized Rehabilitation Units 

(SRUs). The SRUs are multidisciplinary specialty teams which were hypothesized to increase 

awareness toward rehabilitation, which would increase access to helpful rehabilitation services. 

Contrary to expectations, Bates et al.56 found that the presence of a SRU did not increase the 

likelihood that a veteran would be referred for rehabilitation services, however, those within a 

SRU VAMC were more likely to receive specialty, rather than general rehabilitation. 

Finally, Rodriguez et al.57 conducted a qualitative study to examine elderly African American 

veterans’ reaction to a mobile geriatric care unit (MGU). The MGU was a vehicle with a checkin area, bathroom, patient education room, and examination room equipped to perform standard 

preventive care. The qualitative analyses revealed that veterans commented on the accessibility 

of care 26 times in 18 interviews. The comments were related to geographic proximity, hours of 

operation, and wait time. In regard to system-level outcomes, veterans mentioned quality of care 

28 times. No patient-level outcomes were assessed.
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SUMMARY AND DISCUSSION

CONCLUSIONS

Key Questions #1 and #1a: For outpatient care, the majority of studies we identified focused 

on the association between distance from a VA facility and utilization of VA services for 

either physical or mental health needs. Increased distance from a VA facility was consistently 

associated with decreased utilization (fair to good evidence). The pattern was observed for 

veterans in need of primary care services as well as follow-up care for substance abuse, mental 

illness, HIV, or spinal cord injury. Another important factor in utilization of VA services was 

ability to pay for care. Many studies reported increased VA care and use of VA care rather than 

non-VA care by veterans who were homeless, had an income- or disability-related priority status, 

or who were service connected. Social support and the presence of comorbid conditions were 

also factors although the results were less consistent. 

For inpatient care, higher admission and readmission rates were generally associated with 

increased distance from the admitting facility and with increased comorbidity scores. The 

choice to utilize VA or non-VA inpatient care was inversely related to distance in one study. The 

condition for which inpatient care was needed was also a factor. One study of facility wait times 

found increased probability of admission for an ambulatory care sensitive condition for patients 

visiting facilities with wait times of 29 days or longer.

Few studies included patient-level outcomes. There is limited information about the association 

between access to care and mortality, quality of life, and perceived health. 

Key Questions #2 and #2a: Taken as a whole, the results suggest that access to healthcare can 

be improved through structural / organizational interventions. All of the articles reported an 

association between the intervention and at least one measure of access (actual, perceived, or 

satisfaction with access). The evidence was strongest (fair support) for interventions regarding 

medication copayments. All four studies included in the review found that increasing medication 

copayments negatively impacted adherence. Further, the one study that examined system-level 

outcomes found that the copayment increase led to increased levels of psychiatric hospitalization. 

However, it is important to note that it is unclear whether decreasing copayments would improve 

adherence / increase access.

The implementation of CBOCs and PCMH are also promising strategies that warrant more 

rigorous examination, as the existing studies were generally of low quality. Four studies found 

a positive association between the opening of CBOCs and access to primary care, while two 

studies found that veterans were satisfied with CBOCs’ accessibility. While none of the CBOC 

articles were randomized trials, four were fair quality, cohort designs and the sample sizes for a 

majority of the studies were large, with one being VA-wide. There were six studies that presented 

data regarding the impact of PCMH integration on access. Two articles examined the impact of 

integrating mental health services into primary care clinics. Both found that PCMH integration 

increased access to mental health services. Further, it was found that less intensive models of 

PCMH implemented within CBOCs also had a significant positive impact on access. Two of 

the articles, both randomized trials (one fair quality, one good quality), evaluated the efficacy of 
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implementing primary care into mental health clinics. The integration led to self-reported and 

objective increases in access. Finally, one study (two articles), found that integrating homeless, 

mental health, and primary care services reduced wait times to primary care to less than one 

day. Thus, PCMH integration show promise, however, more research on each of the models of 

integration is needed. 

The other intervention that showed promise but requires additional research, was the use of 

telemedicine. Four studies, one of which was a fair quality RCT, showed that veterans found 

telemedicine convenient and it led to increased access to providers. The ability of telemedicine to 

improve access deserves further study, especially in light of findings that interventions delivered 

via telemedicine yield equivalent outcomes to in-person treatment (e.g., Tuerk et al.58). 

A number of other interventions (intensive case management, outreach strategies, copayments, 

mobile access units, and availability / integration of specialty care) each had one to two articles 

which examined their efficacy. While all of the interventions either resulted in referrals to 

additional care, improved wait times, better access to needed treatments (medication), or selfreported satisfaction with access, all require further validation. 

Nineteen of the 24 unique studies reported system-level outcomes. The two most frequently 

reported system-level outcomes were satisfaction with care and number of primary care visits. 

A large majority of studies that reported satisfaction found that veterans were more satisfied 

with care following the intervention; the remaining studies found no difference in satisfaction. 

In regard to primary care and general medical visits, all but one of the studies that reported on 

those outcomes found that the intervention was associated with increased utilization. Findings 

regarding the use of specialty care and hospitalization were mixed. Although few studies reported 

on the outcomes, results were consistent regarding an increase in preventive care and improved 

engagement in mental health / substance use services following the access intervention. 

Finally, only six of the 24 unique studies reported patient-level outcomes. Of those, three 

reported no significant impact of access on outcomes. One study of PCMH integration found that 

integration led to better scores on a measure of physical functioning and a second found that a 

telemedicine intervention led to improvements on mental health related quality of life. A third 

found mixed results in terms of condition-specific patient-level outcomes.

LIMITATIONS

There were several important limitations to this study. First, we identified a number of well 

designed studies that examined access interventions, but they were not included in our review 

because they did not include data regarding either actual or perceived access outcomes. 

Therefore, there may be studies that were designed to assess the impact of interventions on 

access that are not included in this review. We suggest that future research examining access 

interventions collect and compare measures of perceived and actual access across groups. 

Further, given the small number of high quality studies and the relatively small number of studies 

in support of a specific intervention, all findings require further validation. 
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RECOMMENDATIONS FOR FUTURE RESEARCH

Key Questions #1 and #1a: Additional research is warranted to further define the relationship 

between variation in access and variation in system-level and patient-level outcomes. To date, 

most research has focused on the impact of straight-line distance on utilization but actual travel 

time and ease of transportation (measures of perceived access) and wait times (for appointments 

and in clinics) may be important factors to consider. Few studies of inpatient care have looked 

at associations with ability to pay for care or social support. Many of the studies used existing 

databases which allow for large sample sizes but limit analyses to variables captured in those 

databases. For example, few studies could examine the role of non-VA care. Finally, other 

elements of access (e.g., ways in which veterans needing care enter the VA health care system, 

costs of care) and other outcomes (e.g., patient satisfaction, improved health status) should be 

addressed.

Key Questions #2 and #2a: There is a burgeoning literature base which suggests that 

interventions to increase access to healthcare may be efficacious; however, additional research 

is required. During our literature review, we identified a number of well designed studies 

that examined access interventions, but they were not included in our review because they 

did not include either actual or perceived access outcomes.58-62 When studying interventions 

hypothesized to improve access, measures of access need to be collected and compared across 

groups. Not only would this strengthen the evidence base, but would also provide data regarding 

new / different barriers that may emerge in the intervention condition (e.g., technical difficulties 

with telehealth services), and lessen the efficacy of the intervention. 

The strength of evidence was strongest for the studies that examined the impact of copayments 

on access (medication adherence). Future research should examine whether a decrease in 

copayments would increase access to needed medications. Further, the cost of copayment 

decreases as a method of improving access should be compared to the cost of other, more 

resource intensive access interventions to determine the relative cost-effectiveness of decreasing 

medication copayments.

The interventions varied tremendously in their complexity and number of components. Moving 

forward, it will be important to determine the necessary and sufficient components of access 

interventions. Further, researchers must begin to focus on the relationship between the level of 

intervention complexity and the size of its impact on access and other outcomes. Shiner et al.,38

who explored the effectiveness of five levels of PCMH integration, is an example of how such 

intensity-benefit analyses may be conducted. Within such studies, it will also be important to 

determine the cost of the intervention and the impact of the intervention on future healthcare 

costs (some included studies did report cost savings, but those outcomes were not extracted). 

Then, the complexity, intensity, and cost of the interventions can be considered when evaluating 

their impact on access. Such cost / benefit analyses may reveal significant benefits to using 

new, less resource intensive modes of accessing care (e.g., web-based, e-mail, text messaging). 

Further, moving forward, it will be important to determine the quality of care that veterans are 

receiving with increased access. As Shiner et al.38 appropriately asked in their title “Access 

to What?”, in addition to broad measures of access, future research should focus on access to 

evidence-based, quality care. 
22

Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

Finally, a majority of the articles focused on utilization and few examined patient-level 

outcomes. The data regarding utilization are difficult to interpret as it is unclear whether 

increased utilization is a desired, positive outcome. Further, given that utilization data were 

not linked to patient-level outcomes, it is not possible to determine whether the additional care 

was necessary and high quality. For example, one of the two good quality RCTs included in the 

review found that increased access to primary care actually resulted in higher rates of hospital 

readmission.45 The question of whether more, higher intensity care results in better outcomes has 

previously been examined in the literature and the findings clearly suggest that access to more 

care / higher intensity care does not consistently lead to better outcomes, and at times, may be 

associated with poorer outcomes.63-65 Given this, we recommend a decreased focus on utilization 

as an outcome and suggest that if utilization is included as an outcome, it is either specific to the 

type of care received (e.g., receipt of evidence-based care) or linked to patient-level outcomes. 

Finally, research on patient-level outcomes must be priority in the future. Such work will be 

challenging because there are a number of variables might impact both access and outcomes 

(e.g., comorbidities). Thus, rigorous, highly controlled research will be needed to ensure that 

increased access is resulting in improved health for veterans. 
23

Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

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29. Gurley D, Novins DK, Jones MC, Beals J, Shore JH, Manson SM. Comparative use of biomedical services and traditional healing options by American Indian veterans. Psychiatr Serv 

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30. West A, Weeks WB. Physical and mental health and access to care among nonmetropolitan veterans health administration patients younger than 65 years. J Rural Health 2006;22:9-16.

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33. Fortney JC, Maciejewski ML, Warren JJ, Burgess JF Jr. Does improving geographic access to VA 

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34. Fortney JC, Steffick DE, Burgess JF Jr., Maciejewski ML, Petersen LA. Are primary care services 

a substitute or complement for specialty and inpatient services? Health Serv Res 2005;40:1422-42.

35. Rosenheck R. Primary care satellite clinics and improved access to general and mental health 

services. Health Serv Res. 2000;35:777-90. 

36. Borowsky SJ, Nelson DB, Fortney JC, Hedeen AN, Bradley JL, Chapko MK. VA communitybased outpatient clinics: performance measures based on patient perceptions of care. Med Care 

2002;40:578-86.

37. Morgester WA, Biggs CJ. Community-based VHA clinics: effect on patient satisfaction and resource utilization. J Healthc Qual 2002;24:34-8.

38. Shiner B, Watts BV, Pomerantz A, et al. Access to what? An evaluation of the key ingredients 

to effective advanced mental health access at a VA medical center and its affiliated communitybased outreach clinics. Mil Med 2009;174:1024-32.

39. Watts BV, Shiner B, Pomerantz A, Stender P, Weeks WB. Outcomes of a quality improvement 

project integrating mental health into primary care. Qual Saf Health Care 2007;16:378-81.

40. Druss BG, Rohrbaugh RM, Levinson CM, Rosenheck RA. Integrated medical care for patients 

with serious psychiatric illness. Arch Gen Psychiatry 2001;58:861-8.

41. Saxon AJ, Malte CA, Sloan Kl, et al. Randomized trial of onsite versus referral primary medical 

care for veterans in addictions treatment. Med Care 2006;44:334-42.

42. Blue-Howells J, McGuire J, Nakashima J. Co-location of health care services for homeless veterans: 

A case study of innovation in program implementation. Soc Work Health Care 2008;47:219-231.

43. McGuire J, Gelberg L, Blue-Howells J, Rosenheck RA. Access to primary care for homeless veterans with serious mental illness or substance abuse: a follow-up evaluation of co-located primary 

care and homeless social services. Admin Policy Ment Health 2009;36:255-64.

44. Ritchie C, Weiland D, Tully C, Rose J, Sims R, Bodner E. Coordination and advocacy for rural 

elders (CARE): a model of rural case management with veterans. Gerontologist 2002;42:399-405. 

45. Weinberger M, Oddone EZ, Henderson WG. Does increased access to primary care reduce 

hospital readmissions? Veterans Affairs Cooperative Study Group on Primary Care and Hospital 

Readmission. New Engl J Med 1996;334:1441-7.

46. Barnett TE, Chumbler NR, Vogel WB, Beyth RJ, Qin H, Kobb R. The effectiveness of a care coordination home telehealth program for veterans with diabetes mellitus: a 2- year follow-up. Am J 

Manag Care 2006;12:467-74.

47. Hopp F, Woodbridge P, Subramanian U, Copeland L, Smith D, Lowery J. Outcomes associated 

with a home care telehealth intervention. Telemed J E Health 2006;12:297-307. 

48. Wakefield BJ, Buresh KA, Flanagan JR, Kienzle MG. Interactive video specialty consultations in 

long-term care. J Am Geriatr Soc 2004;52:789-93.
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49. Wilkins E, Lowery JC, Goldfarb S. Feasibility of virtual wound care. Adv Skin Wound Care 

2007;20:275-8.

50. McFall M, Malte C, Fontana A, Rosenheck RA. Effects of an outreach intervention on use 

of mental health services by veterans with posttraumatic stress disorder. Psychiatr Serv 

2000;51:369-74.

51. Maciejewski ML, Bryson CL, Perkins M, et al. Increasing copayments and adherence to diabetes, 

hypertension, and hyperlipidemic medications. Am J Manag Care 2010;15:e20-34.

52. Zeber JE, Grazier KL, Valenstein M, Blow FC, Lantz PM. Effect of a medication copayment 

increase in veterans with schizophrenia. Am J Manag Care 2007;13:335-46.

53. Doshi JA, Zhu J, Lee BY, Kimmel SE, Volpp KG. Impact of a prescription copayment increase on 

lipid-lowering medication adherence in veterans. Circulation 2009;119:390-7.

54. Stroupe KT, Smith BM, Lee TA, et al. Effect of increased copayments on pharmacy use in the 

Department of Veterans affairs. Med Care 2007;45:1090-7.

55. Hagedorn H, Dieperink E, Dignmann D, et al. Integrating hepatitis prevention services into a sub

stance use disorder clinic. J Subst Abuse Treat 2007;32:391-8.

56. Bates BE, Kurichi JE, Marshall CR, Reker D, Maislin G, Steineman MG. Does the presence of a 

specialized rehabilitation unit in a Veterans Affairs facility impact referral for rehabilitative care 

after a lower-extremity amputation? Arch Phys Med Rehabil 2007;88:1249-55.

57. Rodriguez KL, Appelt CJ, Young AJ, Fox AR. African American veterans’ experiences with mobile geriatric care. J Health Care Poor Underserved 2007;18:44-53.

58. Tuerk PW, Yoder M, Ruggiero KJ, Gross DF, Acierno R. A pilot study of prolonged exposure 

therapy for posttraumatic stress disorder delivered via telehealth technology. J Trauma Stress 

2010;23:116-23.

59. Bauer MS, McBride L, Shea N, Gavin C, Holden F, Kendall S. Impact of an easy-access VA 

clinic-based program for patients with bipolar disorder. Psychiatr Serv 1997;48:491-6. 

60. Bauer MS, McBride L, Williford WO, et al. Collaborative care for bipolar disorder: Part II. Impact on clinical outcome, function, and costs. Psychiatr Serv 2006;57:937-45.

61. Boutelle KN, Dubbert P, Vander Weg M. A pilot study evaluating a minimal contact telephone and mail weight management intervention for primary care patients. Eat Weight Disord 

2005;10:e1-5.

62. Egede LE, Frueh CB, Richardson LK, et al. Rationale and design: telepsychology service delivery for depressed elderly veterans. Trials [Electronic Resource] 2009;10:22.

63. Fisher, ES. Avoiding the unintended consequences of growth in medical care. JAMA. 

1999;281:446-53.

64. Fisher, ES. Medical care — is more always better? N Engl J Med 2003;349:1665-7.

65. Sirovich BE, Gottlieb, DJ, Welch HG, Fisher, ES. Regional variations in health care intensity and 

physician perceptions of quality of care. Ann Intern Med 2006;144:641-9.
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Interventions to Improve Veterans’ Access to Care Evidence-based Synthesis Program

APPENDIX A. SEARCH STRATEGY

Database: Ovid MEDLINE(R) <1950 to May Week 4 2010>

Search Strategy:

--------------------------------------------------------------------------------

1 exp *Health Services Accessibility/ (34616)

2 limit 1 to (english language and humans and yr=”1990 -Current” and “all adult (19 plus years)” 

and english) (6577)

3 *Veterans/ (4309)

4 *United States Department of Veterans Affairs/ (1252)

5 *Hospitals, Veterans/ (2008)

6 or/3-5 (6992)

7 2 and 6 (75)

8 access.mp. (114750)

9 6 and 8 (287)

10 limit 10 to (english language and humans and yr=”1990 -Current” and “all adult (19 plus 

years)” and english) (182)

11 7 or 10 (209)
28

ans’ Access to Care Evidence-based Synthesis Program

R REVIEW COMMENTS AND AUTHOR RESPONSES

RESPONSE

and methods for this review clearly described? 

t the search strategy:

to access that appears to be addressed in KQ1 was 

umerous other relevant barriers and facilitators to access 

d in KQ1, including price/income, social support, health 

alth systems (e.g., Medicare). These are all implied by 

ure 1, but only distance receives attention. A Medline 

es Accessibility” in Appendix A missed articles that 

ies that I expected to be included in KQ2.

te whether specific types of studies were explicitly 

some reason. There may not have been such exclusion, 

.

n types of interventions discussed in KQ2 would be 

had some other studies in mind and wondered what 

a. Thank you for the suggestion. We revised the KQ1 section to highlight other barriers and facilitators to access. To re-do the search at this point would markedly expand the scope and practice.b. The inclusion and exclusion criteria are outlined in the method section. We attempted to clarify that for KQ1, we included only studies that reported on how a measure of access impacted systemlevel or patient-level outcomes. Further, for KQ2, we included only studies that reported impact of the intervention on a measure of access (objective, subjective, or satisfaction with access).c. We clarified that the types of interventions were not a priori categories used in the search, but rather, we developed after the search as a way to more cohesively present the findings. A brief description of each of the types of interventions is now presented in Table 2.

bias in our synthesis of the evidence? 

above, I expected to see a review of other barriers to 

ponse to KQ1. Not sure if it represents a bias per se.

As noted above, we revised the KQ1 section.

r of studies reviewed in KQ2 that were not and it isn’t 

cluded. Not sure if it represents a bias per se.

xpected to see the following cites: Maciejewski et al. 

 2010..

ase management, I expected to see Bosworth Ann Intern 

9; Piette 2001 (diabetes); Heisler Ann Intern Med 2010; 

y VA researchers

clude papers by Stroupe Medical Care 2007 and Doshi 

Thank you for the suggested references. We have reviewed these citations and have included those that met our inclusion criteria.

 unpublished studies that we may have overlooked?

scussion of 2 Medicare papers), there are a number of 

ks, West, Liu, Morgan) that also address this issue of 

s that should be incorporated.

health applications to improve access, all published 

heVet, telemedicine, nurse case management via 

eviewed and included.

a. We have reviewed the suggested references and included those that met our inclusion criteria.b. We have included studies of e-health applications if they met our inclusion criteria and presented data regarding the impact of the intervention on a measure of access (objective, subjective, or satisfaction with access).
29

ans’ Access to Care Evidence-based Synthesis Program

ortant topic. It is even more important now that the VA 

o all clinics. This mandate makes it even more important 

ature and its limitations.

Thank you.

e much more attention to the quality of studies 

ld like some summary for each section of the types 

buting data to the discussion. There seems to be little 

nd cross-sectional studies as an example ---- no clear 

hors on how the reader should weight the study findings.

We agree and have added information about study type and quality.

distance from the VA” should be considered separately 

nd one is controlled by the patient. It seems to me that 

ient health outcomes and their association with distance 

cal system) are almost meaningless. Unless the studies 

 status, SES, patient choices, etc., the findings are not 

ation of access. It is impossible to know whether patients 

 are similar to those that are closer. Patients choose 

sons some of which could be controlled for if assessed 

 be able to be accounted for in an observational study. 

s studies that attempted to control for other factors, the 

nd weight the studies by their attempts to control for 

n the other hand, waiting times are within the control of 

 to be confounded by patient factors. I feel strongly that 

d be a subsection relating to key questions 1 and 1a. In 

weighting of the studies, these issues should be more 

Thank you for the suggestion. However, in light of the suggestion to include other barriers/facilitators, we modified the response to KQ1 to highlight factors other than distance and wait time. We organized the section by clinical area. We have rated the quality of the included studies and control of potential confounding factors was an important consideration in assigning the quality rating.

ummary of findings at the beginning of a section awkward 

hould come at the end, not the beginning of a section.

We moved the summary of findings to the end of each section.

s fairly strong yet is not discussed much if at all in the 

ly good and important data that could make a difference 

We agree and we added a discussion of the copayment studies to both the conclusions and future research sections.
30

ans’ Access to Care Evidence-based Synthesis Program

ng the literature you found under each subsection. For 

utcomes” section, I think it would be much easier to 

e what you found for these types of studies there rather 

paragraph on page 4 that precedes this section. I would 

17 studies. Were they cross-sectional, prospective or 

 RCTs and what was their quality? I would like to know 

tribute to the section. It might even make sense to divide 

clude both system level and patient level outcomes in one 

ute to both outcomes.

Thank you for the suggestion. We have added information about study design and quality to the text.

miologic thought in the discussion. The issue of more care 

 deserves a little more discussion than it was given. The 

scussed more fully in this regard.

Thank you for the suggestion. We expanded our discussion of the issue as to whether more care equates with better care and reference Weinberger 1996 as an example.
31

ans’ Access to Care Evidence-based Synthesis Program

ENCE TABLES

iation in outcomes associated with variation in access (KQ1)

clusion/Exclusion 

Criteria

Outcomes Assessed

Covariates

Impact on System-Level Outcomes Impact of Access 

on Patient-Level 

Outcomes

Interactions

lusion: Responders 

the 1987 Survey of 

terans (SOV) 

Choice of VA over other outpatient options and amount of VA outpatient useDistance, characteristics of closest VA facility, age

1) Likelihood of using VA for outpatient services decreased as distance increased up to 60 miles (little change beyond 60 miles)2) For veterans who choose some outpatient VA services, distance has a smaller additional effect on number of visits

N/A* Effect of distance on number of 

outpatient VA visits is greatest for those >65 yrs

lusion: ≥18 years 

age, first seen 

h at least one of 

sustained fever, 

nvoluntary weight 

s, c) sustained 

rrhea

clusion: cognitive 

pairment

Overall perceived access, temporal access, health related quality of life (HRQOL)Age, gender, race, mode of HIV transmission, education, income, marital status, log of CD4 counts, symptoms

Prevalence of access problems:Cost of care: 49%Office hours: 48%Location: 34%Appt. w/ Specialists: 15%Transportation time>30 min: 55%>1 hour: 17%# days to schedule urgent appt>1 day 50%>2 days 23%Office wait time>1 hour 54%>2 hours 32%

Better overall perceived access to care associated with better HRQOL for 8 of 11 scales including overall quality of life (p<0.001); temporal access scores not significantly associated with HRQOL

Adjusted access scores for VA care significantly (p<0.05) higher† for:a. covering cost of care (vs. uninsured)b. availability of emergency care (vs. uninsured or Medi-Cal)c. availability of hospital care (vs. uninsured)d. office wait time (vs. uninsured or Medi-Cal)VA scores significantly (p<0.05) lower for:a. convenience of contacting provider (vs. uninsured or Medi-Cal)b. transportation time (vs. Medi-Cal)

lusion: discharged 

the community 

m VA inpatient 

ychiatry and bstance abuse 

ograms during 

month period in 

94-95, primary 

ychiatric or bstance abuse 

order and 

condary medical 

orders

Four measures representing access, timeliness, and intensity of outpatient medical services utilizationSystem-facility factors (e.g., region, hospital size, academic emphasis, specialization in mental health care)Predisposing factors (e.g., age, gender, race, marital status, diagnosis of psychiatric or substance abuse)Enabling factors (e.g., compensation, proximity, receipt of psychiatric or substance abuse services within 30 days of discharge)Illness leading to seeking treatment

Proximity to VA clinic, receipt of VA compensation payments, mental health follow-up within 30 days of discharge, and psychiatric diagnosis associated (p<0.01) with receipt of medical-surgical follow-up within 6 month post-discharge, receipt of medical services within 30 days post-discharge, number of days from discharge until first medical visit (among those with a visit), and number of visits in 6 month post-discharge

N/A N/A
32

ans’ Access to Care Evidence-based Synthesis Program

clusion/Exclusion 

Criteria

Outcomes Assessed

Covariates

Impact on System-Level Outcomes Impact of Access 

on Patient-Level 

Outcomes

Interactions

lusion: non

titutionalized, 

ntified by random it dialing and 

m lists of patients 

rolled in VA health 

re or receiving VA mpensation or 

nsions

Treatment use over past 12 months – VA and non-VA outpatient health care visits, VA and non-VA mental health treatmentGender, age, race, education level, marital status, combat exposure; health insurance status, employment status, urban/rural residence; disability status, SF-12 mental and physical health components

Outpatient health care:1) VA visit counts associated with younger age, unmarried status, lack of health insurance, unemployment, disability rating, poorer physical health (all p<0.01) 2) non-VA visits associated with female gender, older age, college education, unemployment, disability rating, poorer physical and mental health (all p<0.01) Mental healthcare use:1) VA use associated with younger age, unmarried status, unemployment, lack of health insurance2) non-VA use associated with female gender, younger age, college education, unmarried status, unemployed, urban residence, and poorer physical and mental health

N/A N/A

lusion: English 

eaking, receiving 

atient or outpatient 

ntal health service 

HS), mid 2004 to 

d 2006 

MHS utilization (outpatient, inpatient, residential), Global Assessment of Functioning (GAF), and Behavior and Symptoms Identification Scale-24 (BASIS-24) after 3 monthsDemographics, partial self-pay for care, employment, social support, emotional support, problems getting to treatment, housing, level of care at enrollment, baseline GAF and BASIS-24, diagnoses, comorbidities, disability, service connection, MHS use 6 months prior

1) Increased outpatient utilization among patients who reported fewer access problems and no social support (both p<0.05); greatest predictor of use was clinical need2) Increased inpatient hospitalization associated with homelessness; greatest predictor was clinical need

GAF and BASIS-24 at 3 months not significantly related to access or outpatient utilization; inpatient hospitalization predicted worse GAF and BASIS-24 at 3 months

N/A
33

ans’ Access to Care Evidence-based Synthesis Program

clusion/Exclusion 

Criteria

Outcomes Assessed

Covariates

Impact on System-Level Outcomes Impact of Access 

on Patient-Level 

Outcomes

Interactions

lusion: Primary gnosis of alcohol 

pendence; 

mpleted VA 

atient program, 

charged 

h outpatient 

pointment, resided 

primary service 

ea of the inpatient 

ility 

Attendance at aftercare appointment within 30 days of dischargeTravel distance, socio-medical characteristics (age, race, severity of illness, marital status, level of urbanization)

Patients living farther from the treatment program were less likely to choose to attend their aftercare appointment as were urban residing (with distance held constant) patients and unmarried patients

N/A Older patients and rural residents 

more negatively affected by distance than younger patients or urban residents 

lusion: Walk-ins to 

ychiatric Evaluation 

nic in Emergency 

dicine Service

clusion: missing 

ta, out of state 

idence, restricted dical records

Disposition (admission or outpatient appointment) Age, marital status, employment status, ethnicity, travel distance, number of psychiatric and medical comorbidities, number of psychosocial and environmental problems, current GAF

Admissions: 17% of those living <60 mi from VAMC; 43% of those living 60+ mi from VAMC (p=0.003); controlling for case mix OR=4.8 [1.06-22.1]; age >65 and lower GAF also associated with increased likelihood of admission

N/A N/A

lusion: homeless, 

rious mental 

ess, not involved in 

going community 

atment

Lifetime use of VA health servicesAge, gender, marital status, race/ethnicity, education, military service era, addiction severity, health problems, service connection, income, residence in city with VA hospital

Veterans with service connected disabilities or non-service connected pensions or veterans living in cities with VA medical centers or hospitals were more likely to have used VA services (all p<0.05)

N/A N/A

lusion: presently 

recently 

meless military 

erans; identified 

community, VA 

spitals and clinics, 

eran’s centers, 

sons

Use of any VA services in past 6 months Metropolitan/non-metropolitan location, demographics, military history, living situation, employment, medical history

Greater use associated with metropolitan location and VA financial support (p<0.001) 

N/A Significant interactions - metro/nonmetro & use of services (p<0.05): 

Age, military service period, monthly income, time homeless, past alcohol or drug dependency
34

ans’ Access to Care Evidence-based Synthesis Program

clusion/Exclusion 

Criteria

Outcomes Assessed

Covariates

Impact on System-Level Outcomes Impact of Access 

on Patient-Level 

Outcomes

Interactions

lusion: Vietnam 

rvice, living on or 

hin 50 miles of 

ervation, born 

tween 1930 and 58

OTE: VA services 

scribed by authors 

more readily 

ailable for Northern 

ains veterans

Use of VA, Indian Health, other biomedical health services, and traditional healer (inpatient in past year, outpatient in past 6 months)

Significantly greater (p≤ 0.05) use of VA services by veterans from Northern Plains reservation communities for physical and mental health problems; significantly greater (p≤ 0.001) use of traditional healer by Southwest reservation veterans

N/A N/A

usion: discharged 

m internal medicine, 

gery, intermediate e, or neurology vices or a tertiary e VA medical center 

81 to 12/31/82 

usion: patients 

mitted to psychiatry 

vice, uncertainty 

ut readmission 

Early readmission (within 30 days of discharge) for any reasonLocation of residence (relative to VA medical center), number of surgical procedures, compensation and pension status, readmission risk class (based on diagnosis-related group), bed section of discharge, age

Increased distance of county of residence from VAMC associated with non-significant increased probability of early readmission; significantly increased probability if two or more surgeries performed, readmission risk above “very low,” or patient on intermediate, neurology, or surgery service at discharge 

N/A N/A

usion: veterans 

ble to use VA and 

dicare health care 

999, had used VA 

th services between 

7 and 1999

usion: veteran 

us unknown, missing 

nvalid zip code, lived 

uerto Rico or other 

territory, ≤65 years 

on 1/1/99, end-stage 

al disease, enrolled 

edicare+Choice 

e

VA and Medicare use (outpatient and inpatient services)Age; gender; race; vital status; VISN; priority level in VA;, health status risk score; distance to nearest VA inpatient hospital, VA outpatient center, and Medicare inpatient hospital; ZIP code (for poverty level); number of physicians, general hospitals, and beds in county of residence

Outpatient: decreased likelihood of exclusive use of VA as distance to VA increased; older age, higher health risk status, urban residence, and more hospital beds in county also associated with decreased exclusive use of VA; black race, high VA priority level, and high poverty level associated with increased exclusive use of VAInpatient services: same pattern(all p<0.01)

N/A N/A
35

ans’ Access to Care Evidence-based Synthesis Program

clusion/Exclusion 

Criteria

Outcomes Assessed

Covariates

Impact on System-Level Outcomes Impact of Access 

on Patient-Level 

Outcomes

Interactions

usion: traumatic 

ons or demyelinating 

ase of the spinal 

d; intraspinal, 

malignant plasms, vascular 

lts, cauda equina 

drome, inflammatory 

ase of the spine, 

table traumatic 

ons of the spinal 

mn

usion: multiple 

rosis; missing, 

lid, or non U.S./

rto Rico zip code; 

bile clinic use; 

esidential care 

ent; home care and health related clinic 

s, no VA utilization

Number of outpatient visits; number of inpatient dischargesHistory of illness, travel distance to actual facility used; travel distance to nearest facility, age, race, gender, marital status, level of injury

Patients utilized outpatient services less frequently when VA facilities were farther away from their residences (p<0.000); increased age, non-white race, and history of respiratory, kidney/urinary tract, circulatory, or digestive system disease associated with increased outpatient utilization (all p<0.01)Patients had less inpatient utilization if they lived at greater distances (p<0.000); history of illnesses of respiratory, skin/subcutaneous tissue/breast, kidney/urinary tract, circulatory, or digestive systems associated with increased inpatient utilization (all p<0.02)

N/A N/A

usion: diagnosis 

polar disorder, 

zophrenia, or other 

chosis in year FY 

0 with some VA 

tact in FY 1999

usion: little or no 

ngness to seek VA 

e, homeless, stay of 

+ days, died in FY 0

Total outpatient non-psychiatric visit days, total outpatient psychiatric visit daysAge, gender, race/ethnicity, marital status, urban/rural residence, distance to nearest relevant VA provider; psychiatric diagnosis type; comorbidity level, initial treatment location of FY

Patients further from outpatient care had fewer outpatient non-psychiatric visit days; older age, married, female, rural residence, initial visit at outpatient non-psychiatric facility, and higher comorbidity rating associated with increased visit days (all p<0.01)Patients further from psychiatric services had fewer outpatient psychiatric visit days; initial visit at non-psychiatric facility, higher comorbidity rating, and rural residence also associated with fewer psychiatric visits (all p<0.001)

N/A Negative effects of distance on 

outpatient non-psychiatric visits - greater for patients with schizophrenia than bipolar disorders and for patients >65 yrs; on outpatient psychiatric visits - greater for patients with schizophrenia and for ages 45 to 65 yrs.
36

ans’ Access to Care Evidence-based Synthesis Program

clusion/Exclusion 

Criteria

Outcomes Assessed

Covariates

Impact on System-Level Outcomes Impact of Access 

on Patient-Level 

Outcomes

Interactions

usion: diagnosis of 

zophrenia or bipolar 

rder in FY 1998

usion: missing data 

laska resident

Time to first 12-month gap in 1) VA health services utilization and 2) VA mental health services (through the end of FY 2002)Age, gender, marital status, race/ethnicity, VA service connection status, homelessness, primary psychiatric diagnosis, comorbidity index, distance to nearest VA service site or VA provider of substantial psychiatric services, inpatient care in FY 1998, VA and non-VA inpatient beds per 1000 county residents

Risk of gap in health service utilization increased with increased distance to nearest VA facility, homelessness, inpatient stay in FY98, and unknown or non-white race; decreased with more VA beds, increased age, female gender, married, VA service connection, higher comorbidity score, diagnosis of schizophrenia (all p<0.05)Risk of gap in mental health utilization increased with residence further from VA psychiatric service site, age, female gender, non-white race, homelessness, higher comorbidity score, inpatient stay in FY98; decreased with married, VA service connection, diagnosis of schizophrenia (all p<0.05)

N/A N/A

usion: enrolled in 

A and Medicare for at 

t 1 month in 2002

VHA pharmacy useHealth status, income, race/ethnicity, age, metropolitan/nonmetropolitan status, participation in Medicaid, VA priority status

Decreased likelihood of using VHA pharmacy if enrolled in Medicare HMO plan with pharmacy benefits, older than 65 yrs, income of $20,000 or greater, female, priority status other than 1 (no copayment), Medicare state buy-in, resident of metropolitan statistical area, and patient at a teaching hospitalIncreased likelihood if Hispanic race and poorer health status

N/A N/A

usion: inpatient or 

patient VA or Fee 

s use FY 2003 & 

4 who were also 

dicare enrollees 

uding < 65 yrs)

usion: missing 

rity classification, 

nostic data, or ZIP 

e; died in FY 2003 or 

4; ZIP code outside 

S

Reliance on VA health care (overall, inpatient, outpatient)Age, gender, race, differential distance (distance to VA Medical Center minus distance to non-VA hospital), priority classification, aggregated conditions categories (ACCs)

Overall increased reliance on VA care if differential distance is lower, if under age 65, or if disability or low income VA priority classification; mental health and substance abuse ACCs significantly associated with increased reliance on VA careSimilar results for outpatient carePatients with transplant and amputation ACCs more likely to have inpatient VA care; other ACCs associated with inpatient VA care included infectious and parasitic disorders, substance abuse, mental health disorders, and eye disorders

N/A Interaction of age and distance was 

significant but parameter effects were less than main effectsMental health and diseases of eyes, ears, nose, and throat associated with increased reliance on VA care for <65 yr groupMental health, substance abuse, diabetes, and infectious diseases associated with increased VA care for ≥65 yr group
37

ans’ Access to Care Evidence-based Synthesis Program

clusion/Exclusion 

Criteria

Outcomes Assessed

Covariates

Impact on System-Level Outcomes Impact of Access 

on Patient-Level 

Outcomes

Interactions

usion: Admitted to 

acute care hospital, 

harge diagnosis of 

cardial infarction usion: Death or 

dmission within 90 

s of index discharge; 

x length of stay 

0 days, reside >100 

rom a source of VA 

e or >200 mi from 

mitting facility 

Outpatient medical care visits within 30 and 90 days of discharge following acute MI admission; death from all causes or recurrent cardiac admission 91 to 365 days after dischargeAge, VA service connection, comorbidity index, alcoholism, teaching hospital, catheterization or revascularization procedure

Patients with service connected disability, over age 55, with comorbid conditions, discharged from a teaching hospital, and having revascularization are more likely to have 1 or more visits within 30 days; patients with history of alcohol abuse and living more than 20 miles from admitting hospital were less likely (all p<0.05); similar pattern for 1 or more visits within 90 days except comorbidity, alcoholism, and hospital type not related

Age greater than 55, comorbidities, and distance greater than 20 miles associated with increased risk of death within 1 year; revascularization procedure and any VA ambulatory care in 90 days after index visit associated with decreased risk of death (all p<0.05); age greater than 65, comorbidities, and any VA ambulatory care in 90 days associated with increased risk of readmission (all p<0.05)

N/A

usion: veterans ≥65 

rs old who visited at 

t one of three types 

A geriatric outpatient 

cs between 

/00 and 6/30/01 

 survived through 

0/01

6-month mortality (odds of dying between 10/1/01 and 3/31/02)Age, gender, principal diagnoses, comorbidity index, preventable hospitalization in past year, service connected disability (50% or greater); facility 3-month mortality rate, facility wait time

N/A Facility-level wait times 

of ≥31 days associated with significantly higher mortality; increased age, ≥ 50% service connected disability, preventable hospitalization, higher comorbidity index, and diagnosis of cancer or endocrine, neurological, psychiatric, pulmonary, or other disease associated with increased mortality; female gender associated with decreased mortality (all p<0.05)

N/A
38

ans’ Access to Care Evidence-based Synthesis Program

clusion/Exclusion 

Criteria

Outcomes Assessed

Covariates

Impact on System-Level Outcomes Impact of Access 

on Patient-Level 

Outcomes

Interactions

usion: same as 

ve except visits 

ween 10/1/00 and 

/01, surviving 

ugh 6/30/01

Dependent variable: probability of hospitalization for an ambulatory care sensitive condition between 7/1/01 and 12/31/01Age, gender, principal diagnoses, comorbidity index, ambulatory care sensitive condition (ACSC) hospitalization in past year; facility 3-month ACSC hospitalization rate

Facility-level wait times of ≥29 days associated with greater probability of hospitalization for ACSC compared to wait times of <22.5 daysFacility average ACSC hospitalization rate, age, previous ACSC hospitalization, cormobidity index, and diagnosis of cancer, or endocrine, heart, or pulmonary disease also associated with increased probability of ACSC hospitalization (all p<0.02)

N/A N/A

usion: Admitted to 

stance abuse units, 

ble for outpatient 

rcare

usion: Discharged 

nst medical 

ce, death or re

pitalization within 90 s of index discharge, 

valid zip code of 

dence

Use of any outpatient aftercare, number of mental health clinic visits within 90 days (for those with at least one visit)Comorbidity index

Increased likelihood of receiving aftercare if distance < 50 miles with greatest likelihood if distance <10 miles; age, married, service-connected eligibility, psychiatric comorbidity, substance use disorder, and teaching hospital associated with increased likelihood; medical comorbidity index 1, 2, or > 4 associated with decreased likelihood (all p<0.05)Volume of aftercare only greater if distance <10 miles (relative to >50 miles)

N/A N/A 

usion: Non-veteran 

o longer in military 

vice

usion: refused 

ay or didn’t know 

ther ever in military 

vice

Health in general, maximum poor health days (physical, mental, or limited usual activity in prior month), inability to afford needed care in past year

Non-metropolitan VA patients age 18 to 44 were significantly more likely to say they needed to see a doctor but could not because of cost than others of same age (p<0.005); among 45 to 64 year olds, VA patients (regardless of residence) more likely to report cost as a factor in accessing needed treatment 

Self-reported health poorest for nonmetropolitan veterans in VA care age 45 or olderDays in past 30 of poor health highest for veterans in VA care regardless of residence(NOTE: veterans in VA care identified based on self-reported use of VA in past 12 months)

N/A
39

ans’ Access to Care Evidence-based Synthesis Program

clusion/Exclusion 

Criteria

Outcomes Assessed

Covariates

Impact on System-Level Outcomes Impact of Access 

on Patient-Level 

Outcomes

Interactions

usion: ≥65 yrs on 

e of admission, 

enrollee for whom 

dicare claims were 

mitted; received any 

4 high-risk elective 

cedures

Utilization of VA or non-VA care, utilization of lower or higher quality care

Overall, 89% of heart surgeries, 84% of vascular surgeries, and 79% of cancer resections obtained in non-VA hospitals with little difference based on residenceUrban residents more likely to obtain heart surgery (significant only for bypass grafting) and cancer resection in high performance hospitals; rural residents more likely to get vascular surgery in high performance hospitalsTravel time to high performing hospital indicated that urban veterans had least travel burden; travel time to high performance hospital for heart surgery was shorter than to low performance, regardless of residence; no difference for vascular surgery

N/A N/A

rticipant selection, outcomes assessment, and analysis (see text); †Access scores: 0=worst possible access, 100=best possible access; *N/A=Not 

 1 to September 30 of the following year); NS=non-significant; VISN=Veterans Integrated Service Network
40

ans’ Access to Care Evidence-based Synthesis Program

 efficacy of interventions designed to increase access for veterans (KQ2)

etting Patient

Characteristics

Intervention / 

Comparator

Impact of Intervention on 

Access

Impact of Intervention on SystemLevel Outcomes Impact on Intervention 

on PatientLevel 

Outcomes

Community Based Outpatient Clinics (CBOCs) – Opening of satellite primary care clinics 

CBOCS 

36 

es

ding 

nt 

MCs

Randomly selected subset of veterans who had care at one of the selected CBOCs or VAMCs in the preceding six months.

Utilization of CBOCS / VAMC users

Veterans using CBOCs reported better access / timeliness and were more likely to report waits less than 20 minutes.

Veterans using CBOCS had more ratings of good / excellent visits; fewer problems in a variety of areas (e.g., emotional support, preferences, care coordination, education, courtesy).

N/A

CBOCs 

32 

nt 

MCs

All primary care patients treated at participating CBOCs or VAMCs.

Utilization of CBOCS / VAMC users

CBOC patients more likely to be new VA users.

CBOC patients had more primary care encounters and fewer specialty care encounters.

N/A

en 

OCS 

offered 

ary 

 and 

ned 

ng a 

month 

od in 

7

All veterans living in the CBOC catchment area who had any VA service use in the six months before the CBOC opened. Included a matched group of veterans residing outside the catchment area of any new CBOCs

Implementation of CBOCs / pre-CBOC implementation

Decrease in travel distance to the closest VA facility for those in CBOC catchment area.

Decrease in travel distance predicted increase in primary care encounters; across diagnoses, those in CBOC catchment had more primary care visits, ancillary visits, and extended care physical health visits.

N/A

 CBOC 

the 

nt 

MC

Veterans with an appointment at the CBOC or VAMC during the recruitment period; veterans who lived in the CBOC catchment area and received non-VHA primary care

Utilization of CBOCS / utilization of VAMC or nonVA care

All three groups (VAMC, CBOC, non-VA care) reported few problems finding clinic (93-100%) and found the hours of operation convenient (97-100%). There were no statistical comparisons. 

All three groups (VAMC, CBOC, non-VA care) reported satisfaction with care (93-100%); 82-83% of the VAMC and 90-93% of the CBOC veterans reported they had enough information about their condition and medication; 93% of CBOC and 90% of VAMC veterans felt they could care for themselves until next visit. There were no statistical comparisons. 

N/A
41

ans’ Access to Care Evidence-based Synthesis Program

etting Patient

Characteristics

Intervention / 

Comparator

Impact of Intervention on 

Access

Impact of Intervention on SystemLevel Outcomes Impact on Intervention 

on PatientLevel 

Outcomes

ounties 

the 

rict of 

mbia 

mpared 

e with 

without 

OCS 

opened 

1995-

8).

All veterans, based on census data

Implementation of CBOCs/ pre-CBOC implementation

Significantly greater proportion of veterans in counties with CBOCs accessed general VA medical services. In counties with CBOCs that had specialty mental health, mental health access greater.

N/A N/A

Primary Care Mental Health Integration – Co-location of primary care and mental health services

ater Los 

eles 

Medical 

ter

All veterans newly entering the Homeless Program

Implementation of integrated mental health, primary care, and homeless social services clinic / pre-implementation

Shorter wait time for initial primary care visit.

Improved preventive care, more primary care visits, lower emergency care service use.

No significant differences.

e VA 

ical 

ter

Veterans within mental health clinic without a primary care provider.

Integrated primary care services into mental health clinic / usual care.

Better self-reported access. More primary care visits, fewer ER 

visits, improved preventive care, higher satisfaction 

Higher (better) scores on the SF-36 physical component summary.

Puget 

nd 

th Care 

em

Veterans presenting for substance use treatment who did not have a primary care provider and had at least one chronic health or asymptomatic condition (e.g., high blood pressure).

Implemented an onsite (within the substance use clinic) primary care clinic /usual care

Shorter wait for initial primary care visit; greater odds of attending rescheduled initial visit; more likely to attend at least 1 primary care visit.

More likely to attend return primary care visits and averaged more primary care visits; less non-VA primary care. More likely to remain engaged in substance use treatment at 60 days.

No significant differences
42

ans’ Access to Care Evidence-based Synthesis Program

etting Patient

Characteristics

Intervention / 

Comparator

Impact of Intervention on 

Access

Impact of Intervention on SystemLevel Outcomes Impact on Intervention 

on PatientLevel 

Outcomes

e 

MC 

three 

OCs

Veterans who screened positive for depression in primary care.

Varying models of Primary Care Mental Health (PCMH). The VAMC had co-location of, and advance or open access to mental health providers; and standardized assessments. CBOC-A had walk in access one day per week, evaluation by a psychotherapy and a psychopharmacologically oriented provider, and standardized assessment. CBOC-B had a psychotherapist as part of the primary care team and back-up telepsychiatry services (by appointment). CBOC-C did not have PCMH, but mental health care was available at the CBOC. CBOC-D did not have PCMH and there was no mental health care on site (comparator).

Following implementation, VAMC and CBOC-A had increases in veterans seen in mental health within both 4 days and 30 days. CBOC-B had an increase of veterans seen within 30 days and percentage receiving optimal care. No differences in CBOCs C & D.

More patients at VAMC, CBOC-A, and CBOC-B received “optimal depression treatment.”

N/A

e River 

ction 

MC & 

OCs

Veterans who screened positive for depression in primary care

PCMH Integration / no PCMH integration 

More patients received mental health services in primary care and were seen in mental health; shorter wait time for initial mental health appointment (all outcomes only significant for VAMC, not CBOCs)

More patients received “optimal depression treatment” (at VAMC, not CBOC)

N/A

ve Case Management – High intensity treatment coordination to facilitate identification of and access to needed services

 VAMCs Elderly veterans in rural 

counties who were frail and at risk of repeated hospitalization

Pilot implementation of the Coordination and Advocacy for Rural Elders (CARE) program, which performs scheduled, standardized assessments; identifies problems; develops care plans; and tracks resolution of problems / no comparison

Over 56% received a medical service of referral / linkage. 

N/A N/A
43

ans’ Access to Care Evidence-based Synthesis Program

etting Patient

Characteristics

Intervention / 

Comparator

Impact of Intervention on 

Access

Impact of Intervention on SystemLevel Outcomes Impact on Intervention 

on PatientLevel 

Outcomes

e 

MCs with 

rsity in tion and 

demic 

ation

Hospitalized veterans with one of three chronic diseases without continuous primary care.

Implemented intensive primary care program designed to increase access to primary care; intervention included both an inpatient (e.g., followup planning, scheduling) and outpatient (e.g., appointment reminders, check-in phone call) components / usual care

Median time from hospital discharge to primary care shorter. Better satisfaction with self-reported access.

More likely to have at least one general medical clinic visit; more general medical clinic visits during six-months post-discharge; higher monthly hospital readmission rate; more days of hospital readmission; greater satisfaction with care.

No significant differences.

Telemedicine – Conducting encounters via telephone or interactive video conferencing

r 

MCS 

orida, 

rto 

, and 

rgia

Older veterans with type two diabetes at high risk for multiple VA inpatient and outpatient visits.

Nurse coordinators monitored data from a home telehealth messaging device and made phone calls or scheduled appointments with the physician as necessary / treatment as usual

Care coordinator-initiated primary care clinic visits increased by 8.9%.

Decrease in all cause hospitalization, diabetes related hospitalizations (no longer significant after controlling for baseline A1C).

N/A

me care 

ice line 

large 

MC in 

anapolis

All patients receiving home care services at the VAMC

In addition to traditional home care services, participants contacted VAMC using telehealth units / home care as usual

Most reported that their level of contact with VA providers increased.

No significant differences. Improvement 

on the mental component summary of the Health Related Quality of Life scale 

 VAMCs 

a long 

 care ty

Residents living at the Iowa Veterans Home.

Implemented interactive video conferencing to provide specialty consultation to veterans living at the long term care facility / no comparator

92% of veterans reported that using telemedicine made it easier to see the specialist.

81% of veterans reported satisfaction with the telemedicine consultation process.

N/A

 VAMCs 

out 

idisci

ary 

nd care 

ms

Veterans with a wound who sought care at a VAMC without a wound care team.

Implemented telemedicine to seek consultations from a remote wound care team/ no comparator

Veterans reported that telemedicine was more convenient than travelling to wound care team.

Almost all (92.8%) participants were satisfied with telemedicine.

N/A 
44

ans’ Access to Care Evidence-based Synthesis Program

etting Patient

Characteristics

Intervention / 

Comparator

Impact of Intervention on 

Access

Impact of Intervention on SystemLevel Outcomes Impact on Intervention 

on PatientLevel 

Outcomes

Outreach – Providing information about how to access care

e urban 

MC

Vietnam veterans living in vicinity of VAMC who are service-connected for PTSD without use of VA mental health or substance use services in the prior 12 months.

Outreach intervention with (1) a mailing which included information regarding PTSD treatment services and a letter from the PTSD program outlining three ways to initiate care (return postcard, call, or walkin clinic) , and (2) direct phone call during which veterans could ask about services, schedule an appointment, or address barriers / no intervention control group.

Significantly more likely to schedule an intake, present for intake session.

Significantly more likely to attend at least one follow-up session.

N/A

Copayments – Change in medication copayments

 large 

MC

Veterans on lipid-lowering medications

Increase in medication copayments from $2 to $7 / copayment exempt.

Lipid refill rates decreased for all veterans after copayment increase, but the decrease small among those without copayment.

N/A N/A

r large 

MCs

Veterans with diabetic or hypertension who had a prescription for those conditions (a portion of whom had copayments).

Increase in medication copayments from $2 to $7 / copayment exempt.

At the end of the study, lower adherence to diabetic and hypertensive medications among veterans with a copayment.

N/A N/A

Wide A random sample of 5% 

of VA pharmacy users.

Increase in medication copayments from $2 to $7 / copayment exempt.

Those with a copayment received 8% fewer 30-day refills than those without payments.

N/A N/A
45

ans’ Access to Care Evidence-based Synthesis Program

etting Patient

Characteristics

Intervention / 

Comparator

Impact of Intervention on 

Access

Impact of Intervention on SystemLevel Outcomes Impact on Intervention 

on PatientLevel 

Outcomes

wide All veterans receiving 

a diagnosis of schizophrenia or schizoaffective disorder from 1998-1999 (a portion of whom had copayments).

Increase in medication copayments from $2 to $7 / copayment exempt.

For all medication and medical prescriptions: those exempt from copayments, prescriptions increased steadily throughout study, while for those with a copayment, growth slowed after price increase. For psychiatric drugs: for those exempt from copayments, prescriptions increased throughout study, while for those with a copay, use decreased after price increase.

Copayment group more likely to have psychiatric admission.

N/A

Other Access Interventions

 types 

AMCs, 

e with 

without 

cialized 

b units

Veterans with lowerextremity amputations during study time frame.

Presence of Specialized Rehabilitation Unit (SRU) within the hospital / hospital without an SRU

No difference in the probability of receiving an initial rehabilitation consult; those in SRU more likely to receive specialized rehabilitation.

Longer length of non-ICU stays in SRU VAMCs. 

Problems in peripheral circulation more common in non-SRU VAMCs, skin breakdown more common in SRU VAMCs. 

bstance 

clinic 

n a 

e VAMC

Veterans receiving services within the substance use clinic

Implementation of the Healthy Liver Program, designed to increase access to services for the prevention (vaccination), identification (testing), and treatment (referrals) of viral hepatitis within a substance use clinic / preimplementation.

Testing for hepatitis increased, 94% of appropriate veterans started the vaccine series (vaccine was not available prior to implementation).

78% of those who learned they had hepatitis attended their intake at the hepatitis clinic.

N/A
46

ans’ Access to Care Evidence-based Synthesis Program

etting Patient

Characteristics

Intervention / 

Comparator

Impact of Intervention on 

Access

Impact of Intervention on SystemLevel Outcomes Impact on Intervention 

on PatientLevel 

Outcomes

 low me 

n 

h

oods 

n 

VA 

burgh 

thcare 

em

Elderly, urban, predominately African American men receiving care at one of the mobile care units.

Implemented a mobile care program, which had healthcare staff and resources to conduct basic medical care within the van/no comparator.

Accessibility of care was mentioned 26 times in 18 interviews (2nd most common topic behind quality of care).

Quality of care was mentioned 28 times in 18 interviews.

N/A