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Health-Related Quality of Life in Patients Served by the Department of Veterans Affairs
Results From the Veterans Health Study
Lewis E. Kazis, ScD;
Donald R. Miller, ScD;
Jack Clark, PhD;
Katherine Skinner, PhD;
Austin Lee, PhD;
William Rogers, PhD;
Avron Spiro III, PhD;
Susan Payne, PhD;
Graeme Fincke, MD;
Alfredo Selim, MD;
Mark Linzer, MD
Arch Intern Med. 1998;158:626-632.
ABSTRACT
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Background The Department of Veterans Affairs Health Care System (VA) is the largest integrated single payer system in the United States. To date, there has been no systematic measurement of health status in the VA. The Veterans Health Study has developed methods to assess patient-based health status in ambulatory populations.
Objectives To describe the health status of veterans and examine the relationships between their health-related quality of life, age, comorbidity, and socioeconomic and service-connected disability status.
Methods Participants in the Veterans Health Study, a 2-year longitudinal study, were recruited from a representative sample of patients receiving ambulatory care at 4 VA facilities in the New England region. The Veterans Health Study patients received questionnaires of health status, including the Medical Outcomes Study Short Form 36-Item Health Survey; and a health examination, clinical assessments, and medical history taking. Sixteen hundred sixty-seven patients for whom we conducted baseline assessments are described.
Results The VA outpatients had poor health status scores across all measures of the Medical Outcomes Study Short Form 36-Item Health Survey compared with scores in non-VA populations (at least 50% of 1 SD worse). Striking differences also were found with the sample stratified by age group (20-49 years, 50-64 years, and 65-90 years). For 7 of the 8 scales (role limitations due to physical problems, bodily pain, general health perceptions, vitality, social functioning, role limitations due to emotional problems, and mental health), scores were considerably lower among the younger patients; for the eighth scale (physical function), scores of the young veterans (aged 20-49 years) were almost comparable with the levels in the old veterans (>65 years). The mental health scores of young veterans were substantially worse than all other age groups (P<.001) and scores of screening measures for depression were significantly higher in the youngest age group (51%) compared with the oldest age groups (33% and 16%) (P<.001).
Conclusions The VA outpatients have substantially worse health status than non-VA populations. Mental health differences between the young and old veterans who use the VA health care system are sharply contrasting; the young veterans are sicker, suggesting substantially higher resource needs. Mental health differences may explain much of the worse health-related quality of life in young veterans. As health care systems continue to undergo a radical transformation, the Department of Veterans Affairs should focus on the provision of mental health services for its younger veteran.
INTRODUCTION
THE DEPARTMENT of Veterans Affairs Health Care System (VA) is a federally funded integrated system of care, with about 5% of the total market share for hospital services.1 It serves a select group of veterans, with complex health care needs. Compared with veterans nationally and the general US population, users of the VA health care system not only have disabilities that are connected to their military service but they are also older, poorer, less educated, and sicker with more disease.2-3 Lessons learned from the VA can provide a model for monitoring the outcomes of care in other managed care systems, especially those serving older populations. Like other health care systems that are seeking to adapt to a changing health care environment, the VA needs information about the health of current and prospective patients to anticipate patient demand, design effective services, and evaluate the outcomes of its care. The information that the VA has at hand to guide providers of care, administrators, and policymakers regarding ambulatory care is limited. In response to these needs, the Veterans Health Study (VHS) was developed to implement and demonstrate the use of monitoring patient-derived measures of functional status in the VA.
In recent years new approaches for assessing the health of patients have been developed. These approaches are patient-derived measures of health status or health-related quality of life (HRQoL). These methods for assessing health have received considerable attention toward the goal of providing rigorous methods for evaluating impacts of medical interventions on patient outcomes. These measures are obtained directly from the patient using structured questionnaires that provide assessments of functional status (physical, psychological, social, and role functioning) and overall perceptions of health. Patient-derived measures of health status are especially pertinent to health systems such as the VA, since health status information provides a useful and comprehensive assessment of the needs of veterans for monitoring their outcomes of care. In this article, we report the characteristics of a VA outpatient population in terms of sociodemographics, disease prevalence, and HRQoL. We report on some of the unique characteristics of users of the VA ambulatory health care system. We describe veterans' health status and examine its relationships to age, disease, socioeconomic status, and service-connected disability status. This health status information used to characterize the heterogeneity of the veteran population is important in providing a baseline set of assessments for future studies that will monitor the outcomes of care.
METHODS
VETERANS HEALTH STUDY
The conceptual framework and methods of the VHS are described elsewhere.4-5 Briefly, we characterized the health status of patients using multidimensional assessments of HRQoL. In doing this, we are building on the work of previous studies, most notably the Rand Health Insurance Experiment and the Medical Outcomes Study.6-7 These studies have demonstrated the value and utility of patient-based measures of HRQoL.
STUDY DESIGN
The VHS is a 2-year prospective study. Patients were recruited from a cross-sectional sample of the VA patient population receiving ambulatory care at 4 VA facilities in the greater Boston, Mass, area.
The study sites represent clinical settings that are fairly typical of VA ambulatory care. They differed from each other in a number of ways, including geographic location, type of hospital (ie, 2 outpatient clinics, geriatric and extended care facility, and tertiary care hospital), organizational structure, and types of medical care provided. Sites include a large tertiary care facility, a long-term care facility, and 2 freestanding satellites providing ambulatory care services.
Male patients were identified when they came to ambulatory care clinics for a medical visit between August 1993 and December 1995. Eligibility for the study included all patients identified in the clinic who (1) had a medical visit to a VA ambulatory clinic in the past 12 months, (2) provided contact information, such as telephone number and/or address, and (3) read and signed the consent form. Eligible patients were randomly sampled, contacted via telephone, and recruited for the study. All recruited patients were mailed a questionnaire that included the Medical Outcomes Study Short Form 36-Item Health Survey (SF-36) and were scheduled for a health examination, including physical examination, clinical assessments, and medical history taking. Examined patients also completed a questionnaire that included a depression screening measure, and questions about sociodemographics, military history, and VA eligibility. Data collection occurred in 3 waves, each separated by 8 months to control for seasonal variations. Examined patients were impaneled over time and their health was monitored with brief mailed questionnaires on a quarterly basis and with follow-up examinations at 12 and 24 months.
Five thousand six hundred sixty-seven patients have been surveyed and 1667 patients for whom we conducted baseline assessments are included in this study. Of the eligible patients, 58% participated. Nonparticipants who were approached were not significantly different from the participants in terms of sociodemographics or general health measures except that nonparticipants had slightly less education.
STUDY MEASURES
Short Form 36-Item Health Survey
The SF-36 is our primary measure of HRQoL. This assessment has been extensively documented as reliable and valid in ambulatory patient populations.8-9 Because the SF-36 is being disseminated as a standard core set of HRQoL assessments, we examined the utility of this battery for use in VA populations. The SF-36 assesses 8 dimensions of health status, spanning a spectrum from physical to mental health. This health survey includes measures of physical functioning, role limitations due to physical problems, bodily pain, general health perceptions, vitality, and social functioning, and role limitations due to emotional problems and mental health. The tables and figures in this study are arranged so that the 8 scales reflect this ordering and first indicate content in the scales that are more physical (physical functioning and role limitations because of physical problems), then switch to scales that involve both physical and mental concepts (eg, bodily pain, general health perceptions, vitality, and social functioning), and last include scales that are more psychologically based (role limitations because of emotional problems and mental health). Items from each concept are summed and rescaled with a standard range of 0 to 100, where 100 denotes the best health, to permit comparisons with other populations. The 8 SF-36 scales have been summarized into 2 component summary scales, a physical component summary (PCS) and a mental component summary (MCS). The summary scales are based on distinct physical and mental constructs that are well documented in the literature.10 Eighty-five percent of the reliable variance in the 8 SF-36 scales is explained by the physical and mental dimensions of health. The 2 summary component scales, PCS and MCS, were each scored using weights derived from a national probability sample. Each summary is expressed as a t score with a mean of 50 (SD, 10), which facilitates comparisons between the VA patients and the general US population.
Results for the SF-36 scales produced Cronbach's  ranging from .93 for physical functioning to .78 for social functioning.
Medical History
Medical history was assessed using an interviewer-administered questionnaire previously adapted and modified from the Medical Outcomes Study.11 This questionnaire has been clinically validated and tested in prior work. A number of questions were added to identify patients with currently active medically diagnosed conditions, including hypertension, diabetes, chronic lung disease, osteoarthritis of the knee, chronic low back pain, and alcohol-related disorders. The presence of these study conditions has been corroborated by chart audit, and levels of agreement between the 2 data sources range from 95% for diabetes to 70% for low back pain.12-13 Using information obtained from the medical history, we developed an index of the number of health conditions or morbidities that ranged from 1 to an observed maximum of 22. These health conditions include symptoms and reported morbidities (eg, anemia, angina pectoris, congestive heart failure, dermatitis, diverticulitis, enlarged prostate, dizzy spells, fainting spells, gout, inflammatory bowel disease, skin cancer, or thyroid disease). This index has been validated against SF-36 and measures of utilization.14
OTHER CLINICAL ASSESSMENTS, SOCIODEMOGRAPHICS, AND SERVICE-CONNECTED DISABILITY
Depression was assessed using the 3-item screening instrument developed by Rost and coworkers15 that includes items from the Diagnostic Interview Survey and the Center for Epidemiologic Studies in Depression. Alcohol-related disorders (abuse or dependence) were defined as 2 or more positive responses to an alcoholism screening questionnaire containing 4 structured questions (CAGE) together with reported alcohol consumption within the past 12 months.16
Sociodemographic information reported includes age (calculated using the date of birth and the date of initial contact in the study), years of education (range, 1 to >16 years), race, marital status, and income. Patients also responded to questions regarding their military experience, including the period(s) that they served on active duty and whether they were in combat.
Characteristics of the veteran population who use VA health care include military duty during a war or conflict and a service-connected disability or qualifying by a means test based on income (the VA test for free care is approximately $19000 of household income). These factors are relevant because they profile veterans who are eligible for VA care and influence the population of veterans who are most likely to use the VA. Therefore, we included the veteran's service-connected disability status and their rating (range, 0%-100%, where 100% is total disability). The assignment is made on the basis of health conditions that occurred during or as a result of military service. The VA is required to furnish outpatient care without limitation to veterans with 50% or more service-connected disability. The rating reported herein was obtained from the VA hospital–based administrative computer system.
STATISTICAL ANALYSIS
Analysis included evaluation of bivariate associations using contingency tables for categorical variables. For most analyses, the sample was divided into 3 age groups, 22 to 49 years, 50 to 64 years, and 65 years or older, reflecting the observed trimodal age distribution that coincides with the 3 major eras of service, that is, Vietnam, Korea, and World War II. We report the scores from the SF-36 scales and 2 component summary scores by the 3 age groups using means and 95% confidence intervals. Analysis of variance and pairwise comparisons are used to report significant differences between the groups. Tests for linear trend are reported for the SF-36 scores. Least squares regression analysis was used to estimate the associations of sociodemographics (age, education, race, marital status, and income), selected prevalent conditions (hypertension, angina, diabetes, osteoarthritis, chronic low back pain, chronic lung disease, alcohol-related disorders, depression), number of other comorbidities, and service-connected disability rating with each of the SF-36 scales and 2 components. Sets of independent variables were entered into the regression analysis model sequentially to assess the incremental R2 that they contributed.
RESULTS
In the sample of 1667 VA ambulatory patients, ages ranged from 22 to 90 years (mean, 62 years; median, 65 years). Eighteen percent of the 1667 veterans in this study were aged 22 through 49 years, 29% were 50 through 64 years, and 52% were 65 through 90 years (Table 1). Fifty-eight percent of the patients had 12 or fewer years of education, 92% were white, 58% were married, and 52% had an income of $20000 or lower. Results by age group indicated that the younger groups were less often married, more highly educated, and had higher incomes (P<.001). Overall, 36% of the patients had disability ratings that were higher than 50%, and the proportion higher than 50% ranged from 42% in the youngest to 33% in the oldest age groups (P<.05). Forty-six percent of the patients reported combat experience, with a range from 26% in the middle-age group to 59% in the oldest group. Forty-eight percent of the total patient sample reported serving during the World War II era, 30% during the Korean era, and 22% during the Vietnam era. By age group, 98% reported serving during the Vietnam era in the youngest age group (22-49 years), 85% during the Korean era in the middle-age group (50-64 years), and 91% during the World War II era in the oldest group (65-90 years).
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Table 1. Characteristics of Outpatients Served by the Department of Veterans Affairs Participating in the Veterans Health Study
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Patients had an average of 5.8 diagnoses (Table 2). The most prevalent conditions were hypertension and angina (41% and 26%, respectively), and the least prevalent conditions were chronic lung disease and alcohol-related disorders (15% and 11%, respectively). The youngest age group had lower prevalence rates for hypertension, angina, diabetes, and osteoarthritis compared with the other age groups (P<.001). However, for chronic low back pain, the youngest group had a higher prevalence than the older groups (P<.01). Depression was more common in the youngest (51%) than the other 2 age groups (33% and 16%, respectively) (P<.001). Similarly, alcohol-related disorders had a higher prevalence in the youngest age group (21% vs 15% and 6%, respectively) (P<.001).
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Table 2. Prevalence of Health Conditions Among Outpatients Served by the Department of Veterans Affairs in the Veterans Health Study
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Compared with published data from non-VA systems of care (health maintenance organizations and multispecialty groups), mean scores for each of the 8 scales are at least 50% of 1 SD worse compared with those of patients seen in non-VA systems of care controlling for age and sex.17-18
The results of the SF-36 by the 3 age groups with 95% confidence intervals are presented in Figure 1. With the exception of physical function, 7 of the scales have lower scores (worse health) for the younger age groups. Predictably, physical function scores are lower in the older age groups. With the exception of role limitations due to physical problems, the linear age trends are highly significant (P<.001, by analysis of variance F test of trend). Figure 2 presents results of the PCS and MCS components by age group. Results for the PCS show a linear trend and slightly worse health in the older age groups (P<.05). This trend does not mirror the stronger trends often seen in non-VA ambulatory settings, where increasing age is associated with declining overall physical health status, possibly because of the relatively low physical health score in the youngest age group.19 The MCS scores indicate a highly significant linear trend with the youngest groups showing substantially worse mental health than the older groups (P<.001); differences between the 22- to 49-year-old age group and those in the older groups are more marked than what has been reported in non-VA patient populations.20
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Figure 1. Medical Outcomes Study Short Form 36-Item Health Survey scales by age group among outpatients served by the Department of Veterans Affairs in the Veterans Health Study. Values are means and 95% confidence intervals. For definitions of scale see the "Methods" section of the text. PF indicates measures of physical functioning; RP, role limitations due to physical problems; BP, bodily pain; GH, general health perceptions; VT, vitality; SF, social functioning; RE, role limitations due to emotional problems; and MH, mental health.
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Figure 2. Physical component summary (PCS) and mental component summary (MCS) scales by age group among outpatients served by the Department of Veterans Affairs in the Veterans Health Study. Values are means and 95% confidence intervals. For definitions of scale see the "Methods" section of the text.
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The overall level of the PCS score (36.9; 95% confidence interval, 36.3-37.5) is more than 140% of 1 SD worse than that of a general US population (score, 50), and more than 50% of 1 SD worse than that of a sample of ambulatory patients seen in non-VA systems of care (eg, health maintenance organizations and multispecialty groups) (score, 43.6).21 Likewise, the score of the youngest age group is more than 140% of 1 SD worse than that of a general sample of the US population, and also worse than that of a sample of patients seen in non-VA ambulatory care settings (score, 52.3).
Table 3 presents results from a series of multiple regression analysis models evaluating independent predictors of the 2 component health status summaries from the SF-36. In the first set of models (I), the sociodemographic variables (age, race, marital status, education, and income) together explain only 4% (R2) of the variability in the PCS and 10% of the variability in the MCS. Only education and income were significantly associated with the PCS, with higher physical function among those of higher socioeconomic status. Age and income were the sociodemographic variables significantly associated with the MCS, with substantially lower scores among the younger patients and higher income among those with better mental health.
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Table 3. Regression Coefficients of SF-36 Physical and Mental Component Scales With Sociodemographics, Morbidities, and Veteran Status*
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The addition of terms for disease burden (morbidities) in the second set of models (II) substantially increased the explained variability (R2) in component summaries (PCS, 32%; MCS, 21%). With the exception of hypertension and alcohol-related disorders, all the morbidity terms were significantly associated with worse PCS scores. Alcohol disorders, chronic low back pain, and "the count of other morbidities" (number of comorbid disorders) also were significantly associated with worse MCS scores.
In the third set of models (III), morbidities are replaced by VA disability status. Although this measure is negatively associated with the PCS and the MCS scores (more disability with worse health status), the additional explained variabilities are substantially lower compared with the models containing terms for morbidities; this difference reflects 21% of the explanatory power for the PCS and 8% for the MCS. The fourth model includes all terms with an explanatory power of 34% for PCS and 23% for MCS. The addition of VA disability status adds little explanatory power to the PCS (2%) and the MCS (2%).
COMMENT
In this study of 1667 veterans in 4 Boston area VA centers, we found that VA patients are a group with substantial disease burden with major negative impacts across multiple dimensions of HRQoL reflecting considerable patient needs. On average VA patients present with many medical comorbid conditions. More than one quarter of the VA patients screened positively for depression. The VA outpatients had poorer health status scores across all measures of the SF-36 compared with non-VA populations, including those in health maintenance organizations and multispecialty groups.
We found that younger veterans were sicker or as sick as older veterans in contrast to non-VA patients where the younger are often healthier. The younger VA users had physical limitations that were almost as severe as in the older veterans. Mental health status was substantially worse in younger veterans compared with the older age groups. These differences are likely a reflection of the mix of diseases, sociodemographics, and military experience (especially war cohort). The measures of health status are affected by these patient characteristics and represent a synthesis of the needs of veterans. They bear important implications for use of services and resources required in the provision of health care.
Particularly striking are the veterans' characteristics by age group. Selection factors play a major role in the composition of the veteran sample. Veterans use the VA because of their military service, and age is intermingled with the veterans' tour of duty. Veterans in the 22- to 49-year-old age group had substantially more depression and alcohol-related disorders. Functional limitations in mental health status as indicated by results of the SF-36 were also particularly severe in this group, perhaps an indication of the higher prevalence of mental illness.
The findings in this study are consistent with the literature that indicates that younger adults report poorer mental health status than older adults. Perhaps veterans who survive to old age, by virtue of their longevity, are more psychologically resilient to poor health than their younger counterparts.22-23 Alternatively, presentation and manifestation of psychiatric distress may differ by age group.24-25 The prevalence of screening diagnoses reported in this study are noteworthy. Rates of depression among the youngest group of veterans (aged 22-49 years) were more than 5 times those estimated among men in private sector primary care health systems; for veterans aged 50 to 64 years, rates were more than 3 times; and for those 65 years or older, rates were nearly double.26 Screening prevalence of current alcohol disorders among the youngest group of veterans is approximately 1.5 times the rate found among men in the private sector; and for veterans aged 50 to 64 years, rates are approximately comparable. However, rates of alcohol disorders among the oldest group of veterans were one third of those estimated among those in non-VA health care systems. Perhaps alcohol consumption is medically proscribed among this oldest group of veterans who carry a major burden from medical illnesses. Another possibility is that the effects of alcohol disorders have taken their toll such that there was attrition of more severe drinkers out of the cohort due to mortality, and the less severe drinkers and abstainers were more likely to survive to old age.
The limitations in physical functioning were severe in the old age group but interestingly were similar to the levels of dysfunction in the young age group. This suggests major limitations in health status in the younger veterans. The poor functional status in the younger veterans is an indicator in part of their diseases. The young veterans are different and sicker than one might expect in other young populations.
The findings of this study suggest that those in the youngest group require more mental health services than the other age groups. The majority of VHS patients in the youngest group report that they are from the Vietnam War era, while the middle and oldest age groups report that they are from the Korean War and World War II eras. Differences by age are likely related to the war cohorts represented by the age groups as well as factors associated with aging. While this cross-sectional study does not allow us to make causal inferences as they relate to periods of engagement and differences in the mental health functional outcome measures, it does suggest that those in the youngest group require more mental health services than the other groups.
Using physical and mental health status as the outcomes in regression analysis models, demographics explained relatively little of the variability in physical health, but explained almost half the variance in mental health. Education and income were important, but added relatively little power to the overall model when controlling for comorbidity and VA disability status. For mental status, age and income were important and contributed almost half the explanatory power to the model controlling for these other variables. Age was not associated with physical status and reflects the relatively poor levels of function across all age groups. Comorbid medical conditions were the major contributors to the physical and mental health status outcomes. This suggests that a good deal of the variability in the physical and mental status measures of outcome is explained by the mix of morbidities or the presence of disease. The results emphasize the usefulness of the HRQoL measures as an aggregate summary of the burden of disease or case-mix. The VHS was designed to be representative of users of VA ambulatory care. Given the demands of the study in terms of reading comprehension and concentration, the sample may have been underrepresented by patients with less education or limitations in literacy or cognitive functioning. Nevertheless, VHS patient characteristics are comparable with those of other surveys of VA users, including the National Survey of Veterans (IV),27 which suggests that our findings are generalizable to users of VA ambulatory care services on a national basis.
This study has several limitations. This is a cross-sectional sample, so that relationships between variables are descriptive and do not imply causality. The cross-sectional sample is also influenced by the selection of veterans from those who receive VA health care. We do not have internal data to describe or completely model the selection effects (ie, studying patients who chose the VA) that occurred in the VHS, nor are internally estimated selection models equal to the task. Adjustments for age or demographics may be biased. However, the regression analysis models generated coefficients that have been confirmed by previous work28 in non-VA patient populations. Another limitation is that patients have not been diagnosed as having depression but merely screened for depression. However, the screener used in this study has a sensitivity of 80%, a specificity of 95%, and a positive predictive value of 49% based on a medical outpatient clinic population.15
The use of patient-centered measures provides a means for understanding the health care needs of veterans. The results of this study strongly suggest that VA ambulatory patients are characteristically different from the populations served by other non-VA health care systems.29 The distribution of illness in the VA patient population differs markedly from that in the general population and from that of various other health care organizations. In many cases, patients appear to come to the VA for care because they are uninsured, something that is in itself a consequence of their burden of illness and corresponding disability. These findings suggest that because of the considerable needs of veterans, as reflected in their health status outcomes, the Veterans Health Administration will require considerable resources to provide care for its patients.
Health status assessments such as the SF-36 are well suited to measuring the needs of VA health care users. These measures serve as indicators of the outcomes of care and integrate sociodemographics, morbidities, and other patient characteristics into single measures of health. These assessments also provide a means for measuring the outcomes of care given specific defining events that may occur either during hospitalization or an ambulatory visit. The use of these measures by the Veterans Health Administration may provide a useful way of gauging the outcomes of the health status of patient populations within an integrated care system.
AUTHOR INFORMATION
Accepted for publication August 9, 1997.
This study was supported by grant SDR No. 91006.S from the Health Services Research and Development Service, Department of Veterans Affairs, Washington, DC.
We are indebted to Paul Gertman, MD, Sheldon Greenfield, MD, Mark Prashker, MD, and Gene Stollerman, MD, for helpful comments on earlier drafts of the manuscript.
Reprints: Lewis E. Kazis, ScD, Center for Health Quality, Outcomes and Economic Research, Health Services Research and Development Field Program (152), Edith Nourse Rogers Veterans Hospital, 200 Springs Rd, Bedford, MA 01730.
From the Center for Health Quality, Outcomes and Economic Research, Veterans Affairs Health Services Research and Development Field Program, Bedford, Mass (Drs Kazis, Miller, Clark, Skinner, Lee, Fincke, and Selim); Boston University School of Public Health and Medicine (Drs Kazis, Miller, Skinner, and Payne); New England Medical Center (Drs Rogers and Linzer); and Normative Aging Study, Veterans Affairs Outpatient Clinic (Dr Spiro), Boston, Mass.
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ABSTRACT
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Discordance Between Self-report of Physician Diagnosis and Administrative Database Diagnosis of Arthritis and Its Predictors
SINGH
The Journal of Rheumatology 2009;36:2000-2008.
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Spondyloarthritis Is Associated with Poor Function and Physical Health-Related Quality of Life
SINGH and STRAND
The Journal of Rheumatology 2009;36:1012-1020.
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Health-related quality of life in veterans with prevalent total knee arthroplasty and total hip arthroplasty
Singh and Sloan
Rheumatology (Oxford) 2008;47:1826-1831.
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Health-Related Quality of Life and Utilities Among Patients With Depression in the Department of Veterans Affairs
Zivin et al.
Psychiatr. Serv. 2008;59:1331-1334.
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Gout is associated with more comorbidities, poorer health-related quality of life and higher healthcare utilisation in US veterans
Singh and Strand
Ann Rheum Dis 2008;67:1310-1316.
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Equity in Veterans' Mental Health Care: Veterans Affairs Medical Center Clinics Versus Community-Based Outpatient Clinics
Kirchner et al.
American Journal of Medical Quality 2008;23:128-135.
ABSTRACT
Mental health of US Gulf War veterans 10 years after the war
Toomey et al.
Br. J. Psychiatry 2007;190:385-393.
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Predictors of Adherence Within an Intervention Research Study of the At-Risk Older Drinker: PRISM-E.
Zanjani et al.
J Geriatr Psychiatry Neurol 2006;19:231-238.
ABSTRACT
Colorectal cancer screening in young patients with poor health and severe comorbidity.
Sultan et al.
Arch Intern Med 2006;166:2209-2214.
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Mental Distress Among Younger Veterans Before, During, and After the Invasion of Iraq
West and Weeks
Psychiatr. Serv. 2006;57:244-248.
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Use of risk-adjusted change in health status to assess the performance of integrated service networks in the Veterans Health Administration
Selim et al.
Int J Qual Health Care 2006;18:43-50.
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Evaluation of a Care Coordination/Home-Telehealth Program for Veterans with Diabetes: Health Services Utilization and Health-Related Quality of Life
Chumbler et al.
Eval Health Prof 2005;28:464-478.
ABSTRACT
Efficacy of Frequent Mantram Repetition on Stress, Quality of Life, and Spiritual Well-Being in Veterans: A Pilot Study
Bormann et al.
J Holist Nurs 2005;23:395-414.
ABSTRACT
Benefits and Harms of Doxycycline Treatment for Gulf War Veterans' Illnesses: A Randomized, Double-Blind, Placebo-Controlled Trial
Donta et al.
ANN INTERN MED 2004;141:85-94.
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Colorectal Cancer Screening Knowledge, Attitudes, and Beliefs Among Veterans: Does Literacy Make a Difference?
Dolan et al.
JCO 2004;22:2617-2622.
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Who Has Diabetes? Best Estimates of Diabetes Prevalence in the Department of Veterans Affairs Based on Computerized Patient Data
Miller et al.
Diabetes Care 2004;27:B10-B21.
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Posttraumatic Stress Disorder in Female Veterans: Association With Self-reported Health Problems and Functional Impairment
Dobie et al.
Arch Intern Med 2004;164:394-400.
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Depression Management in Medical Clinics: Does Healthcare Sector Make a Difference?
Frayne et al.
American Journal of Medical Quality 2004;19:28-36.
ABSTRACT
Inhaled Corticosteroids in Chronic Obstructive Pulmonary Disease and Risk of Death and Hospitalization: Time-dependent Analysis
Fan et al.
Am. J. Respir. Crit. Care Med. 2003;168:1488-1494.
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Patients' Perceptions of Quality of Life After Treatment for Early Prostate Cancer
Clark et al.
JCO 2003;21:3777-3784.
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Effect of the Transformation of the Veterans Affairs Health Care System on the Quality of Care
Jha et al.
NEJM 2003;348:2218-2227.
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The Health and Functional Status of US Veterans Aged 65+: Implications for VA Health Programs Serving an Elderly, Diverse Veteran Population
Villa et al.
American Journal of Medical Quality 2003;18:108-116.
ABSTRACT
Cognitive Behavioral Therapy and Aerobic Exercise for Gulf War Veterans' Illnesses: A Randomized Controlled Trial
Donta et al.
JAMA 2003;289:1396-1404.
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Strategies to Decrease Costs of Prescribing Selective Serotonin Reuptake Inhibitors at a VA Medical Center
Dobscha et al.
Psychiatr. Serv. 2003;54:195-200.
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The relative health related quality of life of veterans with Parkinson's disease
Gage et al.
J. Neurol. Neurosurg. Psychiatry 2003;74:163-169.
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A Profile of Military Veterans in the Southwestern United States Who Use Complementary and Alternative Medicine: Implications for Integrated Care
Baldwin et al.
Arch Intern Med 2002;162:1697-1704.
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Are Veterans Seeking Veterans Affairs' Primary Care as Healthy as Those Seeking Department of Defense Primary Care? A Look at Gulf War Veterans' Symptoms and Functional Status
Richardson et al.
Psychosom. Med. 2002;64:676-683.
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Comprehensive Assessment of the Elderly Cancer Patient: The Feasibility of Self-Report Methodology
Ingram et al.
JCO 2002;20:770-775.
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US military veterans' perceptions of the conventional medical care system and their use of complementary and alternative medicine
Kroesen et al.
Fam Pract 2002;19:57-64.
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Cost-effectiveness of Gemfibrozil for Coronary Heart Disease Patients With Low Levels of High-Density Lipoprotein Cholesterol: The Department of Veterans Affairs High-Density Lipoprotein Cholesterol Intervention Trial
Nyman et al.
Arch Intern Med 2002;162:177-182.
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Health Status and Satisfaction With Health Care: A Longitudinal Study Among Patients Served by the Veterans Health Administration
Ren et al.
American Journal of Medical Quality 2001;16:166-173.
ABSTRACT
Posttraumatic Stress Disorder and the Use of Health Services
Deykin et al.
Psychosom. Med. 2001;63:835-841.
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Quality of Care in the Veterans Health Administration
Frankel et al.
NEJM 2001;344:1168-1170.
FULL TEXT
The Association of Bone Marrow Lesions with Pain in Knee Osteoarthritis
Felson et al.
ANN INTERN MED 2001;134:541-549.
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Heart murmurs: are older male dental patients aware of their existence?
RANDALL et al.
Journal of the American Dental Association 2001;132:171-176.
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Self-reported and Clinical Oral Health in Users of VA Health Care
Jones et al.
Journals of Gerontology Series A: Biological Sciences and Medical Sciences 2001;56:55M-62.
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Outcome of Myocardial Infarction in Veterans Health Administration Patients as Compared with Medicare Patients
Petersen et al.
NEJM 2000;343:1934-1941.
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Are Patients at Veterans Affairs Medical Centers Sicker?: A Comparative Analysis of Health Status and Medical Resource Use
Agha et al.
Arch Intern Med 2000;160:3252-3257.
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Clinical Factors That Influence Patients' Desire for Participation in Decisions About Illness
Mansell et al.
Arch Intern Med 2000;160:2991-2996.
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Mental Disorders and Mental Health Treatment Among U.S. Department of Veterans Affairs Outpatients: The Veterans Health Study
Hankin et al.
Am. J. Psychiatry 1999;156:1924-1930.
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The "New VA": A National Laboratory for Health Care Quality Management
Kizer
American Journal of Medical Quality 1999;14:3-20.
ABSTRACT
Health Status in VA Patients: Results from the Veterans Health Study
Kazis et al.
American Journal of Medical Quality 1999;14:28-38.
ABSTRACT
How Far Down the Managed Care Road?: A Comparison of Primary Care Outpatient Services in a Veterans Affairs Medical Center and a Capitated Multispecialty Group Practice
Peabody and Luck
Arch Intern Med 1998;158:2291-2299.
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