Where Do Women Veterans Get Their Inpatient Care?

Women’s Health Issues 17 (2007) 367–373

WHERE DO WOMEN VETERANS GET THEIR INPATIENT CARE? Susan E. Mooney, MD, MSa,b*, and William B. Weeks, MD, MBAa,c,d,e a

VA Quality Scholars Fellowship Program, White River Junction, Vermont b Dartmouth Medical School, Hanover, New Hampshire c National Center for Patient Safety d VA Outcomes Group REAP, VAMC, White River Junction, Vermont e Departments of Psychiatry and of Community and Family Medicine, Dartmouth Medical School, Hanover, New Hampshire Received 9 January 2007; accepted 30 August 2007

Purpose. In this study we explore women veterans’ use of Veterans Administration (VA) and private sector inpatient services. Methods. Using a comprehensive dataset of VA and private hospital admissions, we identified 1,409 female patients who were enrolled in the VA system and had an inpatient admission between 1998 and 2000 in either the VA or the private sector. For Major Diagnostic Categories (MDCs) with >20 admits in each sector, we compared care provided in the private sector with care provided in the VA with respect to patient characteristics and resource utilization. In addition, we determined payment sources for women who used the private sector for inpatient care. Findings. Women who used the VA were younger (mean, 54 vs. 60 years; p < .001) and more likely to be service connected (39% vs. 24%; p < .001), African American (25% vs. 13%; p < .001), and urban dwelling (81% vs. 75%; p < .01). Women veterans were significantly more reliant on the VA system for mental diseases, alcohol and drug use, and skin/subcutaneous/ breast diseases. For every MDC examined, VA hospitals had longer mean lengths of stay. Among VA eligible women <65 years old using the private sector, 56% used private insurance, 15% used Medicare, 14% used Medicaid, and 9% did not have insurance. Conclusions. In New York, female veterans admitted to VA hospitals differed from women admitted to private hospitals by patient characteristics, admission reason, and admission resource consumption. Many younger women who used the private sector were reliant on other government agencies (Medicaid or Medicare) or out-of-pocket payments for their inpatient care.

Introduction and Background

O

ver the course of the 1990s, Congress and the Veterans Administration (VA) established the care of women veterans as a health care and research priority (Klein, 2005). Despite this emphasis, the optimal method of delivering comprehensive health care to women veterans remains elusive. Although differ-

Supported by VA Health Services Research and Development Grants ACC 01-117-1, IIR 04 –236, and REA 03-098. * Correspondence to: Sue Mooney, MD, MS, Women’s Care Center at Alice Peck Day Memorial Hospital, 141 Mascoma Street, Lebanon, NH 03766. Phone: 603-448-3996; fax: 603-448-6863. E-mail: [email protected] Copyright © 2007 by the Jacobs Institute of Women’s Health. Published by Elsevier Inc.

ent organizational models within the VA system have been described, no one model has achieved dominance (Washington, Caffrey, Goldzweig, Simon, & Yano, 2003). Debate continues to surround the merits of gender-integrated versus gender-specific primary care (Yano, Washington, Goldzweig, Caffrey, & Turner, 2003). Recent studies have attempted to better characterize the preferences of the women veterans themselves. These efforts, which largely focus on primary care, reveal that access to a dedicated women’s health clinic, scope of services offered, affordability, convenience, and satisfaction with the quality of care all strongly influence a female veteran’s decision to use VA services (Bean-Mayberry, Chang, McNeil, Hayes, & Scholle, 2004; Washington, Yano, Simon, & Sun, 2006). 1049-3867/07 $-See front matter. doi:10.1016/j.whi.2007.08.006

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Although these prior studies are valuable, they are limited because of their exclusive focus on the outpatient setting. Additionally, it is well known that male veterans often receive care in the private sector as well as through the VA. This phenomenon is especially prevalent for male veterans ⬎65 years old who are both VA and Medicare eligible (Fleming, Fisher, Chang, Bubloz, & Malenka, 1992; Wright, Hossain, & Petersen, 2000). Because of the age of these veterans, much of the research has focused on differences between the VA and private sector with respect to inpatient admission for stroke and myocardial infarction (Jia et al., 2007; Wright, Daley, Fisher, & Thibault, 1997). More recent work, however, has evaluated differences between systems for outpatient primary care (Borowsky & Cowper, 1999). These studies are consistent in demonstrating that use of both the VA and the private sector is common among VA enrollees and that patients who seek care exclusively in one system or the other often have different outcomes and experiences than the “dual users” (Cowper, Jia, Qin, & Reker, 2007; Weeks et al., 2006). Despite the size of the established body of research, to date, very little work has been done to describe where VA-eligible women veterans receive their care and this is particularly true for women who are not eligible for Medicare. By 2010, it is estimated that women will comprise roughly 8% of all VA-eligible patients (Klein, 2005); therefore, an understanding of current utilization and payment patterns should be integral to policy development and strategic planning for the VA. To develop an optimal structure of women’s health care delivery throughout the VA, it is important to understand how women veterans use and pay for inpatient as well as outpatient services in both the VA and private sector. Therefore, using New York State as an example, for female veterans who were enrolled in the VA system, we sought to determine which system of care—VA or the private sector—they used to obtain inpatient care. Additionally, we examined whether different levels of resources were consumed in the VA or the private sector, whether there were differences in characteristics of female VA enrollees who used the private sector instead of the VA, and how these female VA enrollees paid for private sector care.

Methods Sample We performed a retrospective study of 2,283 New York State female veterans who lived in ZIP code– defined hospital referral regions that were entirely within the borders of New York State. We linked VA and New York Department of Health discharge datasets and used Diagnosis Related Group (DRG) and Major Diagnostic Category (MDC) codes to identify all

women who were admitted to any hospital, including nonprofit treatment facilities, community mental health centers, and private psychiatric centers, between 1998 and 2000. (A DRG is defined by the VA Health Economic Resource Center as “an inpatient classification system based on several factors: principal diagnosis; secondary diagnosis; surgical factors; age; sex and discharge status.” Similarly, an MDC is defined as “a classification system that represents a group of similar DRGs. Each MDC typically involves a single organ system” [U.S. Department of Veterans Affairs, 2006].) These women had a total of 4,245 admissions during the study period. To perform our analysis, we excluded 236 women who had admissions to both a VA and private hospital during the study period because they represented a unique population that was not directly comparable to the majority of patients. For example, these women averaged 4.5 admissions during the study period, whereas the final study population averaged 1.5 admissions during the same period. Additionally, because the VA does not typically provide obstetric care, we excluded 182 women who were admitted to a private hospital for an obstetric indication. Finally, we excluded 7 women who had admission LOS ⬎60 days. After applying these criteria, 1,622 women representing 2,913 admissions remained. There were 718 women with 1,268 admissions to VA hospitals and 904 women with 1,645 admissions to private sector hospitals. The women were stratified according to system of care (VA vs. private) and each woman’s first admission was identified. Using the DRG for the admission, we identified the MDC for each admission. To preserve patient confidentiality and to ensure an adequate sample size for comparison purposes, we limited our analysis to MDCs with ⬎20 admissions in both sectors of care. The final study population included 636 women who were admitted to a VA hospital and 773 women who were admitted to a private sector hospital (Figure 1). Analysis We conducted several analyses. To determine whether characteristics of women who used the private sector were different from those who used the VA, we compared demographic data using the ␹2 test for categorical variables and the Student t-test for continuous variables. To determine whether women were more reliant on the VA or the private sector for inpatient treatment for particular conditions, we calculated odds ratios (ORs) and 95% confidence intervals (CI) for admission to VA versus private sector hospital for each MDC examined. Using standard logistic regression models, ORs were adjusted for age, race, rural/urban categorization, service connection, and Charlson score (Charlson, Pompei, Ales, &

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Figure 1. Methods.

McKenzie, 1987). An OR compares whether the probability of a certain event is the same for 2 groups. When the CI for an OR crosses 1, statistically speaking, the event is equally likely to occur in both groups; however, when the CI for an OR does not cross 1, an event is more likely to have occurred in one of the groups (Children’s Mercy Hospital & Clinics, 2006). To determine whether resource consumption for services provided within the VA was different from that for services provided in the private sector, within each MDC, we assigned each admission a DRG weight and an expected length of stay (LOS). These data were obtained from standard Medicare “look-up” tables that are available in a well-known, comprehensive DRG guidebook (Drug Expert 2004, 2003). We then calculated a simple ratio of observed to expected (O/E) LOS for each admission and then determined the mean DRG weight, mean LOS, and mean O/E LOS for each MDC by sector of care (VA vs. private). We compared MDC specific means for VA with those

for private sector care using the Student t-test. Finally, we performed a descriptive analysis of the primary source of payment for private sector admission, stratified by age. Statistical analyses were completed using Stata, version 9.0 (StataCorp LP, College Station, TX); p ⬍ .05 was considered significant.

Results Characteristics of the final study population are shown in Table 1. Women who used the VA were younger (mean, 54 vs. 60 years; p ⬍ .001), demonstrated a trend toward being more likely to have a Charlson score of 0 (p ⫽ .06), and had a lower mean Charlson score (0.47 vs. 0.59; p ⫽ .04). In addition, women who used the VA were more likely to have a service-connected disability (39% vs. 24%; p ⬍ .001), were of a different ethnic/racial mix (with a greater

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Table 1. Characteristics of the Study Population

No. of unique women Average age at admission (range) Distribution of Charlson* scores at admission† 0 1 ⱖ2 Average Charlson score Service connected disability Race† Black Hispanic White Other Unknown Rural/urban† Most urban Suburban Sub-suburban Rural Missing data No. women age ⱖ65 (%) Medicare (part A) eligible

VA

Private Sector

p

636 53 (20–95)

773 60 (19–94)

⬍.001 .06

71% 20% 9% 0.47 39%

65% 22% 12% 0.59 24%

26% 6% 62% 2% 4%

14% 3% 59% 10% 14%

⬍.001

81% 6% 6% 7% ⬍1% 205 (32%) 87%

75% 5% 8% 12% ⬍1% 393 (51%) 96%

⬍.01

.04 ⬍.001

⬍.001 ⬍.001

Abbreviation: VA, Veterans Affairs. *The Charlson Comorbidity Index was developed in 1987 and is defined as “. . . a weighted index that takes into account the number and seriousness of comorbid disease. . . . [it] provides a simple, readily applicable and valid method of estimating risk of death . . .” (Charlson et al., 1987). † p-Values for these categories indicate that the distribution of the variable of interest is significantly different in the 2 populations.

preponderance of African Americans; p ⬍ .001), and differently distributed along the rural– urban continuum (with a greater preponderance of urban-dwelling women; p ⬍ .01). Women admitted to the VA were much less likely to be ⱖ65 (34% vs. 51%; p ⬍ .001); of those older women, those admitted to the VA were less likely to be enrolled in Medicare (87% vs. 96%; p ⬍ .001). Female VA enrollees appeared to use the VA and the private sector for different types of inpatient services (Figure 2). Patients were less likely to be admitted to a VA hospital for issues related to the female reproductive system (adjusted OR, 0.58; 95% CI, 0.39 – 0.87), the nervous system (adjusted OR, 0.64; 95% CI, 0.41– 0.99), the musculoskeletal system (adjusted OR, 0.72; 95% CI, 0.52–1.02), or the digestive system (adjusted OR, 0.77; 95% CI, 0.52–1.14). Results for the latter 2 MDCs did not achieve statistical significance. In contrast, patients were more likely to be admitted to a VA hospital for alcohol/drug use (adjusted OR, 2.79; 95% CI, 1.57– 4.95), mental diseases (adjusted OR, 2.1; 95% CI, 1.46 –2.89), or care related to the skin/subcutaneous tissue and breasts (adjusted OR, 1.7; 95% CI, 0.99 –2.92). Resource consumption was evaluated by calculating mean LOS as well as the O/E LOS for each MDC

(Table 2). Although the mean LOS was longer for every MDC examined, the difference reached statistical significance only for musculoskeletal admissions (9.4 vs. 5.2 days; p ⬍ .001) and when examining all admissions (8.7 vs. 6.0 days; p ⬍ .001). The mean DRG weight was lower, suggesting less complex admissions, for VA admissions for each MDC except in the respiratory, hepatic/pancreatic, and skin/subcutaneous, and breast diagnostic categories. Differences reached statistical significance for mental disorders (0.74 vs. 0.77; p ⬍ .01), musculoskeletal disorders (1.34 vs. 1.55; p ⫽ .03). and when comparing all admissions (0.99 vs. 1.25; p ⬍ .001). Mean observed to expected LOS were longer in the VA system for every MDC examined, but only reached statistical significance for mental disorders (1.89 vs. 1.47; p ⫽ .04), musculoskeletal disorders (2.0 vs. 1.1; p ⬍ .001), nervous system disorders (1.81 vs. 1.12; p ⫽ .04), and when comparing all admission (1.54 vs. 1.11; p ⬍ .001). Primary payment sources for private sector hospitalizations are illustrated in Figure 3. For women ⱖ65 years, Medicare was the primary payment source for 82% of admissions. An additional 16% of these admissions were paid for by private insurance. Among women ⬍65 years, private insurance was the primary payment source for 56% of admissions; Medicare, for 15%; and Medicaid, for 14%. Another source of payment, such as worker’s compensation, was the primary payer for 6% of admissions, and out-of-pocket payments were the primary source of payment for 9% of admissions.

Discussion We found that, in New York State, women who were enrolled in the VA system and who used the VA for inpatient services were younger and more likely to have a service connected disability, be African American, and live in urban settings than their counterparts who used the private sector. Female VA enrollees were more reliant on the VA for inpatient treatment of mental diseases, drug and alcohol use, or issues related to the skin, subcutaneous tissue, and breast, and less reliant on the VA for inpatient treatment of the female reproductive system and the nervous system. Additionally, there was a trend toward less reliance on VA for issues related to the musculoskeletal system and the digestive system. Once admitted, women who used VA hospitals experienced longer than expected mean LOS, despite comparable, or even lower, levels of acuity as measured by DRG weight. Finally, women who used private sector hospitals relied on private insurance and other government agencies to fund their care. Our findings are important for several reasons. We are the first investigators to use a comprehensive, population-based dataset to determine the amount

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Figure 2. Odds of admission to VA versus private sector hospital by MDC.

examined, we were not surprised to find a lack of reliance on the VA for services that are unique to women (i.e., gynecologic surgery and breast disorders). This finding is consistent with prior research that revealed that Veterans have variable access to gynecologic specialists, especially for emergent issues (Washington, Yano, Goldzweig, & Simon, 2006). Our analysis of resource consumption during admission reveals substantial aggregate differences between VA and private hospitals and raises interesting questions about potential for improved efficiency. Across all of the MDCs examined, the VA consumed more resources, as measured by the O/E LOS, during inpatient admissions. In the absence of outcome and readmission data, it is inappropriate to draw firm conclusions about this obser-

and type of inpatient care obtained by VA-eligible women veterans using the private sector. We were not surprised to find that women who use VA facilities are more likely to be admitted for treatment of mental diseases or drug and alcohol abuse for 2 reasons. First, others have demonstrated that the prevalence of these disorders is high among women veterans (Frayne et al., 2006). Second, the increased reliance on the VA for treatment of these disorders is likely due to a combination of the expertise that VA has in these areas and the relatively poor inpatient mental health and substance abuse benefit packages that prevail in the private sector. Because it is likely that New York State VA hospitals had differing availability of women’s health clinics and services during the time period

Table 2. Mean LOS, DRG Weight, and Observed/Expected LOS Per Unique Individual in VA and Private Hospitals No. of Admissions

Mean LOS (SD)

Mean DRG Weight (SD)

Mean Observed/Expected LOS (SD)

MDC Name

VA

Private

VA

Private

p

VA

Private

p

VA

Private

p

Mental diseases Circulatory Musculoskeletal Respiratory Alcohol/drug use Female reproductive Digestive system Skin/SQ/breast Nervous system Hepatic/pancreatic Total

146 92 70 61 58 52 50 39 39 29 636

80 157 122 85 21 89 92 27 67 33 773

14.03 (12.20) 5.27 (6.57) 9.41 (8.06) 8.44 (7.98) 9.79 (8.77) 3.25 (2.17) 6.64 (7.13) 4.77 (4.73) 8.33 (9.21) 7.52 (7.64) 8.72 (9.55)

12.11 (10.51) 5.08 (5.88) 5.23 (5.02) 6.36 (5.20) 8.86 (7.19) 3.07 (1.56) 5.28 (4.35) 3.78 (3.78) 6.37 (6.50) 5.67 (5.29) 6.00 (6.48)

NS NS ⬍.001 .06 NS NS NS NS NS NS ⬍.001

0.74 (0.10) 1.05 (1.71) 1.34 (0.67) 1.36 (0.97) 0.53 (0.17) 0.92 (0.25) 1.15 (0.99) 0.78 (0.31) 0.96 (0.49) 1.57 (0.93) 0.99 (0.88)

0.77 (0.07) 1.39 (1.47) 1.55 (0.69) 1.30 (1.77) 0.56 (0.18) 1.00 (0.29) 1.24 (0.95) 0.75 (0.14) 1.45 (1.96) 1.55 (0.84) 1.25 (1.19)

⬍.01 .10 .03 NS NS .09 NS NS NS NS ⬍.001

1.89 (0.11) 1.22 (1.26) 2.00 (1.75) 1.27 (0.85) 1.74 (1.39) 0.94 (0.51) 1.31 (1.31) 1.32 (1.34) 1.81 (2.36) 1.42 (1.39) 1.54 (1.45)

1.47 (0.12) 1.12 (1.07) 1.10 (0.89) 1.05 (0.68) 1.37 (0.69) 0.91 (0.40) 1.06 (0.73) 0.95 (0.75) 1.12 (1.01) 1.04 (0.78) 1.11 (0.90)

.04 NS ⬍.001 .09 NS NS NS NS .04 NS ⬍.001

Abbreviations: DRG, Diagnosis Related Group; LOS, length of stay; SD, standard deviation; SQ, subcutaneous tissue; VA, Veterans Affairs. p-Value reported as NS if ⬍ .1.

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Figure 3. Payment sources for private hospital patients by age.

vation; it is possible that we are measuring underuse in the private sector as opposed to overuse in the VA. However, this finding suggests that additional work needs to be performed to define optimal levels of efficiency for inpatient resource utilization in the care of women veterans. Achieved efficiencies may provide a source of financing for expansion of women’s inpatient health care services within VA. Finally, our work sheds light on the important issue of payment. Little is known about how women veterans who are enrolled in the VA and who are ⬍65 years pay for services that they obtain in the private sector. Previous work examining outpatient care has demonstrated that women who have private insurance are likely to obtain care in the private sector (Washington, Caffrey, et al., 2003). Our study confirms those findings, albeit for inpatient services. More interestingly, however, we found that other federal agencies were the primary payers for almost one third of VA enrollees’ admissions. Therefore, redirecting younger female VA enrollees’ private sector care to VA hospitals could decrease women veterans’ reliance on other governmental agencies. Additionally, attracting more women to VA hospitals may allow facilities to reach a “critical mass” of women that may allow them to expand female-specific services. There are several limitations to our study. It is possible that the New York State women veterans are not representative of the approximately 1.7 million women veterans nationwide (Klein, 2005). Further, because the composition of the active duty military is changing, it is possible that the women examined during the study period are in some ways different from the women who will be joining the ranks of veterans in the upcoming decades. Because of this, our

findings may not accurately predict the demographics and demands of future women veterans in different regions of the country. Additionally, our study is limited because we used administrative data that were collected from health care systems with different incentives. This is especially relevant to DRG weighting, where more attention to “upcoding” and efforts to maximize payment may prevail in the private sector. Finally, as stated, it is difficult to draw firm conclusions about efficiency in the absence of additional data regarding outcomes. Our analysis was restricted to efficiency as measured at the level of independent admissions; an analysis of efficiency as applied to populations over time was beyond the scope of this effort. Despite these limitations, we believe that our findings are valuable on 2 levels. First, our work provides a foundation on which to build additional information about how women veterans use VA and private sector facilities. Further work examining regional variation and variation over time will be important to policy makers. Second, our findings should inform VA policy makers in their debate about how to develop comprehensive women’s health care programs within the VA. Our study suggests that VA managers should consider examining private sector use to identify gaps in perceived service availability, increasing access to selected new services to attract veterans from the private sector, and funding new product lines for women by coordinating care with these other federal agencies and by improving the efficiency of current services.

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Author Descriptions Susan E. Mooney, MD, MS, recently completed the VA National Quality Scholars Fellowship at the White River Junction VA Hospital. As an Obstetrician/Gynecologist, her interests focused on improving the quality of healthcare for female veterans. After completing the fellowship, Dr. Mooney returned to the private sector where she now practices Gynecology and serves as the Medical Director for Quality Improvement at a hospital in Lebanon, NH. William B. Weeks, MD, MBA, is affiliated with the Veterans Affairs Outcomes Group REAP, Veterans Affairs Hospital, White River Junction, Vermont and the Center for Evaluative Clinical Sciences, Dartmouth Medical School. He is also the Director of the White River Junction, Vermont field office of VHA’s National Center for Patient Safety. His research interests include health economics, patient safety, rural veterans’ health care.