MILIT.4RY MEDICINE, 178, 11:1250, 2013
Associations Between Childbirth and Women Veterans' VA and Non-VA Hospitalizations for Major Diagnostic Categories Alan N. West, PhD*; Pamela 1/1/. Lee, PhDf
ABSTRACT Women Veterans enrolled in Veterans Affairs (VA) health care almost always use non-VA hospitals for childbirth, making it more likely they will use non-VA hospitals for other needs, as well. We compared VA and non-VA hospitalizations obtained by VA enrollees in seven states from 2004 through 2007 to determine whether women aged 18 to 44 were more likely to use VA or non-VA care for diagnoses in certain major categories, and how this use differed between women who did or did not have any pregnancy/childbirth admissions during the 4 years. We found that women were hospitalized much more in non-VA than in VA hospitals, though they were relatively more likely to use VA hospitals for mental illness, digestive system diseases, and neoplasms than other diagnoses. Women who gave birth during the time interval had very few VA admissions for any diagnosis, and compared to other women they were also less likely to be hospitalized for mental health or cancer, but more likely to be hospitalized for infectious and parasitic diseases. VA hospitals were used more by women who were slightly older, sicker, poorer, and living nearer to them. VA-using women tend to have different and greater medical needs than those having children.
INTRODUCTION The number of women Veterans using Veterans Affairs (VA) health care has doubled since this century began; most of the new patients are young women in their reproductive years, a higher proportion have service-connected disabilities than ever bsfore, and many use VA primary care or mental health services more heavily than men. ' Yet like their male counterparts, women Veterans use non-VA health care more on average than they use VA care.^ Their choice between VA and non-VA health care depends on several factors, such as affordability and convenience (e.g., their income, eligibility for VA care, private insurance coverage, travel burden to reach care, lost work-time, and family burdens) as well as the availability of needed services.^ A national survey of women who were current or former users of VA health care** found that these Veterans, particularly women with service-connected disabüities, regarded ease of use as their greatest barrier to accessing VA care; for women without service connection, the availability of services was a stronger predictor of VA use. Another survey of women Veterans to understand their reasons for using either VA or non-VA health care^ found that VA users most often endorsed affordability, the availability of a women's health clinic, quality of care, and convenience as their reasons for using the VA. For those who used non-VA care, the most cited reasons for not using the VA were having private health insurance, the greater convenience of non-VA care, a perception that the quality of non-VA care is better, and lack of knowledge about their VA eligibility and benefits. A review of the health research on women Veterans^ concluded that female Veterans »Research Service, VAMC (10A5A), 215 N. Main Street, White River Junction, VT 05009. fVe-.erans Rural Health Resource Center—Eastern Region, VAMC (10A5A), 215 N. Main Street, White River Junction, VT 05009. doi: 10.7205/MILMED-D-13-00200
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use VA care less than male Veterans, and that they often seek health care for reasons that are gender specific. The authors also observed that most VA Medical Centers (VAMCs) provide basic health services for women and that having genderspecific care available has increased women's use of the VA. Yet women Veterans often do not know that the VA provides women's health care or that they are eligible to receive it. The medical or psychiatric needs of women Veterans are likely to differ for those having families, as they will tend to be younger and healthier than other female enrollees of childbearing age. Because VAMCs do not offer planned inpatient obstetric services, women Veterans who have babies must use non-VA hospitals. Because satisfactory experiences will enhance patient loyalty,^ they then may be more likely than other female enrollees to use non-VA hospitals for other conditions, as well. Of course, women hospitalized for reasons other than childbirth may use either VA or non-VA care, with the choice determined at least in part by their medical needs and their access to the appropriate services and expertise. VAMCs, for example, often provide psychiatric care or longer admissions for chronic medical conditions that nonVA hospitals do not. Furthermore, patients who are hospitalized more often are likely to have a wider array of medical problems and so may be more likely to use both VA and nonVA care. For any woman, the choice between going to a VAMC vs. a non-VA hospital will be influenced by the travel burden associated with each, as well as her priority status for receiving VA care (the VA gives greater priority to Veterans who have disabilities related to military service, are catastrophically disabled, or are impoverished). But even accounting for distance, disabüity/financial status, comorbidities, or frequency of hospitalization, young women Veterans may well use VA and non-VA hospitals differently depending on whether some of their use is for pregnancy/childbirth. To test such hypotheses, we analyzed hospital discharge data that include any admissions to either VA or non-VA
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Women's VA and Non-VA Hospitalizations
hospitals that VA enroUees living in any of seven states had during four recent years, 2004-2007. METHODS The pool of potential subjects for this study consisted of all Veterans listed in the VA health care system's 2007 national enrollment file as living in any of seven states (Arizona, Iowa, Louisiana, Florida, South Carolina, Pennsylvania, or New York). These seven states were the only ones we identified that (i) had data that included social security number (and birth date) to enable matching of enrollees to their nonVA hospitalization records, (ii) were willing (or allowed by law) to provide the data, and (iii) were willing to return a unique random identifier to permit matching patients across both VA and non-VA data. We analyzed administrative hospital discharge data for any inpatient admissions to VAMCs or in-state private sector hospitals (non-VAs) that these Veterans had at any time between 2004 and 2007. Because our data include any non-VA hospitalizations that these enrollees had in their home states and any VAMC admissions they had anywhere, their non-VA utilization might be under-represented but their VA usage is complete. VA's National Data Systems (NDS) provided us discharge data for any VAMC hospitalizations these enrollees had during the study interval. For each state, NDS also provided all enrollees' personal identifiers (social security number, date of birth, and gender) to the managers of non-VA hospitalization data (state government agencies or hospital associations), who used them to search for matching records in their databases, applying deterministic matching, i.e., exact matches only. After sending the matching treatment data to NDS, these agencies then deleted all records of enrollees' personal identifiers. The data files provided to us by NDS were stripped of all personal identifiers but included a randomly assigned unique identification number that enabled us to determine whether individuals had both VAMC and non-VA hospitalizations. These data files also included each patient's priority for VA care (described below) at the time of each hospitalization. This study was approved by Dartmouth College's Committee for the Protection of Human Subjects. Among Veterans of ages 18 to 44 in our hospital discharge data, 12,031 (27%) were women, who had 20,011 (23% of all) hospitalizations; roughly 16% of Veterans who had VAMC hospitalizations; and 32% of those who had non-VA admissions were women. We limited our analyses to women 18 to 44 years old, and compared those who had any hospitalization related to pregnancy or childbirth during the four years to those who did not. Among other variables, the administrative hospital discharge datasets included, for each hospitalization, the principal diagnosis (reason for the admission) as well as secondary diagnoses, the diagnosis-related group, length of stay (in days), and the ZIP code of the patient's residence. Diagnoses and diagnosis-related groups were submitted to pubUcly available comorbidity software developed by the Agency for Healthcare Research and Qual-
MILITARY MEDICINE, Vol. 178, November 2013
ity (AHRQ) (http://www.hcup-us.ahrq.gov/toolssoftware/ comorbidity/comorbidity.jsp) to search administrative discharge data for any of 30 physical or psychiatric comorbid diagnoses identified as important predictors of treatment outcomes.' For each hospitalization, we summed the comorbidities detected to yield a single estimate of comorbid illness severity. To simplify utilization comparisons, we also assigned principal diagnoses to the highest-level major diagnostic categories produced by AHRQ's Clinical Classifications Software for ICD-9-CM codes (http://www.hcup-us .ahrq.gov/toolssoftware/ccs/ccsfactsheet.jsp); we report findings for the most frequent categories. We assigned each patient's residence to a Rural-Urban Commuting Area (RUCA) category'°'" by applying a publicly available ZIP code approximation to implement Categorization A (http://depts.washington.edu/uwruca/ruca-uses.php), which defines four categories: Urban, Large Rural Town, Small Rural Town, and Isolated Rural Town. We also applied a publicly available SAS routine'^ to access Google Maps for estimated driving times from the centroid of each patient's ZIP code to the centroids of the ZIP codes of all VAMCs in the patient's region (within a 300-mi. radius, regardless of state), and selected the shortest travel time as a measure of proximity to VA care. We repeated this process to select the nearest non-VA hospital, as well, using a comprehensive list drawn from Medicare's Hospital Compare site (http:// hospitalcompare.hhs.gov/). Finally, we assigned each patient to one of four categories reflecting priority for VA care: (i) patients in VA priority group 1, who have the highest levels of military service-connected disability and resulting unemployability; (ii) those in priority groups 2, 3, or 4, who generally have lower rated service-connected disability or non-service-connected catastrophic disabilities; (iii) those in priority group 5, who generally qualify for VA care because of low income; and (iv) those in priority groups 6, 7, and 8, who qualify for other reasons, including recent military service, or agree to make co-payments for care. We compared women who had any hospitalization for pregnancy or childbirth during the four study years to those who did not, using x^ analyses to compare their likelihood of being hospitalized, and their reliance on VAMCs vs. non-VA hospitals, for different principal diagnoses. We replicated these analyses using logistic regressions to control for age at admission, number of comorbid diagnoses, travel times to the nearest VAMC and the nearest non-VA hospital, priority for VA care, and urban-rural residence. However, because priority for VA care was missing for about 13% of admissions and because odds ratios (ORs) and decisions about the statistical significance of comparisons (whether or not priority for VA care was included) did not differ appreciably from those yielded by the simple x^ analyses, we report only the x'^ results here. We further separated the patients by whether they used VAMCs, non-VA hospitals, or both, during the study interval, and compared them on several characteristics, including age, comorbid diagnoses, hospital length of stay.
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Women's VA and Non-VA Hospitalizations
travel times, priority for VA care, and urban-rural residence, All analyses were conducted using SAS version 9.2 (SAS Institute, Cary, North Carolina). RESULTS Table I shows selected characteristics of the women, separated by whether or not they had any hospitalization during the four years for complications of pregnancy, childbirth, or the puerperium, and whether they were admitted to VA hospitáis, non-VA hospitals, or both during that time. For users of both VAMCs and non-VA hospitals (dual users), some utilization data are separated by hospital type. The table shows numbers of unique patients and numbers of admissions for each cell. Of the 12,031 unique patients, 9,186 (76.4%) used non-VA hospitals, exclusively, 1,911 (15.9%) used VA hospitals only, and 934 (7.7%) used both. Very few women used VA hospitals for obstetric care; in fact, if not emergencies—which VA data do not identify—these admissions might be attributable to coding errors. Women who had any admission for pregnancy/childbirth obtained 6,706 (96.6%) of their 6,941 hospitalizations (for all diagnoses) in non-VA TABLE I.
hospitals; other women obtained 8,276 (63.3%) of their 13,070 hospitalizations in non-VA hospitals, %^ = 2669.0, p < 0.0001. The difference in reliance on non-VA hospitals remains when obstetric admissions are excluded: Though there were 5,762 admissions for pregnancy/childbirth, the young mothers also had 1,179 hospitalizations (17.0% of all their admissions) for other principal diagnoses (221 in VA hospitais and 958 in non-VA hospitals). Compared to other women, they were much less likely to use VA hospitals for other conditions, as wd\,z^ = 152.50,/? < 0.0001, OR = 0.40, 95% CI = 0.34-0.46 (utilization for specific diagnostic categories is addressed below). In short, young women Veterans enrolled in VA health care relied more on non-VA hospitals than VAMCs, and much more so if they gave birth during the study interval. In addition. Table I shows that women who had pregnancy/ childbirth hospitalizations were younger than other women (mean ages: 29.5 vs. 36.6, t = 84.67, p < 0.0001), had fewer comorbid diagnoses (mean diagnoses: 0.3 vs. 1.3, í = 65.61, p < 0.0001), and lived slightly further from the nearest VAMC
Female Veterans 18 to 44 Years Old Living in Seven States and Enrolled in VA Health Care Who Were Admitted to Either VA or Non-VA Hospitals at Any Time in Four Years, 2004-2007 Hospitalized for Pregnancy/Childbirth Any Time in Four Years, 2004-2007? Yes
No Dual Users VA-Only Users Number of Unique Patients % of Total Number Number of Hospitalizations % of All Admissions Mean Admissions per Patient
1906 15.8 3003 15.0 1.6
VA
Non-VA 784 6.5
1791 9.0
1539 7.7 4.2
2.3 Mean Age at Admission (Years) (SD) Mean Comorbid Diagnoses (SD) Mean Length of Stay (Days) (SD) Percentages in Column VA Priority 1 2-4 5 6-8 RUCA Urban Large Rural Town Small Rural Town Isolated Rural Town Mean Driving Minutes to Nearest VA Hospital (SD) Nearest Non-VA Hospital (SD)
36.9 (6.2) 1.4 (1.3) 5.4 (11.2)
Non-VA-Only Users 4404 36.6 6737 33.7 1.5
Dual Users •*/A-Only User , 5 0.0 6 0.0 1.2
7.2 (10.6)
5.3 (5.8)
Non-VA 150 1.2
229 1.1
283 1.4 3.4
1.5
2.0 37.2 (6.2) 1.7 (1.4)
VA
36.1 (6.4) 1.0 (1.1) 4.1 (5.9)
31.3 (5.0) 0.3 (0.8) 3.3 (2.2)
Non-VA-Only Users 4782 39.7 6423 32.1 1.3
1.9 30.6 (6.0) 1.0 (1.1)
4.7 (5.6)
3.7 (5.6)
29.4 (5.2) 0.3 (0.7) 2.9 (4.2)
50.0 24.8 16.5 8.7
48.7 22.8 22.3 6.3
28.8 34.9 17.2 19.1
25.0 50.0 25.0 0.0
47.4 27.0 18.2 7.4
13.8 47.5 12.4 26.3
84.6 8.1 5.2 2.1
85.2 9.6 2.9 2.3
83.4 10.3 3.9 2.5
100.0 0.0 0.0 0.0
82.4 11.0 1.8 4.9
82.8 11.0 3.5 2.7
41.7 (36.5) 12.3 (12.6)
50.2 (43.5) 12.5 (13.1)
63.4 (47.4) 13.1 (12.0)
29.3 (24.1) 12.8 (7.5)
46.4 (36.1) 12.7 (11.9)
58.9 (45.3) 13.3 (12.2)
Separated by whether they used VA hospitals, non-VA hospitals, or both (dual users), and whether any hospitalization was for "complications of pregnancy, childbirth, or the puerperium."
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Women's VA andNon-VA Hospitalizations
(mean driving minutes: 58.0 vs. 55.1, t = 4.33, p < 0.0001) and study interval; and the odds that women with a particular from the nearest non-VA hospital (mean driving minutes: 13.3 diagnosis, compared to other women, went to a VAMC for it vs. 12.8, t = 2.74, p < 0.01). They also were much less likely to or also had a baby during the study interval. More than onebe in VA priority categories 1 (greatest service-connected fourth of all non-birth admissions were for mental illness, disabilities) or 5 (impoverished), %^ = 1249.9, p < 0.0001. and more than another one-fourth were for diseases of the The table also shows that whether or not they had obstetric genitourinary, digestive, or circulatory systems. For every hospitalizations, patients who used VA hospitals lived closer 100 women who did not have a birth admission, there were to them than those who used non-VA hospitals (mean driving more than 50 hospitalizations for mental illness, with more minutes: 42.9 vs. 60.5, t - 26.66, p < 0.0001), were shghtly in VAMCs than in non-VA hospitals. For every 100 women older (mean ages: 36.9 vs. 33.2, t = 35.31, p < 0.0001), had who did have a birth admission, on the other hand, there more comorbid diagnoses (mean diagnoses: 1.5 vs. 0.8, t = were only about 5 hospitahzations for mental illness. Patients 35.75, p < 0.0001), and were more likely to be in priority with other diagnoses consistently used non-VA hospitals categories 1 and 5,%'^ = 1213.5, p< O.OOOI. Group differences more than VAMCs. ORs indicate that relative to other diagin urban-rural, residence were inconsistent and relatively noses, admissions for mental illness, diseases of the digestive small, with (p coefficients of 0.03-0.04. These results suggest system, and neoplasms were more likely to be in VAMCs, that VA hospitals were relied on more by those young women whereas for treatment of genitourinary, circulatory, respirawho were slightly older, sicker, poorer, and living nearer to tory, blood, endocrine, nutritional, metabolic, or immunity them, and who were not in a phase of life in which they were disorders, non-VA hospitals were preferred. Women with bearing children. birth admissions during the study interval were also less likely Table II shows the number of admissions for principal to have an admission for mental health or cancer, but more diagnoses other than complications of pregnancy, childbirth, likely to be hospitalized for infectious and parasitic diseases. or the puerperium; the percentage of these non-birth admisHowever, among dual users (women who had at least one sions that each diagnostic category represents; the average hospitalization in both VA and non-VA hospitals), results number of admissions per diagnostic category for every 100 were unique: Those who had a pregnancy/childbirth hospitalwomen who either did or did not have a baby during the ization were actually more likely than other dual users to be
TABLE II.
VA and Non-VA Admissions for the Most Common Principal Diagnoses (Except Pregnancy/Birth) for Women Who Either Did or Did Not Have a Baby During the Four Years, 2004-2007 Admissions Per 100 Patients
Category of Principal Diagnosis Mental Illness Diseases of the Genitourinary System Diseases of the Digestive System Diseases of the Circulatory System Endocrine, Nutritional, and Metabolic Diseases, and Immunity Disorders Diseases of the Nervous System and Sense Organs Diseases of the Respiratory System Injury and Poisoning Diseases of the Musculoskeletal System Neoplasms Diseases of the Blood and Blood-Forming Organs Infectious and Parasitic Diseases
Non-VA
OR" Odds of Going to a VA Hospital"
OR" Odds That Patient Gave Birth in the Study Interval'^
3.0 2.4
2.82-3.29**** 0.52-0.66****
0.63-0.85**** 0.89-1.29
0.5 0.2
1.9 1.7
1.13-1.43**** 0.55-0.73****
0.98-1.47 0.76-1.19
11.3
O.I
1.9
0.20-0.29****
0.96-1.48
4.0
6.2
0.3
1.5
0.93-1.25
1.07-1.70*
5.1
2.3
6.8
0.2
1.3
0.48-0.68****
1.02-1.67*
716 657
5.0 4.6
3.2 3.2
6.2 5.5
0.2 0.1
0.7 0.8
0.77-1.06 0.85-1.18
0.54-1.00* 0.58-1.08
647 486
4.5 3.4
3.6 0.6
5.3 5.5
0.0 0.1
0.3
0.9
1.04-1.44* 0.14-0.26****
1.04-1.44* 0.93-1.69
451
3.2
0.8
4.7
0.1
1.1
0.22-0.38****
1.29-2.26***
Who Did Not Have a Baby During the Study Interval VA Non-VA
Who had a Baby During the Study Interval
Total Admits
Percent of All Non-birth Admits
VA
3816 1590
26.8 11.2
27.8 5.3
22.4 15.1
2.1 0.4
1226 1144
8.6 8.0
6.6 4.1
9.0 10.7
1023
7.2
1.7
805
5.6
721
ORs show whether diagnoses in each category (compared to other non-birth diagnoses) changed the likelihood of using a VA Hospital, or of the patient also having a baby during 2004-2007. "Odds ratios that compare admissions for diagnoses in the particular category to all other hospitalizations—95% confidence interval and significance of difference from unity, where *p < 0.05, **p < 0.01, ***p < 0.0001, ****p < 0.0001. *Odds of going to a VA hospital if patients are admitted for diagnoses in the category. '^Odds that patients admitted for diagnoses in the category also had a pregnancy/birth hospitalization.
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Women's VA and Non-VA Hospitalizations
admitted to VA hospitals if they needed care for diagnoses not related to childbirth, / = 23.14, p < 0.0001, OR = 1.80, 95% CI = 1.41-2.20. Specific diagnostic categories for which this finding was significant include mental illness {p < 0.05) and diseases of the genitourinary system {p < 0.01), the digestive system {p < 0.05), and the respiratory system {p < 0.01). These results suggest that at least some dual users were VA users primarily but also had babies in non-VA hospitals. DISCUSSION Women Veterans of childbearing age who are enrolled in VA health care are admitted to non-VA hospitals twice as often as VAMCs. Relative to this overall ratio, they are more likely to go to VAMCs for the treatment of mental illness, digestive diseases, and neoplasms, and to non-VA hospitals for most other conditions, including genitourinary, circulatory, endocrine, nutritional, metabolic, immunity, respiratory, blood, and infectious diseases. Conditions for which VA care is preferred often require longer lengths of stay than the private sector provides, and the availability of inpatient treatment for mental illness in non-VA hospitals, or of commercial insurance coverage for it, is often very limited. Those women who are starting families use very little inpatient care aside from obstetric services, and nearly all their admissions are to nonVA hospitals. They are less likely than other women to be hospitalized for mental illness and cancer, though more likely to be admitted for infectious and parasitic diseases. Young women who are hospitalized in VAMCs, on the other hand, tend to be a few years older, sicker, lower income, and living closer to the VAMC; they also are much less likely to have a baby. Among dual users, those who have babies rely more on VAMCs, particularly for the treatment of mental illness and genitourinary, digestive, or respiratory diseases. Our findings suggest that planning services for these young women might benefit from considering their particular characteristics. VAMC bospitalizations are more likely to serve those who are a little older, sicker, and with fewer resources, who tend not to be starting families. Those who are starting families are healthier and rarely hospitalized for other reasons. However, a small proportion of women who are having babies do have other conditions that sometimes require hospitalization, such as mental illness, and they are more likely to seek that care from the VA. An implication for VA system planners might be that effectively meeting the health care needs of young women Veterans could require distinguishing patient types, focusing VA inpatient resources to serve some, and collaborating with non-VA hospitals for the care of others. The VA Women's Health Program (www.womenshealth .va.gov/WOMENSHEALTH/healthcare.asp) has been rapidly developing medical services for women, including pregnancyrelated services such as preconception checkups and maternity care. Each VAMC now has a Women Veterans Program Manager who can provide case management and care coordination to assist women in accessing care, including
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non-VA care, which should improve care transitions and maximize quality for women who choose to access both systems. VAMCs do not have the capacity to offer inpatient obstetric care nor are they likely to have the demand for services to warrant building that capacity. For certain enrollees with service-connected conditions, VA may pay for this care in non-VA hospitals, but most women will not qualify and must rely on commercial insurance or personal funds to pay for childbirth. Assuming they have these means, they are more likely to use non-VA care for other needs, as well. If VA seeks to increase the number of young women using its services, it might consider expanding prenatal, neonatal, and pédiatrie support services to establish contihuity of care, and collaborating with non-VA hospitals to refer patients for childbirth and follow-up with them immediately afterward. Such collaboration could include exchanging important information about other serious conditions th'at some women might have, and quick follow-up could better deal with complications such as postpartum depression^^ Our analyses have several limitations, of course, b'eyond the substantial number of enrollees for which information on their priority for VA care was missing. As this was an observational, retrospective study, with no opportunity to randomly assign patients to childbearing vs. no childbearing conditions, we could not control for unobserved covariates that might have distorted results. The ORs and significance that we report are very similar to those we found with logistic regressions that controlled for certain observed (though sometimes missing) covariates, but they do not account for unobserved confounders. Furthermore^ we distinguished women who had pregnancy/childbirth admissions from those who did not solely on the basis of their hospitalizations during the 4-year study interval; if any woman had a baby before or after that interval, we do not know about it. Though substantial differences in age and comorbid diagnoses give us some confidence in our group definitions, we acknowledge the unknowns. Finally, because our diagnostic information comes from administrative datasets, which are subject to coding errors, including non-VA data from seven different states that might have quite variable coding standards, there might be misclassifications to the diagnostic categories we used. With these limitations in mind, however, we conclude that VA planners seeking to better serve young women Veterans should distinguish the needs of those who are starting families from those who are not. ACKNOWLEDGMENTS The funding was provided by VA Health Services Research & Development IIR 07-233.
REFERENCES 1. Frayne SM, Phibbs CS, Friedman SA et al: Sourcebook: Women Veterans in the Veterans Health Administration. Volume 1. Sociodemographic Characteristics and Use of VHA Care. Women's Health Evaluation Initiative, Women Veterans Health Strategic Health Care Group, Veterans
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Women's VA and Non-VA Hospitalizations Health Administration, Department of Veterans Affairs, Washington, DC. December 2010. Available at http://www.va.gov/vhapublications/ ViewPublication.asp?pub_ID=2455; accessed December 6, 2012. 2. West AN, Weeks WB: Health care expenditures for urban and rural veterans in Veterans Health Administration care. Health Serv Res 2009; 44: 1718-34. 3. Bean-Mayberry B, Batuman F, Huang C, et al: Systematic Review of Women Veterans Health Research 2004-2008. VA-ESP Project No. 05226. U.S. Department of Veterans Affairs, 2010. Available at http:// www.hsrd.research.va.gQv/publications/esp/women.cfm; accessed December 6, 2012. .r''.;'':' 4. Vogt D, Bergeron A, Salgado D, Daley J, Ouimette P, Wolfe J: Barriers to Veterans Health Adrninistration care in a nationally representative sample of women Veterans. J Gen Intern Med 2006; 21(Suppl 3): S19-25.
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5. Washington DL, Yano EM, Simon B, Sun S: To use or not to use. What influences why women veterans choose VA health care. J Gen Intern Med2006;21(Suppl3):Sl'l-8:
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6. Goldzweig CL, Balekian TM, Rolon C, Yano EM, Shekelle PG: The state of women veterans' health research. Results of a systematic literature review. J Gen Intern Med 2006; 21 (Suppl 3): S82-92. 7. Washington DL, Kleimann S, Michelini AN, Kleimann KM, Canning M: Women veterans' perceptions and decision-making about Veterans Affairs health care. Mil Med 2007; 172: 812-7. 8. Kessler DP, Mylod D: Does patient satisfaction affect patient loyalty? Int J Health Care Qual Assur 2011; 24: 266-73. 9. Elixhauser A, Steiner C, Harris DR, Coffey RM: Comorbidity measures for use with administrative data. Med Care 1998; 36: 8-27. 10. Morrill R, Cromartie J, Han LG: Metropolitan, urban, and rural commuting areas: toward a better depiction of the United States settlement system. Urban Geogr 1999; 20: 727-48. 11. Hart LG, Larson EH, Lishner DM: Rural definitions for health policy and research. Am J Public Health 2005; 95: 1149-55. 12. Zdeb M: Driving Distances and Times Using SAS and Google Maps. SAS Global Forum 2010, 2010. Available at http://support.sas.com/resources/ papers/proceedingslO/050-2010.pdf; accessed December 6, 2012.
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Associations Between Childbirth and Women Veterans' VA and Non-VA Hospitalizations for Major Diagnostic Categories Alan N. West, PhD*; Pamela 1/1/. Lee, PhDf
ABSTRACT Women Veterans enrolled in Veterans Affairs (VA) health care almost always use non-VA hospitals for childbirth, making it more likely they will use non-VA hospitals for other needs, as well. We compared VA and non-VA hospitalizations obtained by VA enrollees in seven states from 2004 through 2007 to determine whether women aged 18 to 44 were more likely to use VA or non-VA care for diagnoses in certain major categories, and how this use differed between women who did or did not have any pregnancy/childbirth admissions during the 4 years. We found that women were hospitalized much more in non-VA than in VA hospitals, though they were relatively more likely to use VA hospitals for mental illness, digestive system diseases, and neoplasms than other diagnoses. Women who gave birth during the time interval had very few VA admissions for any diagnosis, and compared to other women they were also less likely to be hospitalized for mental health or cancer, but more likely to be hospitalized for infectious and parasitic diseases. VA hospitals were used more by women who were slightly older, sicker, poorer, and living nearer to them. VA-using women tend to have different and greater medical needs than those having children.
INTRODUCTION The number of women Veterans using Veterans Affairs (VA) health care has doubled since this century began; most of the new patients are young women in their reproductive years, a higher proportion have service-connected disabilities than ever bsfore, and many use VA primary care or mental health services more heavily than men. ' Yet like their male counterparts, women Veterans use non-VA health care more on average than they use VA care.^ Their choice between VA and non-VA health care depends on several factors, such as affordability and convenience (e.g., their income, eligibility for VA care, private insurance coverage, travel burden to reach care, lost work-time, and family burdens) as well as the availability of needed services.^ A national survey of women who were current or former users of VA health care** found that these Veterans, particularly women with service-connected disabüities, regarded ease of use as their greatest barrier to accessing VA care; for women without service connection, the availability of services was a stronger predictor of VA use. Another survey of women Veterans to understand their reasons for using either VA or non-VA health care^ found that VA users most often endorsed affordability, the availability of a women's health clinic, quality of care, and convenience as their reasons for using the VA. For those who used non-VA care, the most cited reasons for not using the VA were having private health insurance, the greater convenience of non-VA care, a perception that the quality of non-VA care is better, and lack of knowledge about their VA eligibility and benefits. A review of the health research on women Veterans^ concluded that female Veterans »Research Service, VAMC (10A5A), 215 N. Main Street, White River Junction, VT 05009. fVe-.erans Rural Health Resource Center—Eastern Region, VAMC (10A5A), 215 N. Main Street, White River Junction, VT 05009. doi: 10.7205/MILMED-D-13-00200
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use VA care less than male Veterans, and that they often seek health care for reasons that are gender specific. The authors also observed that most VA Medical Centers (VAMCs) provide basic health services for women and that having genderspecific care available has increased women's use of the VA. Yet women Veterans often do not know that the VA provides women's health care or that they are eligible to receive it. The medical or psychiatric needs of women Veterans are likely to differ for those having families, as they will tend to be younger and healthier than other female enrollees of childbearing age. Because VAMCs do not offer planned inpatient obstetric services, women Veterans who have babies must use non-VA hospitals. Because satisfactory experiences will enhance patient loyalty,^ they then may be more likely than other female enrollees to use non-VA hospitals for other conditions, as well. Of course, women hospitalized for reasons other than childbirth may use either VA or non-VA care, with the choice determined at least in part by their medical needs and their access to the appropriate services and expertise. VAMCs, for example, often provide psychiatric care or longer admissions for chronic medical conditions that nonVA hospitals do not. Furthermore, patients who are hospitalized more often are likely to have a wider array of medical problems and so may be more likely to use both VA and nonVA care. For any woman, the choice between going to a VAMC vs. a non-VA hospital will be influenced by the travel burden associated with each, as well as her priority status for receiving VA care (the VA gives greater priority to Veterans who have disabilities related to military service, are catastrophically disabled, or are impoverished). But even accounting for distance, disabüity/financial status, comorbidities, or frequency of hospitalization, young women Veterans may well use VA and non-VA hospitals differently depending on whether some of their use is for pregnancy/childbirth. To test such hypotheses, we analyzed hospital discharge data that include any admissions to either VA or non-VA
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Women's VA and Non-VA Hospitalizations
hospitals that VA enroUees living in any of seven states had during four recent years, 2004-2007. METHODS The pool of potential subjects for this study consisted of all Veterans listed in the VA health care system's 2007 national enrollment file as living in any of seven states (Arizona, Iowa, Louisiana, Florida, South Carolina, Pennsylvania, or New York). These seven states were the only ones we identified that (i) had data that included social security number (and birth date) to enable matching of enrollees to their nonVA hospitalization records, (ii) were willing (or allowed by law) to provide the data, and (iii) were willing to return a unique random identifier to permit matching patients across both VA and non-VA data. We analyzed administrative hospital discharge data for any inpatient admissions to VAMCs or in-state private sector hospitals (non-VAs) that these Veterans had at any time between 2004 and 2007. Because our data include any non-VA hospitalizations that these enrollees had in their home states and any VAMC admissions they had anywhere, their non-VA utilization might be under-represented but their VA usage is complete. VA's National Data Systems (NDS) provided us discharge data for any VAMC hospitalizations these enrollees had during the study interval. For each state, NDS also provided all enrollees' personal identifiers (social security number, date of birth, and gender) to the managers of non-VA hospitalization data (state government agencies or hospital associations), who used them to search for matching records in their databases, applying deterministic matching, i.e., exact matches only. After sending the matching treatment data to NDS, these agencies then deleted all records of enrollees' personal identifiers. The data files provided to us by NDS were stripped of all personal identifiers but included a randomly assigned unique identification number that enabled us to determine whether individuals had both VAMC and non-VA hospitalizations. These data files also included each patient's priority for VA care (described below) at the time of each hospitalization. This study was approved by Dartmouth College's Committee for the Protection of Human Subjects. Among Veterans of ages 18 to 44 in our hospital discharge data, 12,031 (27%) were women, who had 20,011 (23% of all) hospitalizations; roughly 16% of Veterans who had VAMC hospitalizations; and 32% of those who had non-VA admissions were women. We limited our analyses to women 18 to 44 years old, and compared those who had any hospitalization related to pregnancy or childbirth during the four years to those who did not. Among other variables, the administrative hospital discharge datasets included, for each hospitalization, the principal diagnosis (reason for the admission) as well as secondary diagnoses, the diagnosis-related group, length of stay (in days), and the ZIP code of the patient's residence. Diagnoses and diagnosis-related groups were submitted to pubUcly available comorbidity software developed by the Agency for Healthcare Research and Qual-
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ity (AHRQ) (http://www.hcup-us.ahrq.gov/toolssoftware/ comorbidity/comorbidity.jsp) to search administrative discharge data for any of 30 physical or psychiatric comorbid diagnoses identified as important predictors of treatment outcomes.' For each hospitalization, we summed the comorbidities detected to yield a single estimate of comorbid illness severity. To simplify utilization comparisons, we also assigned principal diagnoses to the highest-level major diagnostic categories produced by AHRQ's Clinical Classifications Software for ICD-9-CM codes (http://www.hcup-us .ahrq.gov/toolssoftware/ccs/ccsfactsheet.jsp); we report findings for the most frequent categories. We assigned each patient's residence to a Rural-Urban Commuting Area (RUCA) category'°'" by applying a publicly available ZIP code approximation to implement Categorization A (http://depts.washington.edu/uwruca/ruca-uses.php), which defines four categories: Urban, Large Rural Town, Small Rural Town, and Isolated Rural Town. We also applied a publicly available SAS routine'^ to access Google Maps for estimated driving times from the centroid of each patient's ZIP code to the centroids of the ZIP codes of all VAMCs in the patient's region (within a 300-mi. radius, regardless of state), and selected the shortest travel time as a measure of proximity to VA care. We repeated this process to select the nearest non-VA hospital, as well, using a comprehensive list drawn from Medicare's Hospital Compare site (http:// hospitalcompare.hhs.gov/). Finally, we assigned each patient to one of four categories reflecting priority for VA care: (i) patients in VA priority group 1, who have the highest levels of military service-connected disability and resulting unemployability; (ii) those in priority groups 2, 3, or 4, who generally have lower rated service-connected disability or non-service-connected catastrophic disabilities; (iii) those in priority group 5, who generally qualify for VA care because of low income; and (iv) those in priority groups 6, 7, and 8, who qualify for other reasons, including recent military service, or agree to make co-payments for care. We compared women who had any hospitalization for pregnancy or childbirth during the four study years to those who did not, using x^ analyses to compare their likelihood of being hospitalized, and their reliance on VAMCs vs. non-VA hospitals, for different principal diagnoses. We replicated these analyses using logistic regressions to control for age at admission, number of comorbid diagnoses, travel times to the nearest VAMC and the nearest non-VA hospital, priority for VA care, and urban-rural residence. However, because priority for VA care was missing for about 13% of admissions and because odds ratios (ORs) and decisions about the statistical significance of comparisons (whether or not priority for VA care was included) did not differ appreciably from those yielded by the simple x^ analyses, we report only the x'^ results here. We further separated the patients by whether they used VAMCs, non-VA hospitals, or both, during the study interval, and compared them on several characteristics, including age, comorbid diagnoses, hospital length of stay.
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Women's VA and Non-VA Hospitalizations
travel times, priority for VA care, and urban-rural residence, All analyses were conducted using SAS version 9.2 (SAS Institute, Cary, North Carolina). RESULTS Table I shows selected characteristics of the women, separated by whether or not they had any hospitalization during the four years for complications of pregnancy, childbirth, or the puerperium, and whether they were admitted to VA hospitáis, non-VA hospitals, or both during that time. For users of both VAMCs and non-VA hospitals (dual users), some utilization data are separated by hospital type. The table shows numbers of unique patients and numbers of admissions for each cell. Of the 12,031 unique patients, 9,186 (76.4%) used non-VA hospitals, exclusively, 1,911 (15.9%) used VA hospitals only, and 934 (7.7%) used both. Very few women used VA hospitals for obstetric care; in fact, if not emergencies—which VA data do not identify—these admissions might be attributable to coding errors. Women who had any admission for pregnancy/childbirth obtained 6,706 (96.6%) of their 6,941 hospitalizations (for all diagnoses) in non-VA TABLE I.
hospitals; other women obtained 8,276 (63.3%) of their 13,070 hospitalizations in non-VA hospitals, %^ = 2669.0, p < 0.0001. The difference in reliance on non-VA hospitals remains when obstetric admissions are excluded: Though there were 5,762 admissions for pregnancy/childbirth, the young mothers also had 1,179 hospitalizations (17.0% of all their admissions) for other principal diagnoses (221 in VA hospitais and 958 in non-VA hospitals). Compared to other women, they were much less likely to use VA hospitals for other conditions, as wd\,z^ = 152.50,/? < 0.0001, OR = 0.40, 95% CI = 0.34-0.46 (utilization for specific diagnostic categories is addressed below). In short, young women Veterans enrolled in VA health care relied more on non-VA hospitals than VAMCs, and much more so if they gave birth during the study interval. In addition. Table I shows that women who had pregnancy/ childbirth hospitalizations were younger than other women (mean ages: 29.5 vs. 36.6, t = 84.67, p < 0.0001), had fewer comorbid diagnoses (mean diagnoses: 0.3 vs. 1.3, í = 65.61, p < 0.0001), and lived slightly further from the nearest VAMC
Female Veterans 18 to 44 Years Old Living in Seven States and Enrolled in VA Health Care Who Were Admitted to Either VA or Non-VA Hospitals at Any Time in Four Years, 2004-2007 Hospitalized for Pregnancy/Childbirth Any Time in Four Years, 2004-2007? Yes
No Dual Users VA-Only Users Number of Unique Patients % of Total Number Number of Hospitalizations % of All Admissions Mean Admissions per Patient
1906 15.8 3003 15.0 1.6
VA
Non-VA 784 6.5
1791 9.0
1539 7.7 4.2
2.3 Mean Age at Admission (Years) (SD) Mean Comorbid Diagnoses (SD) Mean Length of Stay (Days) (SD) Percentages in Column VA Priority 1 2-4 5 6-8 RUCA Urban Large Rural Town Small Rural Town Isolated Rural Town Mean Driving Minutes to Nearest VA Hospital (SD) Nearest Non-VA Hospital (SD)
36.9 (6.2) 1.4 (1.3) 5.4 (11.2)
Non-VA-Only Users 4404 36.6 6737 33.7 1.5
Dual Users •*/A-Only User , 5 0.0 6 0.0 1.2
7.2 (10.6)
5.3 (5.8)
Non-VA 150 1.2
229 1.1
283 1.4 3.4
1.5
2.0 37.2 (6.2) 1.7 (1.4)
VA
36.1 (6.4) 1.0 (1.1) 4.1 (5.9)
31.3 (5.0) 0.3 (0.8) 3.3 (2.2)
Non-VA-Only Users 4782 39.7 6423 32.1 1.3
1.9 30.6 (6.0) 1.0 (1.1)
4.7 (5.6)
3.7 (5.6)
29.4 (5.2) 0.3 (0.7) 2.9 (4.2)
50.0 24.8 16.5 8.7
48.7 22.8 22.3 6.3
28.8 34.9 17.2 19.1
25.0 50.0 25.0 0.0
47.4 27.0 18.2 7.4
13.8 47.5 12.4 26.3
84.6 8.1 5.2 2.1
85.2 9.6 2.9 2.3
83.4 10.3 3.9 2.5
100.0 0.0 0.0 0.0
82.4 11.0 1.8 4.9
82.8 11.0 3.5 2.7
41.7 (36.5) 12.3 (12.6)
50.2 (43.5) 12.5 (13.1)
63.4 (47.4) 13.1 (12.0)
29.3 (24.1) 12.8 (7.5)
46.4 (36.1) 12.7 (11.9)
58.9 (45.3) 13.3 (12.2)
Separated by whether they used VA hospitals, non-VA hospitals, or both (dual users), and whether any hospitalization was for "complications of pregnancy, childbirth, or the puerperium."
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Women's VA andNon-VA Hospitalizations
(mean driving minutes: 58.0 vs. 55.1, t = 4.33, p < 0.0001) and study interval; and the odds that women with a particular from the nearest non-VA hospital (mean driving minutes: 13.3 diagnosis, compared to other women, went to a VAMC for it vs. 12.8, t = 2.74, p < 0.01). They also were much less likely to or also had a baby during the study interval. More than onebe in VA priority categories 1 (greatest service-connected fourth of all non-birth admissions were for mental illness, disabilities) or 5 (impoverished), %^ = 1249.9, p < 0.0001. and more than another one-fourth were for diseases of the The table also shows that whether or not they had obstetric genitourinary, digestive, or circulatory systems. For every hospitalizations, patients who used VA hospitals lived closer 100 women who did not have a birth admission, there were to them than those who used non-VA hospitals (mean driving more than 50 hospitalizations for mental illness, with more minutes: 42.9 vs. 60.5, t - 26.66, p < 0.0001), were shghtly in VAMCs than in non-VA hospitals. For every 100 women older (mean ages: 36.9 vs. 33.2, t = 35.31, p < 0.0001), had who did have a birth admission, on the other hand, there more comorbid diagnoses (mean diagnoses: 1.5 vs. 0.8, t = were only about 5 hospitahzations for mental illness. Patients 35.75, p < 0.0001), and were more likely to be in priority with other diagnoses consistently used non-VA hospitals categories 1 and 5,%'^ = 1213.5, p< O.OOOI. Group differences more than VAMCs. ORs indicate that relative to other diagin urban-rural, residence were inconsistent and relatively noses, admissions for mental illness, diseases of the digestive small, with (p coefficients of 0.03-0.04. These results suggest system, and neoplasms were more likely to be in VAMCs, that VA hospitals were relied on more by those young women whereas for treatment of genitourinary, circulatory, respirawho were slightly older, sicker, poorer, and living nearer to tory, blood, endocrine, nutritional, metabolic, or immunity them, and who were not in a phase of life in which they were disorders, non-VA hospitals were preferred. Women with bearing children. birth admissions during the study interval were also less likely Table II shows the number of admissions for principal to have an admission for mental health or cancer, but more diagnoses other than complications of pregnancy, childbirth, likely to be hospitalized for infectious and parasitic diseases. or the puerperium; the percentage of these non-birth admisHowever, among dual users (women who had at least one sions that each diagnostic category represents; the average hospitalization in both VA and non-VA hospitals), results number of admissions per diagnostic category for every 100 were unique: Those who had a pregnancy/childbirth hospitalwomen who either did or did not have a baby during the ization were actually more likely than other dual users to be
TABLE II.
VA and Non-VA Admissions for the Most Common Principal Diagnoses (Except Pregnancy/Birth) for Women Who Either Did or Did Not Have a Baby During the Four Years, 2004-2007 Admissions Per 100 Patients
Category of Principal Diagnosis Mental Illness Diseases of the Genitourinary System Diseases of the Digestive System Diseases of the Circulatory System Endocrine, Nutritional, and Metabolic Diseases, and Immunity Disorders Diseases of the Nervous System and Sense Organs Diseases of the Respiratory System Injury and Poisoning Diseases of the Musculoskeletal System Neoplasms Diseases of the Blood and Blood-Forming Organs Infectious and Parasitic Diseases
Non-VA
OR" Odds of Going to a VA Hospital"
OR" Odds That Patient Gave Birth in the Study Interval'^
3.0 2.4
2.82-3.29**** 0.52-0.66****
0.63-0.85**** 0.89-1.29
0.5 0.2
1.9 1.7
1.13-1.43**** 0.55-0.73****
0.98-1.47 0.76-1.19
11.3
O.I
1.9
0.20-0.29****
0.96-1.48
4.0
6.2
0.3
1.5
0.93-1.25
1.07-1.70*
5.1
2.3
6.8
0.2
1.3
0.48-0.68****
1.02-1.67*
716 657
5.0 4.6
3.2 3.2
6.2 5.5
0.2 0.1
0.7 0.8
0.77-1.06 0.85-1.18
0.54-1.00* 0.58-1.08
647 486
4.5 3.4
3.6 0.6
5.3 5.5
0.0 0.1
0.3
0.9
1.04-1.44* 0.14-0.26****
1.04-1.44* 0.93-1.69
451
3.2
0.8
4.7
0.1
1.1
0.22-0.38****
1.29-2.26***
Who Did Not Have a Baby During the Study Interval VA Non-VA
Who had a Baby During the Study Interval
Total Admits
Percent of All Non-birth Admits
VA
3816 1590
26.8 11.2
27.8 5.3
22.4 15.1
2.1 0.4
1226 1144
8.6 8.0
6.6 4.1
9.0 10.7
1023
7.2
1.7
805
5.6
721
ORs show whether diagnoses in each category (compared to other non-birth diagnoses) changed the likelihood of using a VA Hospital, or of the patient also having a baby during 2004-2007. "Odds ratios that compare admissions for diagnoses in the particular category to all other hospitalizations—95% confidence interval and significance of difference from unity, where *p < 0.05, **p < 0.01, ***p < 0.0001, ****p < 0.0001. *Odds of going to a VA hospital if patients are admitted for diagnoses in the category. '^Odds that patients admitted for diagnoses in the category also had a pregnancy/birth hospitalization.
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Women's VA and Non-VA Hospitalizations
admitted to VA hospitals if they needed care for diagnoses not related to childbirth, / = 23.14, p < 0.0001, OR = 1.80, 95% CI = 1.41-2.20. Specific diagnostic categories for which this finding was significant include mental illness {p < 0.05) and diseases of the genitourinary system {p < 0.01), the digestive system {p < 0.05), and the respiratory system {p < 0.01). These results suggest that at least some dual users were VA users primarily but also had babies in non-VA hospitals. DISCUSSION Women Veterans of childbearing age who are enrolled in VA health care are admitted to non-VA hospitals twice as often as VAMCs. Relative to this overall ratio, they are more likely to go to VAMCs for the treatment of mental illness, digestive diseases, and neoplasms, and to non-VA hospitals for most other conditions, including genitourinary, circulatory, endocrine, nutritional, metabolic, immunity, respiratory, blood, and infectious diseases. Conditions for which VA care is preferred often require longer lengths of stay than the private sector provides, and the availability of inpatient treatment for mental illness in non-VA hospitals, or of commercial insurance coverage for it, is often very limited. Those women who are starting families use very little inpatient care aside from obstetric services, and nearly all their admissions are to nonVA hospitals. They are less likely than other women to be hospitalized for mental illness and cancer, though more likely to be admitted for infectious and parasitic diseases. Young women who are hospitalized in VAMCs, on the other hand, tend to be a few years older, sicker, lower income, and living closer to the VAMC; they also are much less likely to have a baby. Among dual users, those who have babies rely more on VAMCs, particularly for the treatment of mental illness and genitourinary, digestive, or respiratory diseases. Our findings suggest that planning services for these young women might benefit from considering their particular characteristics. VAMC bospitalizations are more likely to serve those who are a little older, sicker, and with fewer resources, who tend not to be starting families. Those who are starting families are healthier and rarely hospitalized for other reasons. However, a small proportion of women who are having babies do have other conditions that sometimes require hospitalization, such as mental illness, and they are more likely to seek that care from the VA. An implication for VA system planners might be that effectively meeting the health care needs of young women Veterans could require distinguishing patient types, focusing VA inpatient resources to serve some, and collaborating with non-VA hospitals for the care of others. The VA Women's Health Program (www.womenshealth .va.gov/WOMENSHEALTH/healthcare.asp) has been rapidly developing medical services for women, including pregnancyrelated services such as preconception checkups and maternity care. Each VAMC now has a Women Veterans Program Manager who can provide case management and care coordination to assist women in accessing care, including
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non-VA care, which should improve care transitions and maximize quality for women who choose to access both systems. VAMCs do not have the capacity to offer inpatient obstetric care nor are they likely to have the demand for services to warrant building that capacity. For certain enrollees with service-connected conditions, VA may pay for this care in non-VA hospitals, but most women will not qualify and must rely on commercial insurance or personal funds to pay for childbirth. Assuming they have these means, they are more likely to use non-VA care for other needs, as well. If VA seeks to increase the number of young women using its services, it might consider expanding prenatal, neonatal, and pédiatrie support services to establish contihuity of care, and collaborating with non-VA hospitals to refer patients for childbirth and follow-up with them immediately afterward. Such collaboration could include exchanging important information about other serious conditions th'at some women might have, and quick follow-up could better deal with complications such as postpartum depression^^ Our analyses have several limitations, of course, b'eyond the substantial number of enrollees for which information on their priority for VA care was missing. As this was an observational, retrospective study, with no opportunity to randomly assign patients to childbearing vs. no childbearing conditions, we could not control for unobserved covariates that might have distorted results. The ORs and significance that we report are very similar to those we found with logistic regressions that controlled for certain observed (though sometimes missing) covariates, but they do not account for unobserved confounders. Furthermore^ we distinguished women who had pregnancy/childbirth admissions from those who did not solely on the basis of their hospitalizations during the 4-year study interval; if any woman had a baby before or after that interval, we do not know about it. Though substantial differences in age and comorbid diagnoses give us some confidence in our group definitions, we acknowledge the unknowns. Finally, because our diagnostic information comes from administrative datasets, which are subject to coding errors, including non-VA data from seven different states that might have quite variable coding standards, there might be misclassifications to the diagnostic categories we used. With these limitations in mind, however, we conclude that VA planners seeking to better serve young women Veterans should distinguish the needs of those who are starting families from those who are not. ACKNOWLEDGMENTS The funding was provided by VA Health Services Research & Development IIR 07-233.
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Women's VA and Non-VA Hospitalizations Health Administration, Department of Veterans Affairs, Washington, DC. December 2010. Available at http://www.va.gov/vhapublications/ ViewPublication.asp?pub_ID=2455; accessed December 6, 2012. 2. West AN, Weeks WB: Health care expenditures for urban and rural veterans in Veterans Health Administration care. Health Serv Res 2009; 44: 1718-34. 3. Bean-Mayberry B, Batuman F, Huang C, et al: Systematic Review of Women Veterans Health Research 2004-2008. VA-ESP Project No. 05226. U.S. Department of Veterans Affairs, 2010. Available at http:// www.hsrd.research.va.gQv/publications/esp/women.cfm; accessed December 6, 2012. .r''.;'':' 4. Vogt D, Bergeron A, Salgado D, Daley J, Ouimette P, Wolfe J: Barriers to Veterans Health Adrninistration care in a nationally representative sample of women Veterans. J Gen Intern Med 2006; 21(Suppl 3): S19-25.
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