HE380.0.1 Managed Healthcare Assignment 8

Chang et al. BMC Health Services Research (2015) 15:27 DOI 10.1186/s12913-015-0684-8

RESEARCH ARTICLE Open Access

Medicare and Medicaid enrollment and outside hospitalizations among HIV-infected and uninfected veterans engaged in VA care: a retrospective cohort study Harry Chang1,2*, Janet Tate2, Amy C Justice2,3,4 and Michael E Ohl5,6,7

Abstract

Background: Many veterans engaged in care with the Veterans Administration (VA) health system are also enrolled in Medicare and/or Medicaid and may receive care both inside and outside of the VA. Use of dual health systems has been associated with worse outcomes. Veterans with HIV may have different rates of Medicare and Medicaid enrollment and may be at greater risk of poor outcomes related to non-VA use. This study compares the frequency and factors associated with Medicare and/or Medicaid enrollment and non-VA use in an HIV-infected and uninfected population of veterans.

Methods: We used data from the VA and Center for Medicare & Medicaid Services from 2004 and 2005 to determine the frequency of Medicare and/or Medicaid enrollment among a cohort of HIV-infected and uninfected veterans engaged in VA care. We then restricted the cohort to veterans enrolled in fee-for-service (FFS) Medicare and/or Medicaid with at least one hospitalization and identified characteristics associated with non-VA hospital admissions.

Results: HIV-infected veterans had higher rates of Medicare and/or Medicaid enrollment than uninfected veterans (38% vs. 33%, p < 0.01), though the opposite was true when our sample was limited to veterans 65 years and older (53% vs. 70%, p < 0.0 1). Among veterans enrolled in the VA and FFS Medicare and/or Medicaid, veterans with HIV had greater illness severity and more frequent hospitalizations, but were less likely to be hospitalized outside the VA (48% vs. 54%, p < 0.01). HIV infection was associated with lower odds of outside hospitalization (OR = 0.76 [95% CI: 0.68, 0.85]).

Conclusions: Veterans with HIV have higher rates of Medicare and/or Medicaid enrollment, but lower odds of non-VA hospitalization. The VA integrated model of HIV care may discourage outside use among HIV-infected veterans.

Keywords: HIV, AIDS, Veterans, Medicare, Medicaid, Fragmentation

Background A significant proportion of veterans enrolled with the Veterans Administration (VA) healthcare system are also enrolled in Medicare and/or Medicaid (“CMS enrollment”). An expansion of Medicaid coverage under the Patient Pro- tection and Affordable Care Act of 2010 (ACA) will likely increase the proportion of CMS enrolled veterans [1]. Use

* Correspondence: [email protected] 1Yale School of Medicine, Yale University, 333 Cedar Street, New Haven, CT 06510, USA 2Veterans Aging Cohort Study, VA Connecticut Healthcare System, 950 Campbell Avenue, West Haven, CT 06516, USA Full list of author information is available at the end of the article

© 2015 Chang et al.; licensee BioMed Central. Commons Attribution License (http://creativec reproduction in any medium, provided the or Dedication waiver (http://creativecommons.or unless otherwise stated.

of non-VA health care (“CMS use”) among veterans already engaged in VA care can lead to fragmented, inefficient, lower quality care and increased mortality [2-6]. Previous work has described CMS enrollment and

identified factors that influence CMS use among VA en- rolled veterans, particularly veterans 65 years and older that have age qualified for Medicare [7-9]. Less is known about CMS use among veterans under 65 years of age, who may qualify for Medicare through disability, or those enrolled in Medicaid. People living with HIV are more likely to qualify for Medicare through disability than age, and Medicare currently provides coverage for

This is an Open Access article distributed under the terms of the Creative ommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and iginal work is properly credited. The Creative Commons Public Domain g/publicdomain/zero/1.0/) applies to the data made available in this article,

Chang et al. BMC Health Services Research (2015) 15:27 Page 2 of 9

approximately one-fifth of the people receiving HIV care in the U.S. [10]. Medicaid coverage for HIV varies on a state-to-state basis, but it currently covers about 50% of the people receiving HIV care in the U.S. [11]. Little is known about CMS enrollment among HIV-infected vet- erans, and the frequency and drivers of CMS use among veterans with both VA and CMS coverage. HIV-infected veterans are an aging cohort vulnerable to

adverse outcomes because of the complexity of their care needs, including multimorbidity, polypharmacy, mental health issues, and substance use [12-14]. The VA is the largest provider of care for persons with HIV in the United States, with over 20,000 veterans in care, and has invested significant resources to create an inte- grated HIV care model [15,16]. The integrated model for HIV care in VA emphasizes case management and access to coordinated medical and behavioral health care services, including mental health care, urgent care, substance abuse and on-site pharmacy services. Previ- ous research has demonstrated that integrated HIV care at the VA can lead to higher rates of viral load suppres- sion [14]. Given the high, and potentially expanding, rates of CMS enrollment in the HIV population, an un- derstanding of Medicare and Medicaid enrollment and the frequency and drivers of CMS use among veterans with HIV is necessary to inform efforts to coordinate care. The objectives of this paper were to: 1) determine the

frequency of Medicare and/or Medicaid enrollment among HIV-infected veterans engaged in VA care, com- pared with uninfected veterans; 2) determine the fre- quency of non-VA hospital admissions among male, CMS enrolled HIV-infected and uninfected veterans with any hospitalizations; and 3) identify characteristics that pre- dict non-VA hospital admission among male HIV-infected veterans enrolled in Medicare and/or Medicaid, compared with uninfected veterans. We hypothesized that CMS en- rolled HIV-infected veterans would be less likely to use non-VA care than their uninfected counterparts.

Methods This retrospective cohort study included two popula- tions of veterans in VA care in the United States during 2004 and 2005: 1) HIV-infected veterans; and 2) age, race and facility-matched uninfected comparators. We used data from the Veterans Aging Cohort Study

(VACS), a prospective, observational cohort study of HIV infected veterans and age, race and site matched controls. VACS is made up of eight urban sites, but also includes a virtual cohort (VACS-VC), a nationally repre- sentative sample of HIV-infected veterans and matched uninfected controls identified through the VA electronic medical record (EMR) system and followed since 1996 [17,18]. Demographic data, medical diagnoses (based on

International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] codes), and labora- tory results were extracted from VA EMR. Medicare and/or Medicaid enrollment and utilization for these veterans were extracted from data provided by the Cen- ter for Medicare & Medicaid Services (CMS). The study received approval from Human Investigations Commit- tee at Yale University and the VA Connecticut Health- care System and was granted a waiver of informed consent. We started with a cohort that included all veterans en-

rolled in the VACS-VC prior to January 1, 2003 (cohort 1 in Figure 1) and engaged in VA care. For the purpose of this analysis we defined engaged in care as at least one inpatient or outpatient visit to a VA medical center in 2003. Using CMS enrollment data we determined the frequency of Medicare and/or Medicaid enrollment in this cohort. To study frequency and drivers of CMS use we limited our cohort of VA enrolled veterans to include only those with coverage for CMS use. We narrowed our sample to veterans that were CMS enrolled in the 2004 and 2005 calendar years and had at least one in- patient admission in either VA or non-VA hospitals dur- ing this same period. From this group we excluded those CMS enrolled for less than 18 months in the 24 month period, enrolled in HMO plans (as defined in the CMS data file), and enrolled in Medicaid in more than one state. Finally, we excluded female veterans, due to their low numbers in our final sample (cohort 2 in Figure 1). Our final sample consisted of 7,765 male HIV infected and uninfected veterans enrolled in FFS Medicare and/ or Medicaid with at least one inpatient admission in 2004 and 2005. We used this cohort to determine the frequency and predictors of non-VA hospital admissions. We created a series of variables to identify factors asso-

ciated with non-VA hospital admissions among male vet- erans, enrolled in fee for service (FFS) Medicare and/or Medicaid that received inpatient care in 2004 and 2005 (cohort 2). Our dependent variable was a dichotomous in- dicator of any non-VA admissions, (vs. only VA inpatient admissions). Hospital admissions were identified by com- bining VA EMR data with CMS FFS reimbursement files. We considered a number of independent variables we

believed could influence use of non-VA inpatient care, including demographics, access to care, illness severity, and admission to a medical or surgical intensive care unit (ICU). Age and race data were taken from VA ad- ministrative databases. Age was constructed as a dichot- omous variable, under age 65 and 65 years and older. Race was divided into three categorical variables: White, African American, and Other. Patients’ access to care was measured by three variables:

enrollment in Medicare, Medicaid or both programs; dis- tance to nearest VA tertiary care center treated as a

Figure 1 Cohort development for 2004 dual enrollment and dual use in 2004-2005. 1Veterans Aging Cohort Study Virtual Cohort. 2Veterans Administration. 34827 veterans excluded because died in 2004 or 2005. 4Health Maintenance Organization. 5Fee-for-service.

Chang et al. BMC Health Services Research (2015) 15:27 Page 3 of 9

categorical variable: 0 to 9.9 miles, 10-29.9 miles, 30-59.9 miles, 60-119.9 miles, and greater than 120 miles [19]; and an indicator of whether veterans were subject to co-pays for VA care. Co-pay status was in turn determined using data on service connection, medical conditions, and an income-based means test for each veteran. We used the CMS hierarchical condition categories

(HCC) model to calculate risk scores [20] and used the scores as a measure of patients’ illness severity. The HCC model is a risk adjustment method employed by CMS to predict prospective payments for patients based on the pre- vious year’s claims data, using patient demographics and major medical conditions, and has been applied to the VA population in the past for similar analyses [7]. Each year the average risk score is set at one, and we divided our HCC risk scores into a dichotomous variable: scores greater than one and scores less than or equal to one. We created a bin- ary variable for HIV status, identified through VA admi- nistrative data. We also used VA administrative data to identify veterans that carried a diagnosis of a substance use problem (illicit substance abuse or dependence) using ICD- 9CM codes and a previously validated algorithm available on the VACS website (vacohort.org).

We generated categorical variables for number of in- patient admissions (one vs. two or more) and the admis- sion diagnosis (ICU vs. non-ICU admission) because we believe both could influence the likelihood of a veteran having a non-VA admission. Veterans with more fre- quent admissions have more “opportunities” to be hospi- talized in a non-VA facility. Similarly, patients in critical condition, requiring admission to ICUs, may be more likely to be routed to a non-VA hospital. Though these variables do not reflect patient behavior, they may influ- ence the likelihood of an admission outside the VA and, thus, we controlled for these factors in our model.

Analysis We first examined veterans in the VACS-VC (cohort 1) to determine the frequency of CMS enrollment among veterans engaged in care. We stratified our analysis by age and HIV status, and used student t-tests to compare the frequency of CMS enrollment between HIV-infected and uninfected veterans. Next, we described the cohort of male, veterans enrolled in FFS Medicare and/or Medicaid with at least one inpatient admission (cohort 2) using the independent variables listed above. We stratified cohort

Chang et al. BMC Health Services Research (2015) 15:27 Page 4 of 9

2 by HIV status and used chi-squared tests to compare the two sub-populations. Finally, we explored the asso- ciation between these independent variables and non- VA hospital admissions using univariate and multivariable logistic regression. We created a multivariate model that included all patients in cohort 2, as well as separate models stratified by HIV status. All analyses were con- ducted using SAS version 9.2.

Results Overall, HIV-infected veterans engaged in VA care were more likely than uninfected veterans to be enrolled in Medicare and/or Medicaid (38% vs. 33%, p < 0.01) (Table 1). While HIV-infected veterans under age 65 were more likely to be CMS enrolled than uninfected veterans, (36% vs. 29%, p < 0.01), HIV-infected veterans 65 years and older were less likely to be CMS enrolled (53% vs. 70%, p < 0.01). The majority of CMS enrolled veterans were enrolled in Medicare, but HIV-infected veterans were more likely than uninfected veterans to be enrolled in Me- dicaid, either alone or in combination with Medicare. Among veterans enrolled in FFS Medicare and/or Me-

dicaid with at least one inpatient admission (cohort 2) the frequency of HIV-infected veterans with CMS use was lower than the frequency among uninfected veterans (48% vs.54%, p < 0.01) (Table 2). Compared to uninfected veterans, HIV-infected veterans were younger and lived closer to VA hospitals. A greater proportion of HIV- infected veterans was also of African American race, had an HCC score greater than 1 and carried a diagnosis of substance use problem.

Table 1 Medicare and/or Medicaid enrollment among veteran

All patients n (%)

n = 91369

Total Unique in VACS-VC

Medicare Only 20964 (23)

Medicaid Only 5220 (6)

Medicare and Medicaid 5290 (6)

Total Enrolled in CMS2 31474 (34)

Under 65 n = 82835

Medicare Only 16309 (20)

Medicaid Only 5187 (6)

Medicare and Medicaid 4475 (5)

Total Enrolled in CMS 25971 (31)

65 and over n = 8534

Medicare Only 4655 (55)

Medicaid Only 33 (0)

Medicare and Medicaid 815 (10)

Total Enrolled in CMS 5503 (64) 1Veterans Aging Cohort Study – Virtual Cohort. 2Center for Medicare & Medicaid Service.

HIV-infected veterans had lower odds of CMS use than uninfected veterans (OR = 0.78 [95% CI: 0.71, 0.85]) (Table 3). In addition, older veterans and veterans with higher HCC risk scores had greater odds of CMS use than their respective younger and healthier counterparts. Among HIV-infected veterans a substance abuse diagno- sis was associated with increased non-VA use (OR = 1.34 [95% CI: 1.14, 1.58]). There was not a significant associ- ation between substance abuse and non-VA use in unin- fected veterans (OR = 0.91 [95% CI: 0.80, 1.04]). The association between HIV status and decreased

odds of non-VA use remained in the multivariable model (OR = 0.76 [95% CI: 0.68, 0.85]); however, there was no longer an association between higher HCC risk score and increased non-VA use (Table 4). We posited that number of admissions, which had the greatest marginal effect on the multivariate model, was overwhelming the effects of other variables. When we removed number of admissions from the adjusted model (analysis not shown), both higher HCC risk score and African American race had significant associations with increased non-VA use (OR = 1.28 [95% CI: 1.13, 1.44] and OR = 1.18 [95% CI: 1.05, 1.33], respectively). After stratifying by HIV statuses, the predictors of

CMS use were similar in both the HIV-infected and un- infected models (Table 4).

Discussion In our sample of veterans engaged in VA care, we found that HIV-infected veterans were more likely than their uninfected counterparts to be enrolled in Medicare and/

s enrolled in VACS-VC1 in 2004

HIV+ n (%) HIV- n (%) p-value

n = 29909 n = 61460

6461 (22) 14503 (24) <.0001

2203 (7) 3017 (5) <.0001

2618 (9) 2672 (4) <.0001

11282 (38) 20192 (33) <.0001

n = 27193 n = 55642

5334 (20) 10975 (20) 0.7111

2190 (8) 2997 (5) <.0001

2329 (9) 2146 (4) <.0001

9853 (36) 16118 (29) <.0001

n = 2716 n = 5818

1127 (41) 3528 (61) <.0001

13 (0) 20 (0) 0.3497

289 (11) 526 (9) 0.0192

1429 (53) 4074 (70) <.0001

Table 2 CMS1 enrolled veterans with 1 or more inpatient admissions in 2004 and 2005

All patients n (%)

HIV+ n (%) HIV- n (%) p-value

n = 7765 n = 2799 n = 4966

DEMOGRAPHICS

Age

<65 6319 (81) 2405 (86) 3914 (79) <.0001

≥65 1446 (19) 394 (14) 1052 (21)

Race

White 3903 (50) 1343 (48) 2560 (52) 0.009

African American 3755 (48) 1413 (50) 2342 (47)

Other 107 (2) 43 (2) 64 (1)

Distance from VA

0-9.9 miles 3253 (42) 1445 (52) 1808 (36) <.0001

10-29.9 miles 1824 (24) 599 (21) 1225 (25)

30-59.9 miles 1270 (16) 393 (14) 877 (18)

60-119.9 miles 1192 (15) 310 (11) 882 (18)

≥120 miles 224 (3) 52 (2) 172 (3)

Co-pay status

No Co-pay 7174 (95) 2592 (96) 4582 (95) 0.0997

Co-pay 352 (5) 112 (4) 240 (5)

ENROLLMENT

Medicare Only 6408 (83) 2088 (74) 4320 (87) <.0001

Medicaid Only 469 (6) 274 (10) 195 (4)

Medicare and Medicaid 888 (11) 437 (16) 451 (9)

HEALTH

HIV

Positive 2799 (36)

Negative 4966 (64)

HCC Risk Score2

<1 4129 (53) 1040 (37) 3089 (62) <.0001

≥1 3636 (47) 1759 (63) 1877 (38)

INPATIENT ADMISSIONS

Number of Admissions

1 3186 (41) 1091 (39) 2095 (42) 0.0058

≥2 4579 (59) 1708 (61) 2871 (58)

ICU3 Admission

Yes 1637 (21) 575 (21) 1062 (21) 0.3822

No 6128 (79) 2224 (79) 3904 (79)

Substance Abuse

Yes 1958 (25) 828 (30) 1130 (23) <.0001

No 5807 (75) 1971 (70) 3836 (77)

UTILIZATION

VA4 Admissions Only 3757 (48) 1467 (52) 2290 (46) <.0001

Non-VA Admission 4008 (52) 1332 (48) 2676 (54) 1Center for Medicare & Medicaid Serivces. 2Hierarchical Conditional Category Risk Score. 3Intensive Care Unit. 4Veterans Administration.

Chang et al. BMC Health Services Research (2015) 15:27 Page 5 of 9

or Medicaid, but this difference varied by age. HIV- infected veterans under age 65 were more likely to be CMS enrolled, while HIV-infected veterans 65 years and older were much less likely to be CMS enrolled. Confirm- ing our initial hypothesis, we also found that male, HIV- infected veterans enrolled in FFS Medicare and/or Medic- aid were less likely to have an outside hospitalization. This was despite the fact that these veterans were generally sicker, more likely to have multiple admissions, and more likely to be enrolled in FFS Medicaid – independent risk factors for greater non-VA use. We suspect that HIV-infected veterans were less likely

to use non-VA hospitals because they feel more tied to the VA – possibly due to the integrated care and the dif- ferent providers they see in VA infectious disease clinics or the desire for continuity with established caregivers for what is historically a stigmatized disease. The pre- scription drug coverage afforded veterans – and the high costs of antiretroviral therapy - may also play a signifi- cant role. While every state provides some coverage for antiretroviral drugs, the coverage varies substantially. Very few states cover as many of these drugs as are cov- ered nationally within VA. This conclusion is also sup- ported from patient self report data in VACS 8 in which 96% of those on ART reported getting all their antiretro- viral medications through VA [17]. Our findings on frequency of CMS enrollment among

veterans were not completely consistent with previous literature. Overall, we found lower rates of Medicare en- rollment, but higher rates of enrollment in Medicaid [21]. This difference was particularly evident among vet- erans 65 years and older where Medicare enrollment has been reported to be greater than 90% [7,21]. This dif- ference is likely driven primarily by our initial cohort (cohort 1), which included only patients who were already engaged in VA care, i.e. were seen at the VA at least once in the past year. We suspect that veterans already receiving care at the VA are less likely to seek al- ternative forms of coverage than all veterans ever en- rolled in VA care. The difference may also be partially attributed to the greater share of HIV-infected veterans in our sample than in previously studied groups. VACS- VC is a nationally representative sample of HIV-infected veterans, not all veterans enrolled in VA care. As noted in the background, HIV-infected veterans differentially qualify for Medicare coverage, primarily through disabi- lity [10]. Similarly, we believe that comorbid and socio- economic factors that contribute to higher rates of Medicaid enrollment among all persons living with HIV contributed to the higher rates of Medicaid enrollment in our sample of veterans. Among HIV infected and un- infected veterans, some of these changes may also be partially driven by a change in the population utilizing VA care since 1999 [8,21], when Shen, et al. reported

Table 3 Characteristics associated with non-VA inpatient admissions in 2004 and 2005, univariate analysis

All patients n (%) p-value HIV+ n (%) p-value HIV- n (%) p-value

DEMOGRAPHICS

Age

<65 Ref Ref Ref

≥65 1.86 (1.65-2.09) <.0001 1.39 (1.12-1.72) 0.0028 2.05 (1.77-2.36) <.0001

Race

White Ref Ref Ref

African American 0.96 (0.87-1.04) 0.3126 1.08 (0.93-1.26) 0.3031 0.90 (0.81-1.01) 0.0696

Other 3.40 (2.13-5.41) <.0001 3.39 (1.70-6.79) 0.0006 3.58 (1.90-6.74) <.0001

Distance from VA

0-9.9 miles Ref Ref Ref

10-29.9 miles 1.30 (1.16-1.46) <.0001 1.16 (0.96-1.40) 0.1297 1.37 (1.19-1.59) <.0001

30-59.9 miles 1.75 (1.54-2.00) <.0001 1.45 (1.16-1.81) 0.0012 1.91 (1.62-2.25) <.0001

60-119.9 miles 2.55 (2.22-2.93) <.0001 1.92 (1.49-2.46) <.0001 2.82 (2.38-3.34) <.0001

≥120 miles 2.41 (1.82-3.20) <.0001 2.95 (1.62-5.37) 0.0004 2.26 (1.63-3.12) <.0001

Co-pay status

No Co-pay Ref Ref Ref

Co-pay 2.58 (2.04-3.27) <.0001 1.92 (1.30-2.84) 0.001 3.01 (2.22-4.08) <.0001

ENROLLMENT

Medicare Ref Ref Ref

Medicaid 1.94 (1.60-2.36) <.0001 2.51 (1.94-3.27) <.0001 1.75 (1.30-2.36) 0.0003

Medicare and Medicaid 2.40 (2.07-2.79) <.0001 2.95 (2.38-3.68) <.0001 2.26 (1.83-2.80) <.0001

HEALTH

HIV

Positive 0.78 (0.71-0.85) <.0001

Negative Ref

HCC Risk Score1

<1 Ref Ref Ref

≥1 1.14 (1.04-1.25) 0.004 1.26 (1.08-1.46) 0.0039 1.21 (1.08-1.36) 0.0014

INPATIENT ADMISSIONS

Number of Admissions

1 Ref Ref Ref

≥2 3.06 (2.79-3.37) <.0001 4.29 (3.64-5.06) <.0001 2.64 (2.35-2.97) <.0001

ICU2 Admission

Yes 2.21 (1.97-2.47) <.0001 2.00 (1.66-2.42) <.0001 2.34 (2.02-2.70) <.0001

No Ref Ref Ref

Substance Abuse

Yes 1.04 (0.94-1.15) 0.4531 1.34 (1.14-1.58) 0.0004 0.91 (0.80-1.04) 0.1549

No Ref Ref Ref 1Hierarchical Conditional Category Risk Score. 2Intensive Care Unit.

Chang et al. BMC Health Services Research (2015) 15:27 Page 6 of 9

their data, and our results from five years later, and may also reflect an evolving perception of VA care or in- creased Medicare cost sharing. Our findings regarding predictors of non-VA hospita-

lization among CMS enrolled veterans engaged in VA

care were consistent with previous literature. In general, these studies have found older age, increased distance to the VA, greater cost-sharing and worse health to be as- sociated with non-VA use [7,8,22,23]. Our results con- firm these findings among HIV-infected veterans, and

Table 4 Characteristics associated with non-VA inpatient admissions in 2004 and 2005, multivariate analysis

All patients n (%) p-value HIV+ n (%) p-value HIV- n (%) p-value

DEMOGRAPHICS

Age

<65 Ref Ref Ref

≥65 1.90 (1.65-2.17) <.0001 1.61 (1.25-2.08) 0.0002 2.00 (1.70-2.35) <.0001

Race

White Ref Ref Ref

African American 1.05 (0.94-1.16) 0.4032 1.02 (0.86-1.22) 0.8293 1.07 (0.94-1.22) 0.3128

Other 3.17 (1.91-5.27) <.0001 3.58 (1.63-7.85) 0.0015 2.98 (1.52-5.83) 0.0015

Distance from VA

0-9.9 miles Ref Ref Ref

10-29.9 miles 1.51 (1.33-1.72) <.0001 1.41 (1.13-1.75) 0.0022 1.59 (1.35-1.86) <.0001

30-59.9 miles 2.08 (1.79-2.41) <.0001 1.78 (1.38-2.30) <.0001 2.25 (1.87-2.70) <.0001

60-119.9 miles 3.42 (2.92-4.01) <.0001 3.06 (2.29-4.09) <.0001 3.62 (2.99-4.37) <.0001

≥120 miles 3.06 (2.23-4.19) <.0001 5.67 (2.90-11.06) <.0001 2.61 (1.83-3.74) <.0001

Co-pay status

No Co-pay Ref Ref Ref

Co-pay 2.66 (2.05-3.46) <.0001 2.61 (1.68-4.05) <.0001 2.76 (1.99-3.84) <.0001

ENROLLMENT

Medicare Ref Ref Ref

Medicaid 2.83 (2.28-3.52) <.0001 2.93 (2.17-3.94) <.0001 2.57 (1.85-3.57) <.0001

Medicare and Medicaid 2.50 (2.11-2.95) <.0001 2.89 (2.27-3.69) <.0001 2.17 (1.72-2.73) <.0001

HEALTH

HIV

Positive 0.76 (0.68-0.85) <.0001

Negative Ref

HCC Risk Score1

<1 Ref Ref Ref

≥1 0.99 (0.89-1.10) 0.8071 0.95 (0.79-1.14) 0.5937 1.01 (0.88-1.15) 0.9127

INPATIENT ADMISSIONS

Number of Admissions

1 Ref Ref Ref

≥2 3.10 (2.79-3.45) <.0001 4.45 (3.69-5.37) <.0001 2.62 (2.30-2.98) <.0001

ICU2 Admission

Yes 1.73 (1.52-1.96) <.0001 1.42 (1.15-1.76) 0.0012 1.94 (1.65-2.27) <.0001

No Ref Ref Ref

Substance Abuse

Yes 1.16 (1.03-1.31) 0.0179 1.28 (1.05-1.55) 0.0138 1.08 (0.92-1.26) 0.3356

No Ref Ref Ref 1Hierarchical Conditional Category Risk Score. 2Intensive Care Unit.

Chang et al. BMC Health Services Research (2015) 15:27 Page 7 of 9

provide guidance to VA care providers on patients that are more likely to receive non-VA care and thus benefit from care coordination efforts with outside providers. Our results should be viewed in light of several limita-

tions – most importantly, our limited access to data on

private insurance enrollment and utilization in the VA population. As a result of the lack of claims data for pa- tients hospitalized under private insurance, some pa- tients classified as having only VA admissions may actually have unaccounted for admissions to non-VA

Chang et al. BMC Health Services Research (2015) 15:27 Page 8 of 9

hospitals. Moreover, CMS enrollment with private insur- ance may lead to significantly lower costs for veterans, in- fluencing their choice of health care setting. The VACS does collect some survey data on private insurance enroll- ment. Among veterans in VACS8, 15% of HIV-infected veterans and 20% of uninfected veterans reported enroll- ment in private insurance (analysis not shown). Given the lower rates of supplemental insurance in the HIV-infected population, we believe our finding that HIV-infected vet- erans are less likely to have non-VA admissions likely still holds true. Another limitation is that inpatient admissions are more likely to be influenced by factors beyond patient preference. We tried to control for those variables in our analysis, but using inpatient admissions as our outcome may limit the conclusions that can be drawn from our re- sults. We chose inpatient admissions because non-VA in- patient care places HIV-infected veterans at risk for adverse events related to poor coordination of care transi- tions between outside hospitals and VHA HIV clinics; however, choice in outpatient setting may be a better re- flection of patient preferences and will be the subject of future studies. We also did not take into account pathways to CMS enrollment. Veterans that were enrolled in Medi- care or Medicaid prior to engagement with the VA system may be more likely to have non-VA admissions; the op- posite may be true of veterans that were seeking care with the VA prior to enrolling with Medicare and/or Medicaid. In addition, though most HIV infected people with Medi- care qualify through disability, it is unknown if this is also true among veterans. The heterogeneity of Medicare and/or Medicaid from

state to state further limits our ability to generalize the data. Medicare Advantage plans, i.e. managed care plans provided by private insurers, are highly variable by de- sign, and Medicaid benefits and eligibility vary from state to state. Moreover, to date only 26 of the 50 states have chosen to accept the ACA provision to expand Me- dicaid, making comparisons between states more diffi- cult in the post-ACA era. Finally, our findings are limited by the age of our data. We restricted our analysis to 2004 and 2005, the latest years we had complete data available. However, we believe our analysis uses more re- cent data than similar studies analyzing CMS enrollment and CMS use.

Conclusion Many veterans engaged in care in the VA are also enrolled in Medicare and/or Medicaid, including a significant pro- portion of veterans under age 65. Like the general popula- tion, the rates of CMS enrollment are higher among HIV infected veterans. However, among veterans enrolled in both VA and CMS care, HIV-infected veterans have lower odds of non-VA hospitalization despite having greater ill- ness severity and more frequent hospitalizations than

uninfected veterans. The VA’s integrated model of care used to treat HIV/AIDS may explain why HIV-infected veterans were more likely to seek care within the VA. The impact of CMS use on veterans with HIV and

other complex medical conditions requires further inves- tigation. HIV-infected veterans have complicated med- ical histories and are likely to experience inefficient care and poor outcomes related to non-VA use. Research that provides evidence of the cost and health implications of CMS use may guide the VA in how aggressively to pur- sue and retain these patients in the VA system. Future research should also explore why veterans with

HIV were less likely than uninfected veterans to use non-VA care. If specific aspects of VA’s integrated care programs for veterans with HIV, such as intensive case management, are found to contribute to lower likelihood of non-VA admission, then this would inform strategies to limit non-VA use among other veteran populations at high risk from fragmented care, such as veterans with other major chronic diseases or illnesses. CMS enrollment is a valuable resource for veterans who

face higher copayments or live long distances from VA medical centers; however, among some veterans, CMS enrollment may lead to inefficient care and poor health outcomes. As health coverage is further expanded efforts should be made to ensure that additional coverage is reaching the populations that can benefit the most. The VA and federal government should shape their policies to incentivize use of a single health system and develop pro- cedures to ensure comprehensive exchange of information between health systems.

Abbreviations HIV: Human immunodeficiency virus; AIDS: Acquired immunodeficiency disease syndrome; VA: Veterans Administration; CMS: Center for Medicare & Medicaid Services; ACA: Affordable Care Act; VACS-VC: Veterans Aging Cohort Study – Virtual Cohort; FFS: Fee for service; ICU: Intensive care unit; HCC: Hierarchical condition category; 95% CI: 95% Confidence interval; OR: Odds ratio.

Competing interests The authors declare that they have no competing interests.

Authors’ contributions HC, JT, AJ, and MO conceived this study together and participated in its design. HC and JT conducted the data extraction. HC performed the statistical analyses with support from JT and MO. HC, JT, AJ, and MO drafted the manuscript. All authors read and approved the final manuscript.

Acknowledgements The work reported here was supported by The Veterans Aging Cohort Study, with funding from National Institute on Alcohol Abuse and Alcoholism (U10 AA 13566) and VHA Public Health Strategic Health Care Group, and housed at the West Haven VAMC. The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs.

Author details 1Yale School of Medicine, Yale University, 333 Cedar Street, New Haven, CT 06510, USA. 2Veterans Aging Cohort Study, VA Connecticut Healthcare System, 950 Campbell Avenue, West Haven, CT 06516, USA. 3Department of Internal

Chang et al. BMC Health Services Research (2015) 15:27 Page 9 of 9

Medicine, Yale School of Medicine, 330 Cedar St, Boardman 110, P.O. Box 208056, New Haven, CT 06520, USA. 4Department of Public Health, Yale School of Public Health, 60 College Street, P.O. Box 208034, New Haven, CT 06520, USA. 5VA Office of Rural Health (ORH), Midwest Rural Health Resource Center, Iowa City VAMC, 601 Highway 6 West (152), Iowa City, IA 52246, USA. 6Center for Comprehensive Access and Delivery Research and Evaluation (CADRE) at the Iowa City VA Medical Center, Mailstop 152, Iowa City VAMC, Iowa City, IA 52246, USA. 7Department of Internal Medicine, University of Iowa Carver College of Medicine, 200 Hawkins Drive, Iowa City, IA 52242, USA.

Received: 4 June 2014 Accepted: 6 January 2015

References 1. Haley JK, Kenney GM. Uninsured veterans and family members: State and

National Estimates of expanded medicaid eligibility under the ACA. In: Timely analysis of immediate health policy issues. Urban Institute; 2013.

2. Trivedi AN, Grebla RC, Jiang L, Yoon J, Mor V, Kizer KW. Duplicate federal payments for dual enrollees in Medicare advantage plans and the Veterans affairs health care system. JAMA. 2012;308(1):67–72.

3. Tarlov E, Lee TA, Weichle TW, Durazo-Arvizu R, Zhang Q, Perrin R, et al. Re- duced overall and event-free survival among colon cancer patients using dual system care. Cancer Epidemiol Biomarkers Prev. 2012;21(12):2231–41.

4. Wolinsky FD, An H, Liu L, Miller TR, Rosenthal GE. Exploring the association of dual use of the VHA and Medicare with mortality: separating the contributions of inpatient and outpatient services. BMC Health Serv Res. 2007;7:70.

5. Wolinsky FD, Miller TR, An H, Brezinski PR, Vaughn TE, Rosenthal GE. Dual use of Medicare and the Veterans Health Administration: are there adverse health outcomes? BMC Health Serv Res. 2006;6:131.

6. Helmer D, Sambamoorthi U, Shen Y, Tseng CL, Rajan M, Tiwari A, et al. Opting out of an integrated healthcare system: dual-system use is associated with poorer glycemic control in veterans with diabetes. Prim Care Diabetes. 2008;2(2):73–80.

7. Hynes DM, Koelling K, Stroupe K, Arnold N, Mallin K, Sohn MW, et al. Veterans' access to and use of Medicare and Veterans Affairs health care. Med Care. 2007;45(3):214–23.

8. Humensky J, Carretta H, De Groot K, Brown MM, Tarlov E, Hynes DM. Service utilization of veterans dually eligible for VA and medicare fee-for-service: 1999- 2004. Medicare Medicaid Res Rev. 2012;2(3). doi:10.5600/mmrr.002.03.a06.

9. Liu CF, Manning WG, Burgess JF, Sharp N, Perkins M, Maciejewski ML. Reliance on Veterans Affairs outpatient care by Medicare-eligible veterans. Med Care. 2011;49(10):911–7.

10. Medicare and HIV/AIDS: fact sheet. In: the Henry J. Kaiser family foundation 2009. Last accessed 6 October 2014. http://kaiserfamilyfoundation.files. wordpress.com/2013/01/7171_04.pdf.

11. Medicaid and HIV/AIDS: a national analysis. In: The Henry J. Kaiser family foundation October 2011. Last accessed 6 October 2014. http://kff.org/ hivaids/report/medicaid-and-hiv-a-national-analysis/.

12. Womack JA, Goulet JL, Gibert C, Brandt CA, Skanderson M, Gulanski B, et al. Physiologic frailty and fragility fracture in HIV-infected male veterans. Clin Infect Dis. 2013;56(10):1498–504.

13. Justice AC, Braithwaite RS. Lessons learned from the first wave of aging with HIV. AIDS. 2012;26 Suppl 1:S11–8.

14. Hoang T, Goetz MB, Yano EM, Rossman B, Anaya HD, Knapp H, et al. The impact of integrated HIV care on patient health outcomes. Med Care. 2009;47(5):560–7.

15. Yano EM, Asch SM, Phillips B, Anaya H, Bowman C, Chang S, et al. Organization and management of care for military veterans with human immunodeficiency virus/acquired immunodeficiency syndrome in Department of Veterans Affairs Medical Centers. Mil Med. 2005;170(11):952–9.

16. The State of Care for Veterans with HIV/AIDS: 2011 Summary Report, D.o.V. Affairs, Editor 2012. Last accessed 6 October 2014. http://www.hiv.va.gov/ pdf/VA2011-HIVSummaryRpt.pdf.

17. Justice AC, Dombrowski E, Conigliaro J, Fultz SL, Gibson D, Madenwald T, et al. Veterans Aging Cohort Study (VACS): overview and description. Med Care. 2006;44(8 Suppl 2):S13–24.

18. Fultz SL, Skanderson M, Mole LA, Gandhi N, Bryant K, Crystal S, et al. Development and verification of a “virtual” cohort using the National VA Health Information System. Med Care. 2006;44(8 Suppl 2):S25–30.

19. Bliss RL, Katz JN, Wright EA, Losina E. Estimating proximity to care: are straight line and zipcode centroid distances acceptable proxy measures? Med Care. 2012;50(1):99–106.

20. Evans MA. Evaluation of the CMS-HCC Risk Adjustment Model, C.f.M.M. Services, Editor. 2011.

21. Shen Y, Hendricks A, Wang F, Kazis LE. VHA enrollees’ health care coverage and use of care. Med Care Res Rev. 2003;60(2):253–67.

22. Petersen LA, Byrne MM, Daw CN, Hasche J, Reis B, Pietz K. Relationship between clinical conditions and use of Veterans Affairs health care among Medicare-enrolled veterans. Health Serv Res. 2010;45(3):762–91.

23. Shen Y, Findley PA, Maney M, Pogach L, Crystal S, Rajan M, et al. Department of Veterans Affairs-Medicare dual beneficiaries with stroke: where do they get care? J Rehabil Res Dev. 2008;45(1):43–5.

Submit your next manuscript to BioMed Central and take full advantage of:

• Convenient online submission

• Thorough peer review

• No space constraints or color figure charges

• Immediate publication on acceptance

• Inclusion in PubMed, CAS, Scopus and Google Scholar

• Research which is freely available for redistribution

Submit your manuscript at www.biomedcentral.com/submit