Veterans receiving a second course of cognitive processing therapy or prolonged exposure therapy: is it better to switch or stay the same?

Cognitive processing therapy (CPT) and prolonged exposure therapy (PE) are effective psychotherapies for post-traumatic stress disorder (PTSD). However, these treatments also have high rates of dropout and non-response. Therefore, patients may need a second course of treatment. We compared outcomes for patients who switched between CPT/PE and those who repeated CPT/PE during a second course of treatment. We collected data from Iraq and Afghanistan war veterans (n = 2,958) who received a second course of CPT/PE in the Veterans Health Administration from 2001 to 2017 and had symptom outcomes (PTSD checklist; PCL). We measured the association between treatment sequence and change in PCL score over the second course of treatment using hierarchical Bayesian regression, adjusted for sociodemographic and clinical characteristics. All treatment sequences showed a significant reduction in PCL score over time (ß = -4.80; HDI95: -5.74, -3.86). Veterans who switched from CPT to PE had modestly greater PCL reductions during the second course than those who repeated CPT. However, no significant difference in PCL change during the second course was observed between veterans who repeated PE and those who switched from PE to CPT. Veterans participating in a second course of CPT/PE can benefit, and switching treatment may be slightly more beneficial following CPT.

Association of Secure Messaging with Primary Care In-Person and Telephone Visits Among Veterans: a Matched Difference-in-Difference Analysis.

BACKGROUND: Secure messaging (SM) between patients and primary care teams has expanded care access but may impact other clinical encounters. OBJECTIVE: To study associations between SM use and primary care in-person and telephone visits in the Veterans Health Administration (VHA). DESIGN: The SM feature of VHA's patient portal, MyHealtheVet, supports asynchronous communication between patients and primary care teams. To study the impact of SM on in-person and telephone visits, two analyses were performed: (1) a retrospective pre-/post-analysis comparing changes after initiating SM use and (2) a difference-in-difference comparison among SM users and non-users 1 year before and after index SM use. Matching to non-users was by primary care team, demographics, and predicted propensity of SM use by Nosos comorbidity score and drive time to clinic. PATIENTS: In 2016, 154,053 Veterans initiated SM from all primary care patients (N = 5,891,893); 25,683 were propensity-matched to controls (N = 49,266) from the same primary care team not using SM. MAIN MEASURES: Primary care provider in-person visits and telephone contacts between patients and their primary care team were assessed 1 year prior and post index SM. KEY RESULTS: Overall, primary care in-person visits decreased 13.3% (p < 0.0001); telephone visits increased 13.5% (p < 0.0001). In the matched analysis, in-person primary care visits decreased by 16.0% (p < 0.0001) by SM users and 9.9% (p < 0.0001) among controls, resulting in a across-group decrease of 6.1% in-person visits after SM initiation. Telephone visits increased by 11.0% (p < 0.0001) for SM users and 4.5% for controls (p < 0.0001) resulting in an across-group increase of 6.5% telephone visits after SM initiation. CONCLUSIONS: Use of SM was associated with decreased in-person visits and increased telephone visits. This may improve clinic appointment availability, while increasing time commitments for providers for non-traditional forms of access.

Events Associated With Changes in Reliance on the Veterans Health Administration Among Medicare-eligible Veterans.

OBJECTIVES: We can learn something about how Veterans value the Veterans Health Administration (VHA) versus community providers by observing Veterans' choices between VHA and Medicare providers after they turn 65. For a cohort of Veterans who were newly age-eligible for Medicare, we estimated the change in VHA reliance (VHA outpatient visits divided by total VHA and Medicare visits) associated with specific events: receiving a life-threatening diagnosis, having a Medicare-paid hospitalization, or moving further from the VHA. RESEARCH DESIGN: A longitudinal cohort study of VHA and Medicare administrative data. SUBJECTS: A total of 5932 VHA users who completed a health survey in 1999 and became age-eligible for Medicare from 1998 to 2000 were followed through 2016. PRINCIPAL FINDINGS: More Veterans chose to rely on the VHA than Medicare (64% vs. 36.%). For a VHA-reliant Veteran, a Medicare-paid hospital stay was associated with a decrease of 7.8 percentage points (pps) (P<0.001) in VHA reliance in the subsequent 12 months, but by 36 months reliance increased to near prehospitalization levels (-1.5 pps; P=0.138). Moving further from the VHA, or receiving a diagnosis of cancer, heart failure, or renal failure had no significant association with subsequent VHA reliance; however, a diagnosis of dementia was associated with a decrease in VHA reliance (-8.6 pps; P=0.026). CONCLUSIONS: A significant majority of newly Medicare-eligible VHA users voted with their feet in favor of sustaining the VHA as a provider of comprehensive medical care for Veterans. These VHA-reliant Veterans maintained their reliance even after receiving a life-threatening diagnosis, and after experiencing Medicare-provided hospital care.

The Burden of Mental Illness Among Veterans: Use of VHA Health Care Services by Those With Service-connected Conditions.

BACKGROUND: Little is known about how Veterans with service-connected conditions use health care provided by the Veterans Health Administration (VHA). OBJECTIVES: To ascertain what proportion of Veterans with service-connected conditions used VHA health care and whether it varied according to type of condition, combined disability rating, age, sex, military rank, or other characteristics and whether there were differences in receipt of inpatient and outpatient care. RESEARCH DESIGN: Cross-sectional analysis of administrative benefits and claims data for 2015 and 2016. SUBJECTS: In total, 4,029,672 Veterans who had an active award status for service-connected conditions in October 2016. MEASURES: Independent variables included age, sex, military rank, service branch, combined disability rating, Agent Orange exposure, and type of service-connected condition. The key-dependent variable was VHA health care use including specific types of health care utilization such as inpatient and outpatient services. RESULTS: In total, 52% of those with service-connected conditions used VHA health care. Type of condition and disability rating were associated with use. Over 65% of those with major depression, posttraumatic stress disorder (PTSD), Agent Orange exposure, or diabetes used VHA health care, as did 76% of those with a 100% rating. Almost one third of users of VHA health care were compensated for PTSD. In general, both inpatient and outpatient mental health services were frequently used by Veterans with service-connected mental health conditions. CONCLUSIONS: Veterans with service-connected conditions, particularly those with diabetes or mental illness such as depression or PTSD, depend heavily upon VHA for health care, including mental health services.

Association between local area unemployment rates and use of Veterans Affairs outpatient health services.

BACKGROUND: Prior research indicates that federal spending on Medicare, Medicaid, and other government health programs accelerated during the Great Recession. OBJECTIVES: To examine whether local unemployment was associated with utilization of Veterans Affairs Health Care System (VA) primary care, specialty care, and mental health services during 2004-2012. RESEARCH DESIGN: We analyzed utilization of VA health services at the clinic level using fixed-effects negative binomial models. We stratified analyses by veterans' copayment status (exempt and nonexempt) and age (under 65 and 65+) to account for differences in VA utilization because of Medicare eligibility. SUBJECTS: A total of 11,041,855 veterans assigned to 892 clinics identified in the VA Primary Care Management Module, representing nearly all veterans receiving primary care from VA, were included. MEASURES: Clinic-level utilization was calculated quarterly as the total number of visits for patients assigned to a clinic. Local area unemployment rates were defined as quarterly unemployment rates within VA geographical planning sectors. RESULTS: Higher local unemployment was associated with greater use of VA care in all categories among veterans exempt from copayments. The association between local unemployment and utilization differed by age group among veterans subject to copayments. Higher local unemployment was associated with lower use of primary and specialty care among Medicare-eligible veterans aged 65+, but greater use of primary care among veterans under age 65. CONCLUSIONS: Our findings highlight the importance of the state of the economy in interpreting and forecasting demand for government health programs including VA, particularly during periods focused on deficit reduction.

Patient-centered medical home implementation and primary care provider turnover.

BACKGROUND: The Veterans Health Administration (VHA) began implementing a patient-centered medical home (PCMH) model of care delivery in April 2010 through its Patient Aligned Care Team (PACT) initiative. PACT represents a substantial system reengineering of VHA primary care and its potential effect on primary care provider (PCP) turnover is an important but unexplored relationship. This study examined the association between a system-wide PCMH implementation and PCP turnover. METHODS: This was a retrospective, longitudinal study of VHA-employed PCPs spanning 29 calendar quarters before PACT and eight quarters of PACT implementation. PCP employment periods were identified from administrative data and turnover was defined by an indicator on the last quarter of each uncensored period. An interrupted time series model was used to estimate the association between PACT and turnover, adjusting for secular trend and seasonality, provider and job characteristics, and local unemployment. We calculated average marginal effects (AME), which reflected the change in turnover probability associated with PACT implementation. RESULTS: The quarterly rate of PCP turnover was 3.06% before PACT and 3.38% after initiation of PACT. In adjusted analysis, PACT was associated with a modest increase in turnover (AME=4.0 additional PCPs per 1000 PCPs per quarter, P=0.004). Models with interaction terms suggested that the PACT-related change in turnover was increasing in provider age and experience. CONCLUSIONS: PACT was associated with a modest increase in PCP turnover, concentrated among older and more experienced providers, during initial implementation. Our findings suggest that policymakers should evaluate potential workforce effects when implementing PCMH.

Validation of the EDDS-5 self-report survey against the SCID-5 diagnostic interview in US veterans.

The aim of our study was to validate the Eating Disorder Diagnostic Scale (EDDS-5) updated for the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) with a diverse veteran population against a clinician-administered interview based on the Structured Clinical Interview for DSM-5 (SCID-5). Our sample included 343 veterans, 18-75 years, recruited April 2019 to December 2022 who completed the EDDS-5 as well as other eating disorder and mental health measures. A subsample of these veterans received clinical interviews (n = 166), which were used to validate the EDDS-5. We found that despite multiple proposed modifications, the EDDS-5 performed poorly at correctly identifying diverse veterans who were diagnosed as having eating disorders through clinician-administered interviews. The sensitivity was very low, indicating that using the EDDS-5 did not identify many true positives and may also over diagnose those without true eating disorders. The EDDS-5 may not be the best for screening or diagnostic purposes among diverse samples like veterans.

Advancing health equity by understanding race disparities and other factors associated with PTSD symptom improvement following evidence-based psychotherapy.

Several studies found that Black veterans demonstrate less posttraumatic stress disorder (PTSD) symptom improvement than White veterans following PTSD evidence-based psychotherapies (EBPs). We aimed to understand this disparity among veterans receiving EBPs by modeling race with demographic, clinical, and service utilization factors. Using electronic health records, we employed a cohort study of Iraq and Afghanistan War Veterans who initiated PTSD EBP treatment and completed > 2 PTSD symptom measures (N = 21,751). Using hierarchical Bayesian logistic regressions, we modeled the probability of PTSD symptom improvement. Black race was associated with less PTSD improvement (mean posterior odds ratio [MPOR] = 0.92; 95 % plausibility interval [PI] = 0.84, 1.0), as was group therapy (MPOR = 0.67; 95 % PI = 0.62, 0.73). Factors associated with greatest improvement included prolonged exposure (MPOR = 1.35; 95 % PI = 1.25, 1.45) and treatment density (MPOR = 1.40; 95 % PI = 1.36, 1.45). On average, Black veterans evidenced PTSD EBP improvement disparities. Clinical and utilization did not fully account for these disparities, although disproportionate representation of Black veterans in group CPT may explain some of these differences. Understanding experiences such as race-based trauma and chronic racism and discrimination is critical to provide Black veterans with the most effective PTSD care.

Trajectories of kidney function decline in the 2 years before initiation of long-term dialysis.

BACKGROUND: Little is known about patterns of kidney function decline leading up to the initiation of long-term dialysis. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: 5,606 Veterans Affairs patients who initiated long-term dialysis in 2001-2003. PREDICTOR: Trajectory of estimated glomerular filtration rate (eGFR) during the 2-year period before initiation of long-term dialysis. OUTCOMES & MEASUREMENTS: Patient characteristics and care practices before and at the time of dialysis initiation and survival after initiation. RESULTS: We identified 4 distinct trajectories of eGFR during the 2-year period before dialysis initiation: 62.8% of patients had persistently low level of eGFR < 30 mL/min/1.73 m2 (mean eGFR slope, 7.7 ± 4.7 [SD] mL/min/1.73 m2 per year), 24.6% had progressive loss of eGFR from levels of approximately 30-59 ml/min/1.73 m2 (mean eGFR slope, 16.3 ± 7.6 mL/min/1.73 m2 per year), 9.5% had accelerated loss of eGFR from levels > 60 mL/min/1.73 m2 (mean eGFR slope, 32.3 ± 13.4 mL/min/1.73 m2 per year), and 3.1% experienced catastrophic loss of eGFR from levels > 60 mL/min/1.73 m2 within 6 months or less. Patients with steeper eGFR trajectories were more likely to have been hospitalized and have an inpatient diagnosis of acute kidney injury. They were less likely to have received recommended predialysis care and had a higher risk of death in the first year after dialysis initiation. CONCLUSIONS: There is substantial heterogeneity in patterns of kidney function loss leading up to the initiation of long-term dialysis perhaps calling for a more flexible approach toward preparing for end-stage renal disease.

Associations between the Veterans Health Administration's Life-Sustaining Treatment Decisions Initiative and Quality of Care at the End of Life.

Background: In 2017, Veterans Health Administration (VHA) implemented the Life-Sustaining Treatment Decisions Initiative (LSTDI) to promote goals-of-care conversations (GoCC) between seriously ill patients and their practitioners, to document patient preferences in the electronic health record, and to provide care consistent with patients' goals. Objectives: We evaluated the associations between this initiative and quality of care in the last month of life (i.e., emergency department/intensive care unit [ED/ICU] visits and hospice consultations). Design: We conducted patient-level propensity score analyses to evaluate the associations between LSTDI and care utilization in the last 30 days of life. The primary exposure was a three-level factor: no GoCC (reference group), GoCC with Full Code, and GoCC with do not resuscitate (DNR). The outcomes were ED/ICU visits and hospice consultations within 30 days of death. Setting/Subjects: A total of 44,320 patients receiving care in Veterans (VA), who were older than 18, and who died and had a completed encounter within 24 months of death in a VA primary care, mental health, or medical specialty between January 2017 and December 2019. Results: Patients with a documented GoCC and DNR code status had decreased risk of ED visits (odds ratio [OR] = 0.6, 89% credible intervals [CI] = [0.57-0.64]) and ICU visits (OR = 0.49, 89% CI = [0.45-0.53]), and increased rates of hospice visits (ß = 2.18, 89% CI = [2.11-2.26]) compared with patients with no GoCC. Conclusion: The LSTDI had a positive impact by eliciting and documenting patient preferences for care at the end of life and quality of care in the last month of life. We observed associations between care preferences and ED/ICU visits and hospice consultations within 30 days of death. Further research should address the associations between LSTDI and use of palliative care, and outcomes associated with limits to specific life-sustaining treatments such as mechanical ventilation, artificial nutrition, and hydration.

An Exploratory Study of Goals of Care Conversations Initiated with Seriously Ill Veterans in the Emergency Room.

Background: Emergency department (ED) visits are common for older patients with chronic, life-limiting illnesses and may offer a valuable opportunity for clinicians to initiate proactive goals of care conversations (GoCC) to ensure end-of-life care that aligns with the patients' values, goals, and preferences. Objectives: The purpose of this study is to assess whether GoCC are occurring with patients in Department of Veteran Affairs (VA) EDs, to characterize these patients' goals of care and life-sustaining treatment (LST) decisions, and to examine the extent to which palliative or hospice consultations occur following the ED visit. Design: We conducted a cross-sectional retrospective study using health record data. Settings/Subjects: A total of 10,780 patients receiving care in VA, whose first GoCC occurred during an ED visit. Results: Of the patients in the study, approximately half were at least 70 years of age, three-quarters were white, and half had multiple serious disease comorbidities. The percentage of patients who desired cardiopulmonary resuscitation was lower among the highest risk (i.e., of hospitalization and death) patients (64% vs. 51%). The percentage of patients wanting other LSTs (e.g., mechanical ventilation) was higher among the lowest risk patients; and the percentage of patients requesting limits to LSTs was highest among higher risk patients. Eighteen percent of patients had a palliative or hospice care consult within three months of their ED visit. Conclusions: In this study, we verified that GoCC are being initiated in the ED with Veterans at differing stages in their illness trajectory and that higher proportions of higher risk patients preferred to limit LSTs.

Development of a novel metric of timely care access to primary care services.

OBJECTIVE: To develop a model for identifying clinic performance at fulfilling next-day and walk-in requests after adjusting for patient demographics and risk. DATA SOURCE: Using Department of Veterans Affairs (VA) administrative data from 160 VA primary care clinics from 2014 to 2017. STUDY DESIGN: Using a retrospective cohort design, we applied Bayesian hierarchical regression models to predict provision of timely care, with clinic-level random intercept and slope while adjusting for patient demographics and risk status. Timely care was defined as the provision of an appointment within 48 hours of any patient requesting the clinic's next available appointment or walking in to receive care. DATA COLLECTION/EXTRACTION METHODS: We extracted 1 841 210 timely care requests from 613 263 patients. PRINCIPAL FINDINGS: Across 160 primary care clinics, requests for timely care were fulfilled 86 percent of the time (range 83 percent-88 percent). Our model of timely care fit the data well, with a Bayesian R2 of .8. Over the four years of observation, we identified 25 clinics (16 percent) that were either struggling or excelling at providing timely care. CONCLUSION: Statistical models of timely care allow for identification of clinics in need of improvement after adjusting for patient demographics and risk status. VA primary care clinics fulfilled 86 percent of timely care requests.

A Resampling Based Grid Search Method to Improve Reliability and Robustness of Mixture-Item Response Theory Models of Multimorbid High-Risk Patients.

There are many statistics available to the applied statistician for assessing model fit and even more methods for assessing internal and external validity. We detail a useful approach using a grid search technique that balances the internal model consistency with generalizability and can be used with models that naturally lend themselves to multiple assessment techniques. Our method relies on resampling and a simple grid search method over 3 commonly used statistics that are simple to calculate. We apply this method in a latent traits framework using a mixture Item Response Theory (MIXIRT) model of common chronic health conditions. Model fit is assessed using Akaike's Information Criteria (AIC), latent class similarity is measured with the Variance of Information (VI), and the consistency of condition complexity and prevalence across latent classes is compared using Kendall's τ rank order statistic. From two patient cohorts at high risk for hospitalization in 2014 and 2018, we generated 19 MIXIRT models (allowing 2-20 latent classes) on 21 common comorbid conditions identified via healthcare encounter diagnosis codes. We ran these models on 100 bootstrap samples of size 10% for each cohort. Among the resulting models, combined AIC and VI statistics identified 5-7 latent classes, but the rank order correlation of condition complexity revealed that only the 5 class solutions had consistent condition complexity. The 5 class solutions were combined to produce a single parsimonious MIXIRT solution that balanced clinical significance with model fit, cluster similarity, and consistency of condition complexity.

Association of High-Cost Health Care Utilization With Longitudinal Changes in Patient-Centered Medical Home Implementation.

Importance: In 2010, the US Veterans Health Administration (VHA) implemented one of the largest patient-centered medical home (PCMH) models in the United States, the Patient Aligned Care Team initiative. Early evaluations demonstrated promising associations with improved patient outcomes, but limited evidence exists on the longitudinal association of PCMH implementation with changes in health care utilization. Objective: To determine whether a change in PCMH implementation is associated with changes in emergency department (ED) visits, hospitalizations for ambulatory care-sensitive conditions (ACSCs), or all-cause hospitalizations. Design, Setting, and Participants: This cohort study used national patient-level data from the VHA and Centers for Medicare & Medicaid Services between October 1, 2012, and September 30, 2015. A total of 1 650 976 patients from 897 included clinics were divided into 2 cohorts: patients younger than 65 years who received primary care at VHA sites affiliated with a VHA ED and patients 65 years or older who were enrolled in both VHA and Medicare services. Exposures: Clinics were categorized on improvement or decline in PCMH implementation based on their Patient Aligned Care Team implementation progress index (Pi2) score. Main Outcomes and Measures: Change in the number of ED visits, ACSC hospitalizations, and all-cause hospitalizations among patients at each clinic site. Results: The study included a total of 1 650 976 patients, of whom 581 167 (35.20%) were younger than 65 years (mean [SD] age, 49.03 [10.28] years; 495 247 [85.22%] men) and 1 069 809 (64.80%) were 65 years or older (mean [SD] age, 74.64 [7.41] years; 1 050 110 [98.16%] men). Among patients younger than 65 years, there were fewer ED visits among patients seen at clinics that had improved PCMH implementation (110.8 fewer visits per 1000 patients; P < .001) and clinics that had somewhat worse implementation (69.0 fewer visits per 1000 patients; P < .001) compared with clinics that had no change in Pi2 score. There were no associations of change in Pi2 scores with all-cause hospitalizations or ACSC hospitalizations among patients younger than 65 years. In patients 65 years or older, those seen at clinics that had somewhat worse PCMH implementation experienced fewer ED visits (20.1 fewer visits per 1000 patients; P = .002) and all-cause hospitalizations (12.4 fewer hospitalizations per 1000 patients; P = .007) compared with clinics with no change in Pi2 score. There was no association between change in Pi2 score with ACSC hospitalizations among patients 65 years or older. Conclusions and Relevance: There were no consistent associations of change in Pi2 score with high-cost health care utilization. This finding highlights the key differences in measuring PCMH implementation longitudinally compared with cross-sectional study designs.

Developing an Algorithm for Combining Race and Ethnicity Data Sources in the Veterans Health Administration.

INTRODUCTION: Racial/ethnic disparities exist in the Veterans Health Administration (VHA), despite financial barriers to care being largely mitigated and Veterans Administration's (VA) organizational commitment to health equity. Accurately identifying minority veterans is critical to monitoring progress toward equity as the VHA treats an increasingly racially and ethnically diverse veteran population. Although the VHA's completeness of race and ethnicity data is generally better than its public sector and private counterparts, the accuracy of the race and ethnicity in the various databases available to VHA is variable, as is the accuracy in identifying specific minority groups. The purpose of this article was to develop an algorithm for constructing race and ethnicity variables from data sources available to VHA researchers, to present demographic differences cross the data sources, and to apply the algorithm to one study year. MATERIALS AND METHODS: We used existing VHA survey data from the Survey of Healthcare Experiences of Patients (SHEP) and three commonly used administrative databases from 2003 to 2015: the VA Corporate Data Warehouse (CDW), VA Defense Identity Repository (VADIR), and Medicare. Using measures of agreement such as sensitivity, specificity, positive and negative predictive values, and Cohen kappa, we compared self-reported race and ethnicity from the SHEP and each of the other data sources. Based on these results, we propose an algorithm for combining data on race and ethnicity from these datasets. We included VHA patients who completed a SHEP and had race/ethnicity recorded in CDW, VADIR, and/or Medicare. RESULTS: Agreement between SHEP and other sources was high for Whites and Blacks and substantially lower for other minority groups. The CDW demonstrated better agreement than VADIR or Medicare. CONCLUSIONS: We developed an algorithm of data source precedence in the VHA that improves the accuracy of the identification of historically under-identified minorities: (1) SHEP, (2) CDW, (3) Department of Defense's VADIR, and (4) Medicare.

The Association Between Neighborhood Socioeconomic and Housing Characteristics with Hospitalization: Results of a National Study of Veterans.

BACKGROUND: Social determinants of health (SDOH) have an inextricable impact on health. If remained unaddressed, poor SDOH can contribute to increased health care utilization and costs. We aimed to determine if geographically derived neighborhood level SDOH had an impact on hospitalization rates of patients receiving care at the Veterans Health Administration's (VHA) primary care clinics. METHODS: In a 1-year observational cohort of veterans enrolled in VHA's primary care medical home program during 2015, we abstracted data on individual veterans (age, sex, race, Gagne comorbidity score) from the VHA Corporate Data Warehouse and linked those data to data on neighborhood socioeconomic status (NSES) and housing characteristics from the US Census Bureau on census tract level. We used generalized estimating equation modeling and spatial-based analysis to assess the potential impact of patient-level demographic and clinical factors, NSES, and local housing stock (ie, housing instability, home vacancy rate, percentage of houses with no plumbing, and percentage of houses with no heating) on hospitalization. We defined hospitalization as an overnight stay in a VHA hospital only and reported the risk of hospitalization for veterans enrolled in the VHA's primary care medical home clinics, both across the nation and within 1 specific case study region of the country: King County, WA. RESULTS: Nationally, 6.63% of our veteran population was hospitalized within the VHA system. After accounting for patient-level characteristics, veterans residing in census tracts with a higher NSES index had decreased odds of hospitalization. After controlling all other factors, veterans residing in census tracts with higher percentage of houses without heating had 9% (Odds Ratio, 1.09%; 95% CI, 1.04 to 1.14) increase in the likelihood of hospitalization in our regional Washington State analysis, though not our national level analyses. CONCLUSIONS: Our results present the impact of neighborhood characteristics such as NSES and lack of proper heating system on the likelihood of hospitalization. The application of placed-based data at the geographic level is a powerful tool for identification of patients at high risk of health care utilization.

Reliance on Medicare Providers by Veterans after Becoming Age-Eligible for Medicare is Associated with the Use of More Outpatient Services.

OBJECTIVE: To estimate the effect of Medicare use on the receipt of outpatient services from 2001 through 2015 for a cohort of Veterans Administration (VA) users who became age-eligible for Medicare in 1998-2000. DATA SOURCES/STUDY SETTING: VA administrative data linked with Medicare claims for veterans who participated in the 1999 Large Health Survey of Enrolled Veterans. STUDY DESIGN: We coded each veteran as VA-reliant or Medicare-reliant based on the number of visits in each system and compared the health and social risk factors between VA-reliant and Medicare-reliant veterans. We used bivariate probit and instrumental variables models to estimate the association between a veteran's reliance on Medicare and the receipt of outpatient procedures in Medicare and the VA. PRINCIPAL FINDINGS: Veterans who chose to rely on the VA (n = 4,317) had substantially worse social and health risk factors than Medicare-reliant veterans (n = 2,567). Medicare reliance was associated with greater use of outpatient services for 24 of the 28 types of services considered. Instrumental variable estimates found significant effects of Medicare reliance on receipt of advanced imaging and cardiovascular testing. CONCLUSIONS: Expanded access to fee-for-service care in the community may be expensive, while the VA will likely continue to care for the most vulnerable veterans.

Fee-for-Service Medicare-Enrolled Elderly Veterans Are Increasingly Voting with Their Feet to Use More VA and Less Medicare, 2003-2014.

OBJECTIVE: To examine the long-term reliance on outpatient care at the population (i.e., system) level among fee-for-service Medicare-enrolled elderly veterans in the Department of Veterans Affairs (VA) health care system and Medicare from 2003 to 2014. DATA SOURCES/STUDY SETTING: We analyzed a 5 percent random sample, stratified by facility, age, gender, and race, of Medicare-enrolled veterans enrolled in a VA primary care panel using VA administrative data and Medicare claims. STUDY DESIGN: We performed a repeated cross-sectional analysis over 48 quarters. VA reliance was defined at the system level as the proportion of total visits (VA + Medicare) that occurred in VA. We examined four visit types and seven high-volume medical subspecialties. We applied direct standardization adjusting for age, gender, and race using the 2010 population distribution of Medicare-enrolled veterans. PRINCIPAL FINDINGS: Over the 12-year period, VA provided the vast majority of mental health care. Conversely, veterans received slightly more than half of their primary care and most of their specialty care, surgical care, and seven high-volume medical subspecialties through Medicare. However, reliance on VA outpatient care steadily increased over time for all categories of care. CONCLUSIONS: Despite the controversies about VA access to care, Medicare-enrolled veterans, who have a choice of using VA or Medicare providers, appear to increase their use of VA care prior to the Choice Act.