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.

Behavioral Health Integration in Community Health Centers and Emergency Department Use.

Medicaid enrollees with behavioral health disorders often experience fragmented care, leading to high rates of preventable use of emergency departments (EDs). As part of its Medicaid Transformation Program, the Washington Health Care Authority partnered with regional accountable communities of health to collect data on behavioral health integration in community health centers. Clinics who participated in the integrated care demonstration received technical and financial support to increase capacity for integration. This column describes results from an analysis that linked clinic surveys to Medicaid claims to explore characteristics of highly integrated clinics and assess whether clinic capacity for behavioral health integration is associated with ED visit frequency.

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.

Patient-Centered Medical Home Implementation and Burnout Among VA Primary Care Employees.

Burnout is widespread throughout primary care and is associated with negative consequences for providers and patients. The relationship between the patient-centered medical home model and burnout remains unclear. Using survey data from 8135 and 7510 VA primary care employees in 2012 and 2013, respectively, we assessed whether clinic-level medical home implementation was independently associated with burnout prevalence and estimated whether burnout changed among this workforce from 2012 to 2013. Adjusting for differences in respondent and clinic characteristics, we found that burnout was common among primary care employees, increased by 3.9% from 2012 to 2013, and was not associated with the extent of medical home implementation.

The facilitators and barriers associated with implementation of a patient-centered medical home in VHA.

BACKGROUND: The patient-centered medical home (PCMH) is a team-based, comprehensive model of primary care. When effectively implemented, PCMH is associated with higher patient satisfaction, lower staff burnout, and lower hospitalization for ambulatory care-sensitive conditions. However, less is known about what factors contribute to (or hinder) PCMH implementation. We explored the associations of specific facilitators and barriers reported by primary care employees with a previously validated, clinic-level measure of PCMH implementation, the Patient Aligned Care Team Implementation Progress Index (Pi(2)). METHODS: We used a 2012 survey of primary care employees in the Veterans Health Administration to perform cross-sectional, respondent-level multinomial regressions. The dependent variable was the Pi(2) categorized as high implementation (top decile, 54 clinics, 235 respondents), medium implementation (middle eight deciles, 547 clinics, 4537 respondents), and low implementation (lowest decile, 42 clinics, 297 respondents) among primary care clinics. The independent variables were ordinal survey items rating 19 barriers to patient-centered care and 10 facilitators of PCMH implementation. For facilitators, we explored clinic Pi(2) score decile both as a function of respondent-reported availability of facilitators and of rating of facilitator helpfulness. RESULTS: The availability of five facilitators was associated with higher odds of a respondent's clinic's Pi(2) scores being in the highest versus lowest decile: teamlet huddles (OR = 3.91), measurement tools (OR = 3.47), regular team meetings (OR = 2.88), information systems (OR = 2.42), and disease registries (OR = 2.01). The helpfulness of four facilitators was associated with higher odds of a respondent's clinic's Pi(2) scores being in the highest versus lowest decile. Six barriers were associated with significantly higher odds of a respondent's clinic's Pi(2) scores being in the lowest versus highest decile, with the strongest associations for the difficulty recruiting and retaining providers (OR = 2.37) and non-provider clinicians (OR = 2.17). Results for medium versus low Pi(2) score clinics were similar, with fewer, smaller significant associations, all in the expected direction. CONCLUSIONS: A number of specific barriers and facilitators were associated with PCMH implementation, notably recruitment and retention of clinicians, team huddles, and local education. These findings can guide future research, and may help healthcare policy makers and leaders decide where to focus attention and limited resources.

Local Area Unemployment and the Demand for Inpatient Care Among Veterans Affairs Enrollees.

Prior research examining the relationship between economic conditions and health service demand has focused primarily on outpatient use. This study examines whether local area unemployment, as an indicator of economic conditions, was associated with use of inpatient care, which is theoretically less subject to discretionary use. Using a random sample of 131,603 patients dually enrolled in the Veterans Affairs (VA) Health System and fee-for-service Medicare, we measured VA, Medicare, and total (VA and Medicare) hospitalizations. Overall, local unemployment was not associated with VA, Medicare, or total hospitalization probability. Among low-income veterans exempt from VA copayments, higher local unemployment was moderately associated with a lower probability of hospitalization through Medicare. For veterans subject to VA copayments, higher local unemployment was moderately associated with a higher likelihood of VA hospitalization. These results suggest inpatient use is less sensitive to the economy, although worse economic conditions slightly affected inpatient demand for select veterans.