Medical training program size and clinical staff productivity and turnover.

OBJECTIVE: The objective of this analysis was to evaluate the effect of resident program training size on clinician productivity and turnover in the Veterans Health Administration (VHA), the largest education and training platform for medical professionals in the United States. DATA SOURCES: We retrieved administrative data on training programs and training facilities from the VA Office of Academic Affiliations and the VHA Corporate Data Warehouse. Data on primary care physician shortage areas were retrieved from the Health Resources and Services Administration. STUDY DESIGN: We used a quasi-experimental instrumental variables 2SLS design and constructed an exogenous predicted training allocation treatment variable as a function of the total national training program allocation. The outcome was clinical staff productivity and turnover. Secondary analyses stratified results using Health Professional Shortage Areas data (HPSA). DATA COLLECTION/EXTRACTION METHODS: Data were obtained for a national dataset of 141 VHA medical facilities and 26 specialties that hosted training programs across 11 years from 2011 to 2021 (N = 132,177). PRINCIPAL FINDINGS: Instrumental variables results showed that on average, an increase of one training slot in a specialty leads to a decrease of 0.039 visits per standardized clinic day (p < 0.001) and a 0.02 percentage point increase in turnover (p < 0.001). The direction of this association varied by specialty: while psychiatry and psychology specialties saw a decline in productivity, fields such as primary care and cardiology experienced an increase in productivity. HPSA stratified results indicate that negative effects on productivity and turnover are driven by areas with little to no primary care physician shortage, whereas shortage areas experienced a small increase in productivity and no effect on turnover. CONCLUSIONS: This quasi-experimental evaluation indicates that resident training program size is associated with reduced productivity and increased turnover in specialties such as psychiatry and in facilities with high baseline productivity. However, in specialties like primary care and cardiology, as well as areas with shortages of primary care, larger training programs are associated with increased productivity.

Impact of Nurse Residency Program on Time-to-Fill Nurse Vacancies at the Veterans Health Administration.

BACKGROUND: The Department of Veterans Affairs (VA) offers a 1-year Post-Baccalaureate-Registered Nurse Residency (PB-RNR) Program. The impact of the PB-RNR program on local RN recruitment was unknown. OBJECTIVES: We aimed to evaluate the effect of the size of the PB-RNR program at a VA facility on its time-to-fill RN vacancies. PROJECT DESIGN: We used an instrumental variable approach with a 2-stage residual inclusion specification. SUBJECTS: We included RN filled vacancies in the VA that were posted nationwide between 2020 and 2021. MEASURES: Our independent variable was the facility-year level number of PB-RNR program allocations. The 3 binary outcomes were whether the RN vacancy was filled within 90, 60, or 30 days. RESULTS: An increase of one training allocation was significantly associated with a 5.60 percentage point (PP) (95% CI: 2.74-8.46) higher likelihood of filling a vacancy within 90 days, 7.34 PP (95% CI: 4.66-10.03) higher likelihood of filling a vacancy within 60 days, and 5.32 PP (95% CI: 3.18-7.46) higher likelihood of filling a vacancy within 30 days. The impact was significant in both 2020 and 2021 positions, and in facilities located in areas with lower social deprivation scores, higher-quality public schools, or with either no or partial primary care physician shortages. CONCLUSIONS: We found favorable impacts of the size of the PB-RNR program at a VA facility on filling RN vacancies.

Effect of mental health staffing inputs on initiation of care among recently separated Veterans.

OBJECTIVE: To estimate a causal relationship between mental health staffing and time to initiation of mental health care for new patients. DATA SOURCES AND STUDY SETTING: As the largest integrated health care delivery system in the United States, the Veterans Health Administration (VHA) provides a unique setting for isolating the effects of staffing on initiation of mental health care where demand is high and out-of-pocket costs are not a relevant confounder. We use data from the Department of Defense and VHA to obtain patient and facility characteristics and health care use. STUDY DESIGN: To isolate exogenous variation in mental health staffing, we used an instrumental variables approach-two-stage residual inclusion with a discrete time hazard model. Our outcome is time to initiation of mental health care after separation from active duty (first appointment) and our exposure is mental health staffing (standardized clinic time per 1000 VHA enrollees per pay period). DATA COLLECTION/EXTRACTION METHODS: Our cohort consists of all Veterans separating from active duty between July 2014 and September 2017, who were enrolled in the VHA, and had at least one diagnosis of post-traumatic stress disorder, major depressive disorder, and/or substance use disorder in the year prior to separation from active duty (N = 54,209). PRINCIPAL FINDINGS: An increase of 1 standard deviation in mental health staffing results in a higher likelihood of initiating mental health care (adjusted hazard ratio: 3.17, 95% confidence interval: 2.62, 3.84, p < 0.001). Models stratified by tertile of mental health staffing exhibit decreasing returns to scale. CONCLUSIONS: Increases in mental health staffing led to faster initiation of care and are especially beneficial in facilities where staffing is lower, although initiation of care appears capacity-limited everywhere.

Growth of community-based immunotherapy treatment in the Veterans Health Administration.

BACKGROUND: The MISSION and CHOICE Acts expanded the Veterans Health Administration's (VA) capacity to purchase immunotherapy services for VA patients from community-based providers. Our objective was to identify predictors of community-based immunotherapy treatment, and assess differences in cost and utilization across community treatment settings METHODS: We examined claims for 21,257 patients who started immunotherapy treatment between 2015 and 2020. We assessed growth in VA community-based immunotherapy care, predictors of community-based immunotherapy treatment using multivariable logistic regression based on patients' sociodemographic and clinical characteristics. We compared utilization and costs among those who received community-based immunotherapy services in hospital outpatient departments (HOPDs) versus physician office settings (POs). RESULTS: The proportion of community-based immunotherapy in the VA increased from 5.3% in 2015 to 32.1% in 2020, with total annual costs of immunotherapy growing from $6.1 million to $187 million. Older, married, and rural patients and those with more comorbidities were more likely than younger, single, or urban patients to be treated in the community. Black patients were more likely to be treated in the VA. Respiratory Cancer was the most common cancer type in both settings. Among community immunotherapy patients, we observed no meaningful differences in the number of units administered, the unit drug costs, or the cost per immunotherapy visit between POs and HOPDs. CONCLUSION: Drug costs did not differ widely across HOPDs and POs among VA patients who receive community-based immunotherapy.

What is the role of selection bias in quality comparisons between the Veterans Health Administration and community care? Example of elective hernia surgery.

OBJECTIVE: To investigate the relationship between community care (CC) treatment and a postoperative surgical complication in elective hernia surgery among Veterans using multiple approaches to control for potential selection bias. DATA SOURCES AND STUDY SETTING: Veterans Health Administration (VHA) data sources included Corporate Data Warehouse (VHA encounters and patient data), the Program Integrity Tool and Fee tables (CC encounters), the Planning Systems Support Group (geographic information), and the Paid file (VHA primary care providers). STUDY DESIGN: Prior works suggest patient outcomes are better in VHA than in CC settings; however, these studies may not have appropriately accounted for the selection of higher-risk cases into CC. We estimated (1) a naïve logistic regression model to calculate the effect of CC setting on the probability of a complication, controlling for facility fixed effects and patient and procedure characteristics, and (2) a 2-stage model using the hernia patient's primary care provider's 1-year prior CC referral rate as the instrument. DATA COLLECTION: We identified patients residing ≤40 miles from a VHA surgical facility with elective VHA or CC hernia surgery from 2018 to 2019. PRINCIPAL FINDINGS: Of 7991 hernia surgeries, 772 (9.7%) were in CC. The overall complication rate was 4.2%; 286/7219 (4.0%) among VHA surgeries versus 51/5772 (6.6%, p < 0.05) in CC. We observed a 2.8 percentage point increase in the probability of postoperative complication given CC surgery (95% confidence interval: 0.7, 4.8) in the naïve model. After accounting for the VHA provider's historical rate of CC referral, we no longer observed a relationship between surgery setting and risk of postoperative complication. CONCLUSIONS: After accounting for the selection of higher-risk patients to CC settings, we found no difference in hernia surgery postoperative complications between CC and VHA. Future VHA and non-VHA comparisons should account for unobserved as well as observed differences in patients seen in each setting.

Effect of mental health staffing inputs on suicide-related events.

OBJECTIVE: To estimate the effects of changes in Veterans Health Administration (VHA) mental health services staffing levels on suicide-related events among a cohort of Veterans. DATA SOURCES: Data were obtained from the VHA Corporate Data Warehouse, the Department of Defense and Veterans Administration Infrastructure for Clinical Intelligence, the VHA survey of enrollees, and customized VHA databases tracking suicide-related events. Geographic variables were obtained from the Area Health Resources Files and the Centers for Medicare and Medicaid Services. STUDY DESIGN: We used an instrumental variables (IV) design with a Heckman correction for non-random partial observability of the use of mental health services. The principal predictor was a measure of provider staffing per 10,000 enrollees. The outcome was the probability of a suicide-related event. DATA COLLECTION/EXTRACTION METHODS: Data were obtained for a cohort of Veterans who recently separated from active service. PRINCIPAL FINDINGS: From 2014 to 2018, the per-pay period probability of a suicide-related event among our cohort was 0.05%. We found that a 1% increase in mental health staffing led to a 1.6 percentage point reduction in suicide-related events. This was driven by the first tertile of staffing, suggesting diminishing returns to scale for mental health staffing. CONCLUSIONS: VHA facilities appear to be staffing-constrained when providing mental health care. Targeted increases in mental health staffing would be likely to reduce suicidality.