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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 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.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 were obtained for a cohort of Veterans who recently separated from active service.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.VHA facilities appear to be staffing-constrained when providing mental health care. Targeted increases in mental health staffing would be likely to reduce suicidality.

Risk of overdose, suicide, and other adverse outcomes are elevated among sub-populations prescribed opioid analgesics. To address this, the Veterans Health Administration (VHA) developed the Stratification Tool for Opioid Risk Mitigation (STORM)-a provider-facing dashboard that utilizes predictive analytics to stratify patients prescribed opioids based on risk for overdose/suicide.To evaluate the impact of the case review mandate on serious adverse events (SAEs) and all-cause mortality among high-risk Veterans.A 23-month stepped-wedge cluster randomized controlled trial in all 140 VHA medical centers between 2018 and 2020.A total of 44,042 patients actively prescribed opioid analgesics with high STORM risk scores (i.e., percentiles 1% to 5%) for an overdose or suicide-related event.A mandate requiring providers to perform case reviews on opioid analgesic-prescribed patients at high risk of overdose/suicide.Nine serious adverse events (SAEs), case review completion, number of risk mitigation strategies, and all-cause mortality.Mandated review inclusion was associated with a significant decrease in all-cause mortality within 4 months of inclusion (OR: 0.78; 95% CI: 0.65-0.94). There was no detectable effect on SAEs. Stepped-wedge analyses found that mandated review patients were five times more likely to receive a case review than non-mandated patients with similar risk (OR: 5.1; 95% CI: 3.64-7.23) and received more risk mitigation strategies than non-mandated patients (0.498; CI: 0.39-0.61).Among VHA patients prescribed opioid analgesics, identifying high risk patients and mandating they receive an interdisciplinary case review was associated with a decrease in all-cause mortality. Results suggest that providers can leverage predictive analytic-targeted population health approaches and interdisciplinary collaboration to improve patient outcomes.ISRCTN16012111.

Resource-constrained delivery systems often have access issues, causing patients to wait a long time to see a provider. We develop theoretical and empirical models of wait times and apply them to primary care delivery by the U.S. Veterans Health Administration (VHA). Using instrumental variables to handle simultaneity issues, we estimate the effect of clinician supply on new patient wait times. We find that it has a sizable impact. A 10% increase in capacity reduces wait times by 2.1%. Wait times are also associated with clinician productivity, scheduling protocols, and patient access to alternative sources of care. The VHA has adopted our models to identify underserved areas as specified by the MISSION Act of 2018.

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.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).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.We identified patients residing ≤40 miles from a VHA surgical facility with elective VHA or CC hernia surgery from 2018 to 2019.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.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.

Aim To test the effectiveness of a ketogenic diet and virtual coaching intervention in controlling markers of diabetes care and healthcare utilization. Materials and methods Using a difference-in-differences analysis with a waiting list control group-a quasi-experimental methodology-we estimated the 5-month change in HbA1c, body mass index, blood pressure, prescription medication use and costs, as well as healthcare utilization. The analysis included 590 patients with diabetes who were also overweight or obese, and who regularly utilize the Veterans Health Administration (VA) for healthcare. We used data from VA electronic health records from 2018 to 2020. Results The ketogenic diet and virtual coaching intervention was associated with significant reductions in HbA1c (-0.69 [95% CI -1.02, -0.36]), diabetes medication fills (-0.38, [-0.49, -0.26]), body mass index (-1.07, [-1.95, -0.19]), diastolic blood pressure levels (-1.43, [-2.72, -0.14]), outpatient visits (-0.36, [-0.70, -0.02]) and prescription drug costs (-34.54 [-48.56, -20.53]). We found no significant change in emergency department visits (-0.02 [-0.05, 0.01]) or inpatient admissions (-0.01 [-0.02, 0.01]). Conclusions This real-world assessment of a virtual coaching and diet programme shows that such an intervention offers short-term benefits on markers of diabetes care and healthcare utilization in patients with diabetes.

Spillovers can arise in markets with multiple purchasers relying on shared producers. Prior studies have found such spillovers in health care, from managed care to nonmanaged care populations-reducing spending and utilization, and improving outcomes, including in Medicare. This study provides the first plausibly causal estimates of such spillovers from Medicare Advantage (MA) to Traditional Medicare (TM) in the post-Affordable Care Act era using an instrumental variables approach. Controlling for health status and other potential confounders, we estimate that a one percentage point increase in county-level MA penetration results in a $64 (95% CI: $18 to $110) (0.7%) reduction in standardized per-enrollee TM spending. We find evidence for reductions in utilization both on the intensive and extensive margins, across a number of health care services. Our results complement and extend prior work that found spillovers from MA to TM in earlier years and under different payment policies than are in place today.

The Foundations for Evidence-Based Policymaking Act of 2018 requires cabinet-level agencies to use evidence to justify and support budget and policy making. As investigators from the Quality Enhancement Research Initiative (QUERI) program, we were tasked with assisting Veterans Health Administration (VHA) leadership with the implementation of the Evidence-Based Policymaking Act of 2018. Through meetings with stakeholders, we identified a gap in the review process for legislative and budget proposals; no systematic process existed to evaluate the supporting evidence base for proposals.Here, we describe the development, refinement, and use of a checklist to assess the strength of evidence included in VHA legislative and budget proposals for changes to care delivery; clinical, research, and administrative operations; and staffing and workforce issues.The evidence assessment checklist is now part of the regular review process for VHA legislative and budget proposals. It is also being adapted for use elsewhere within the Department of Veterans Affairs. The checklist has provided a framework for briefings and training on best practices for using evidence to guide policy and budget decisions.Including evidence reviews in the legislative and budget proposal prioritization process may be an effective institutional arrangement to promote the use of evidence to inform high-level health policy decisions and to build a "culture of evidence" within the government.

The aim was to explore the relationship between changes in regional economic conditions and quality of care-preventable hospitalization or death among older patients with diabetes at Veterans Health Administration (VHA), safety-net system for veterans.VHA patients aged 65 years and older with a diabetes diagnosis between July 2012 and June 2014, who had at least 1 primary care visit in the past year.County-level and state-level public data were used to characterize regional health insurance coverage and affluence surrounding the VHA facilities. Each patient was associated with a VHA facility and its corresponding regional market variables, and followed up to 48 months or until they experienced diabetes-related Prevention Quality Indicators or death.Discrete-time Cox proportional hazards models estimated that changes in regional market variables characterizing regional health insurance coverage and affluence were significant factors associated with preventable hospitalization or death. All regional market variables were combined into a demand index, where 1 SD decrease in the demand index was associated with a 2.0-point increase in predicted survival for an average patient at an average VHA facility. For comparison, a 1 SD increase in primary care capacity was associated with 4.7-point increase.Downturns in regional economic conditions could increase demand for VHA care and raise the risk of diabetes-related preventable hospitalization or death among older VHA patients diagnosed with diabetes. Safety-net hospitals may be unfairly penalized for lower quality of care when experiencing higher demand for care because of an economic downturn.

Policy Points Evidence suggests that bundled payment contracting can slow the growth of payer costs relative to fee-for-service contracting, although bundled payment models may not reduce absolute costs. Bundled payments may be more effective than fee-for-service payments in containing costs for certain medical conditions. For the most part, Medicare's bundled payment initiatives have not been associated with a worsening of quality in terms of readmissions, emergency department use, and mortality. Some evidence suggests a worsening of other quality measures for certain medical conditions. Bundled payment contracting involves trade-offs: Expanding a bundle's scope and duration may better contain costs, but a more comprehensive bundle may be less attractive to providers, reducing their willingness to accept it as an alternative to fee-for-service payment. Context Bundled payments have been promoted as an alternative to fee-for-service payments that can mitigate the incentives for service volume under the fee-for-service model. As Medicare has gained experience with bundled payments, it has widened their scope and increased their duration. However, there have been few reviews of the empirical literature on the impact of Medicare's bundled payment programs on cost, resource use, utilization, and quality. Methods We examined the history and features of 16 of Medicare's bundled payment programs involving hospital-initiated episodes of care and conducted a literature review of articles about those programs. Database and additional searches yielded 1,479 articles. We evaluate the studies' methodological quality and summarize the quantitative findings about Medicare expenditures and quality of care from 37 studies that used higher-quality research designs. Findings Medicare's bundled payment initiatives have varied in their design features, such as episode scope and duration. Many initiatives were associated with little to no reduction in Medicare expenditures, unless large pricing discounts for providers were negotiated in advance. Initiatives that included post-acute care services were associated with lower expenditures for certain conditions. Hospitals may have been able to reduce internal production costs with help from physicians via gainsharing. Most initiatives were not associated with significant changes in quality of care, as measured by readmission and mortality rates. Of the significant changes in readmission rates, the results were mixed, showing increases and decreases associated with bundled payments. Some evidence suggested that worse patient outcomes were associated bundled payments, although most results were not statistically significant. Results on case-mix selection were mixed: Several initiatives were associated with reductions in episode severity, whereas others were associated with little change. Conclusions Bundled payments for hospital-initiated episodes may be a good alternative to fee-for-service payments. Bundled payments can help slow the growth of payer spending, although they do not necessarily reduce absolute spending. They are associated with lower provider production costs, and there is no overwhelming evidence of compromised quality. However, designing a bundled payment contract that is attractive to both providers and payers proves to be a challenge.

BACKGROUND: Rural residents face more barriers to healthcare access, including challenges in receiving home- and community-based long-term services, compared to urban residents. Self-directed services provide flexibility and choice in care options and may be particularly well suited to help older adults with multiple chronic conditions and functional limitations who reside in rural areas remain independent and live in the community. METHODS: We conducted a retrospective observational study to understand whether differences in health outcomes between Veteran-Directed Care (VDC), a self-directed Veterans Health Administration (VHA)-paid care program, and other VHA-paid home- and community-based personal care services vary in rural/urban location. The sample included 37,395 Veterans receiving VHA-paid home- and community-based long-term care services in FY17. Our primary outcomes were changes in monthly incidence of VHA or VHA-paid community acute care admissions, nursing home admissions, and emergency department (ED) visits. We used fixed effects logistic regression models on unmatched and coarsened exact matched cohorts, stratified by rural/urban location. RESULTS: Both urban and rural VDC recipients were significantly less likely to be admitted to VHA-paid nursing homes, compared to those receiving other VHA-paid personal care services (rural: incremental effect = −0.22, [ −0.30, −0.14]; urban: incremental effect = −0.14, [−0.20, −0.07]). Rural, but not urban, VDC enrollees had significantly fewer VHA-paid acute care admissions and ED visits, relative to recipients of other VHA-paid personal care services (acute care, rural: incremental effect = −0.07, 95% CI = [−0.14, −0.01], urban: incremental effect = −0.01, [−0.06, 0.03]; ED, rural: incremental effect = −0.08, [−0.14, −0.02], urban: incremental effect = 0.01, [−0.03, 0.05]). CONCLUSIONS: VDC recipients had fewer incidents of potentially avoidable VHA-paid health care use, compared to similar Veterans receiving other VHA-paid personal care services. These differences were more pronounced among rural VDC recipients than urban VDC recipients.

To estimate the effect of wait times on patients' choice of provider and simulate changes in choice of provider due to compliance with VA MISSION Act wait time targets.We use nationwide administrative data (2014-2017) on Veterans who are enrolled in Medicare and the Veterans Health Administration (VHA), the Survey of VHA Enrollees, Area Health Resource Files, and other data provided by the Centers for MedicareMedicaid Services.We use an instrumental variables approach to identify the effect of VHA wait times on the proportion of total (Medicare and VHA) services that are paid for by the VHA ("reliance"). We exploit shocks to VHA provider supply to isolate supply-driven changes in wait times and estimate the effect on VHA reliance. We control for market and time fixed effects and local demand factors.We use monthly aggregated data on 140 markets (groups of counties). VHA reliance is computed among patients aged 65 years or older who are dually enrolled in VHA and Medicare. VHA wait times and reliance are calculated for multiple specialties: cardiology, gastroenterology, orthopedics, urology, dermatology, and ophthalmology/optometry.A 10% increase in the mean wait time (+2.8 days) reduces VHA reliance by 2.3 percentage points (95% CI: 2.3, 2.7), or 7.9% of the sample mean. This implies that meeting the MISSION Act wait time targets may have multi-billion-dollar budgetary impacts. Effects vary across specialties. For example, a 10% increase in the mean wait time for cardiology services (+2.0 days) reduces reliance by 1.8 percentage points (95% CI: 1.6, 2.1), or 6.3% of the sample mean for cardiology services.Meeting statutory wait time targets may have substantial unforeseen impacts on federal health care spending as patients sort to providers who have lower wait times.

Objective: Nutrition interventions are key components of diabetes care. In light of increased disease prevalence among Veterans, the Veterans Health Administration (VA) partnered with Virta Health to test the effectiveness of a ketogenic-diet and virtual coaching intervention in controlling markers of diabetes care and healthcare utilization. Research Design and Methods: Using a difference-in-differences analysis with a waitlist-control group—a quasi-experimental methodology—we estimated the five-month change in hemoglobin A1c (HbA1c), body mass index, blood pressure, prescription medication use, and healthcare utilization. The analysis included 590 patients with diabetes who were also overweight or obese, and who regularly utilize VA for healthcare. We used data from VA electronic health records from 2018-2020. Results: The ketogenic diet and virtual coaching intervention was associated with significant reductions in HbA1c levels (-0.68, [95% CI -1.01, -0.35]), diabetes medication fills (-0.38, [-0.49, -0.26]), body mass index (-1.08, [-1.96, -0.20]), diastolic blood pressure levels (-1.4, [-2.73, -0.14]) and outpatient visits (-0.36, [-0.70, -0.02]). We found no significant change in emergency department visits. Conclusions: This real-world assessment of a virtual coaching and diet program shows that such an intervention offers short-term benefits on markers of diabetes care and healthcare utilization in patients with diabetes. It remains unclear whether the effect of the program operates primarily through the personalized coaching component, the ketogenic diet recommendations, or some combination of the two. Disclosure K. Strombotne: None. J. Lum: None. N. Ndugga: None. A. Utech: None. S. Pizer: None. A. Frakt: None. P. Conlin: None. Funding U.S. Department of Veterans Affairs (HSR&D SDR 20-386); National Institute of Diabetes and Digestive and Kidney Diseases (R01DK114098)

In response to widespread concerns regarding Veterans’ access to VA care, Congress enacted the Veterans Access, Choice and Accountability Act of 2014, which required VA to establish the Veterans Choice Program (VCP). Since the inception of VCP, more than two million Veterans have received care from community providers, representing approximately 25% of Veterans enrolled in VA care. However, expanded access to non-VA care has created challenges in care coordination between VA and community health systems. In March 2018, the VA Health Services Research & Development Service hosted a VA State of the Art conference (SOTA) focused on care coordination. The SOTA convened VA researchers, program directors, clinicians, and policy makers to identify knowledge gaps regarding care coordination within the VA and between VA and community systems of care. This article provides a summary and synthesis of relevant literature and provides recommendations generated from the SOTA about how to evaluate cross-system care coordination. Care coordination is typically evaluated using health outcomes including hospital readmissions and death; however, in cross-system evaluations of care coordination, measures such as access, cost, Veteran/patient and provider satisfaction (including with cross-system communication), comparable quality metrics, context (urban vs. rural), and patient complexity (medical and mental health conditions) need to be included to fully evaluate care coordination effectiveness. Future research should examine the role of multiple individuals coordinating VA and non-VA care, and how these coordinators work together to optimize coordination.

The Veteran-Directed Care (VDC) program facilitates independent community living among adults with multiple chronic conditions and functional limitations. Family caregivers value the choice and flexibility afforded by VDC, but rigorous evidence to support its impact on health care costs and use is needed. We identified veterans enrolled in VDC in fiscal year 2017 and investigated differences in hospital admissions and costs after initial receipt of VDC services. We compared VDC service recipients to a matched comparison group of veterans receiving homemaker or home health aide, home respite, and adult day health care services and found similar decreases in hospital use and costs from before to after enrollment in the groups. Further investigation into trends of nursing home use, identification of veterans most likely to benefit from VDC, and relative costs of operating VDC versus other purchased care programs is needed, but our results suggest that VDC remains a valuable option for supporting veterans and caregivers.

The United States is facing an opioid crisis in which overdose is the leading cause of injury death—misuse of opioids constitutes the vast majority of those deaths. In 2016 alone, over 42,000 people died from opioid overdose, an increase of 27% from the prior year. Deployment of the Stratification Tool for Opioid Risk Mitigation (STORM), a clinical decision support tool to improve opioid safety, is one response by the Veterans Health Administration (VHA) to the opioid crisis. STORM identifies VHA patients at very high risk of opioid-related adverse events and lists potential risk mitigation strategies. Deployment of STORM also helps VHA meet certain requirements of the Comprehensive Addiction and Recovery Act of 2016. In alignment with the VHA's learning health care system initiative, a multidisciplinary team designed a randomized evaluation of a policy approach to mandating case reviews of very-high-risk patients identified by STORM and the impacts of patient inclusion versus exclusion in mandated STORM case reviews using a stepped-wedge design. The STORM evaluation involves drafting the policy notice, shepherding it through the VHA approval process, and implementing the cluster randomized design. This mixed-methods evaluation includes (1) a qualitative assessment of medical center implementation strategies with the aim of understanding of how STORM is incorporated into practice, and (2) quantitative analyses of the relations between policy mandates and STORM inclusion on opioid-related adverse events. The findings from this synergistic research design will yield critical insights for VHA leadership to refine opioid prescribing-related policy and practice.

OBJECTIVE: To characterize the rate of guideline‐concordant initiation of oral anticoagulation (OAC) among elderly Veterans with atrial fibrillation (AF) and high stroke risk. DATA SOURCES/STUDY SETTING: Veterans Health Administration (VHA) Corporate Data Warehouse (CDW) linked with Medicare claims 2011‐2015. STUDY DESIGN: We identified 6619 elderly, high stroke‐risk patients with a new episode of AF initially diagnosed in the VHA during fiscal years 2012‐2015. We used logistic regression to estimate marginal effects of associations between patient characteristics and OAC initiation within 90 days of the first AF episode. DATA EXTRACTION METHODS: We identified OACs using generic drug names. We calculated comorbidities and risk scores using diagnosis codes from 1 year of baseline data. PRINCIPAL FINDINGS: Overall, 66.5% of Medicare‐eligible Veterans with AF at high risk of stroke initiated an OAC within 90 days. We found lower initiation rates for patients enrolled in Medicare Part D and those ineligible for drug co‐payment subsidies. OAC initiation rates increased during the study among VHA‐reliant patients but not among dual VHA‐Part D enrollees. CONCLUSIONS: One‐third of elderly Veterans at risk of stroke are not receiving recommended therapy. Increased coordination between Medicare and VHA providers may lead to improvements in anticoagulation quality and stroke prevention.

Objectives To evaluate the association between regional market factors and experience with patient-provider communication in primary care services of safety net hospitals. Study design A retrospective cohort study with 933,407 patient experience survey respondents from 128 Veterans Health Administration (VHA) hospitals between fiscal years 2013 and 2016. Methods Patient responses on 5 patient-provider communication questions were used to evaluate quality of care. Six regional market factors were used to characterize veterans' health care insurance coverage and affluence. A logistic regression was used to examine changes in individual-level patient-provider communication experience when regional market factors increase or decrease the demand for VHA primary care services. Results Our findings supported our hypothesis that changes in regional market factors shift patient demand for VHA care and affect patient-provider communication measured by patient experience surveys. The adjusted odds ratio (AOR) of positive patient-provider communication was associated with a regional increase (first to third quartile) of employer-sponsored insurance (AOR, 1.028; 95% CI, 1.001-1.055) and a decrease (third to first quartile) in the veterans' unemployment rate (AOR, 0.966; 95% CI, 0.944-0.990). Higher primary care capacity (first to third quartile) was also associated with positive patient-provider communication (AOR, 1.050; 95% CI, 1.018-1.082). Conclusions Findings from this study raise concerns that safety net hospitals could be unfairly penalized by value-based payment programs and Medicare Hospital Compare. Such policies and programs could improve resource allocation by accounting for regional market factors before acting on quality of care measures.

This cross-sectional study compares appointment wait times at Veterans Health Administration facilities and those at community medical centers accessed via the Veterans Choice Program.

BACKGROUND: Health care operations managers need to balance scheduling frequent follow-ups for patients with chronic conditions and fitting in patients requiring care for new complaints. OBJECTIVE: We quantify how frequency of follow-up visits corresponds with access to care for patients receiving care from the Department of Veterans Affairs (VA). DESIGN: We use patient data collected between October 2013 and June 2016 by the Survey of Healthcare Experiences of Patients (SHEP). Our sample is comprised of 94,496 patients. We estimate logistic models with 1-month lagged facility-level predictors. MAIN MEASURES: We calculate monthly measures characterizing facility-level service provision, including the average time between successive primary care visits, the average primary care visit length, the percentage of primary care appointments that are overbooked, the percent of visits that are unscheduled (i.e., walk-ins), and the ratio of patients to providers. We control for economic factors that are associated with health care supply and demand, including median household income, veteran priority status, the Zillow Housing Price Index, and veteran unemployment rates. We also control for patient demographics. PATIENTS: We restrict the data to patients with at least one in-person primary care visit who have provided information on their ability to access urgent and routine care. KEY RESULTS: We find that shorter average follow-up times are associated with better access for patients needing urgent or routine care. A 1-month increase in the average time between successive primary care visits is associated with 10% (p

Access to care is an important issue in public health care systems. Unlike private systems, in which price equilibrates supply and demand, public systems often ration medical services through wait times. Access that is given on a first come, first served basis might not yield an allocation of resources that maximizes the health of a population, potentially creating suboptimal heterogeneity in wait times. In this study, we examine an access disparity between two groups of patients-established patients and new patients. We exploit an exogenous policy change-implemented by the U.S. Veterans Health Administration-that removed the disparity and homogenized the wait time. We find strong evidence that without such a policy, established patients have priority access over new patients. We discuss whether this is a suboptimal allocation of resources. We additionally find that established patient priority access is an important determinant of access for new patients; accounting for it increased the explanatory power of our statistical model of new patient wait times by a factor of five. The findings imply that policy and management decisions may be more effective in achieving the optimal distribution of access if access heterogeneity is recognized and accounted for explicitly.

Objective Develop and validate a surveillance model to identify outpatient surgical adverse events (AEs) based on previously developed electronic triggers. Data sources Veterans Health Administration's Corporate Data Warehouse. Study design Six surgical AE triggers, including postoperative emergency room visits and hospitalizations, were applied to FY2012-2014 outpatient surgeries (n = 744,355). We randomly sampled trigger-flagged and unflagged cases for nurse chart review to document AEs and measured positive predictive value (PPV) for triggers. Next, we used chart review data to iteratively estimate multilevel logistic regression models to predict the probability of an AE, starting with the six triggers and adding in patient, procedure, and facility characteristics to improve model fit. We validated the final model by applying the coefficients to FY2015 outpatient surgery data (n = 256,690) and reviewing charts for cases at high and moderate probability of an AE. Principal findings Of 1,730 FY2012-2014 reviewed surgeries, 350 had an AE (20 percent). The final surveillance model c-statistic was 0.81. In FY2015 surgeries with >0.8 predicted probability of an AE (n = 405, 0.15 percent), PPV was 85 percent; in surgeries with a 0.4-0.5 predicted probability of an AE, PPV was 38 percent. Conclusions The surveillance model performed well, accurately identifying outpatient surgeries with a high probability of an AE.

OBJECTIVE: To describe a new Veterans Health Administration (VHA) program to foster the learning health system paradigm by rigorously evaluating health care initiatives and to report key lessons learned in designing those evaluations. PRINCIPAL FINDINGS: The VHA's Quality Enhancement Research Initiative and its Health Services Research and Development Service are cooperating on several large, randomized program evaluations aimed at improving the care veterans receive and the efficiency with which it is delivered. The evaluations we describe involve collaborative design, outcomes assessment, and implementation science through partnerships between VHA operations and researchers. We review key factors to assess before committing to an evaluation. In addition to traditional design issues (such as ensuring adequate power and availability of data), these include others that are easily overlooked: the stability of intervention financing, means of controlling and commitment to adhering to randomized roll‐out, degree of buy‐in from key implementation staff, and feasibility of managing multiple veto points for interventions that span several programs, among others. CONCLUSIONS: Successful program implementation and rigorous evaluation require resources, specialized expertise, and careful planning. If the learning health system model is to be sustained, organizations will need dedicated programs to prioritize resources and continuously adapt evaluation designs.

Background Medical scribes are trained professionals who assist health care providers by administratively expediting patient encounters. Section 507 of the MISSION Act of 2018 mandated a 2-year study of medical scribes in VA Medical Centers (VAMC). This study began in 2020 in the emergency departments and specialty clinics of 12 randomly selected VAMCs across the country, in which 48 scribes are being deployed. Methods We are using a cluster randomized trial to assess the effects of medical scribes on productivity (visits and relative value units [RVUs]), wait times, and patient satisfaction in selected specialties within the VA that traditionally have high wait times. Scribes will be assigned to emergency departments and/or specialty clinics (cardiology, orthopedics) in VAMCs randomized into the intervention. Remaining sites that expressed interest but were not randomized to the intervention will be used as a comparison group. Results Process measures from early implementation of the trial indicate that contracting may hold an advantage over direct hiring in terms of reaching staffing targets, although onboarding contractor scribes has taken somewhat longer (from job posting to start date). Conclusions Our evaluation findings will provide insight into whether scribes can increase provider productivity and decrease wait times for high demand specialties in the VA without adversely affecting patient satisfaction. Implications As a learning health care system, this trial has great potential to increase our understanding of the potential effects of scribes while also informing a real policy problem in high wait times and provider administrative burdens.

Objectives To examine how medical complexity modifies the relationship between enrollment in Department of Veterans Affairs (VA) home-based primary care (HBPC) and hospitalization for ambulatory care–sensitive conditions (ACSC) for veterans with diabetes mellitus and whether the effect of HBPC on hospitalizations varies according to clinical condition. Design Retrospective cohort study. Setting VA and non-VA hospitals. Participants VA beneficiaries aged 67 and older with diabetes mellitus and enrolled in Medicare (N = 364,972). Measurements Instrumental variables regression models were used to estimate the effect of HBPC enrollment on hospitalization for ACSCs (defined according to the Agency for Healthcare Research and Quality Prevention Quality Indicators) overall and in subgroups stratified according to medical complexity. Models were also estimated for each ACSC to determine which conditions were most sensitive to HBPC. Distance from the veteran's residence to the nearest HBPC site was used as the instrumental variable. Results HBPC was associated with fewer ACSC hospitalizations (odds ratio (OR) = 0.35 per person-month, 95% confidence interval (CI) = 0.30–0.42). For veterans in the highest quartile of medical complexity, HBPC enrollment was associated with fewer ACSC hospitalizations (OR = 0.43, 95% CI = 0.19–0.93), whereas for those in the lowest quartile, HBPC was associated with more ACSC hospitalizations (OR = 33.2, 95% CI = 4.6–240.1). HBPC enrollment was associated with fewer hospitalizations for a range of ACSCs. Conclusion HBPC enrollment was associated with fewer hospitalizations for a range of ACSCs in veterans with diabetes mellitus but only in the most medically complex individuals. This demonstrates the importance of appropriate targeting and suggests that the effect of HBPC is attributable to its comprehensive approach rather than condition-specific interventions.

OBJECTIVES: There is little research on the relationship between call center performance and patient-centered outcomes. In this study, we quantified the relationships between 2 measures of telephone access, average speed of answer (ASA) and abandonment rate (AR), and patient satisfaction outcomes within the Veterans Health Administration (VHA). STUDY DESIGN: We analyzed 2015 and 2016 data from the Survey of Healthcare Experiences of Patients and linked them with administrative data to gather features of the patient visit and monthly measures of telephone access for each medical center. METHODS: We used mixed effects logistic regression models to estimate the effects of ASA and AR on a variety of access and satisfaction outcomes. Models were adjusted for patient-level demographics, time-varying facility-level characteristics, features of the patient visit, and facility-level random effects to control for care quality and case mix differences. RESULTS: The VHA made substantial strides in both access measures between 2015 and 2016. We found that a center’s ASA was inversely associated with patients’ perceptions of their ability both to access urgent care appointments and to do so in a timely manner. In contrast, telephone AR was not associated with any of the patient satisfaction outcomes. CONCLUSIONS: Our results associate decreased telephone waits with improved perceptions of urgent care access even without concomitant decreases in observed appointment waits. These findings may have important implications for regulators as well as for healthcare organizations that must decide resource levels for call centers, including hospitals, federal health insurance exchanges, and insurers.

Treatment effect estimation must account for observed confounding, in which factors affect treatment assignment and outcomes simultaneously. Ignoring observed confounding risks concluding that a helpful treatment is not beneficial or that a treatment is safe when actually harmful. Propensity score matching or weighting adjusts for observed confounding, but the best way to use propensity scores for multiple treatments is unknown. It is unclear when choice of a different weighting or matching strategy leads to divergent inferences. We used Monte Carlo simulations (1,000 replications) to examine sensitivity of multi-valued treatment inferences to propensity score weighting or matching strategies. We consider five variants of propensity score adjustment: inverse probability of treatment weights (IPTW), generalized propensity score matching, kernel weights, vector matching, and a new hybrid that is easily implemented — vector-based kernel weighting (VBKW). VBKW matches observations with similar propensity score vectors, assigning greater kernel weights to observations with similar probabilities within a given bandwidth. We varied degree of propensity score model misspecification, sample size, treatment effect heterogeneity, initial covariate imbalance, and sample distribution across treatment groups. We evaluated sensitivity of results to propensity score estimation technique (multinomial logit or multinomial probit). Across simulations, VBKW performed equally or better than the other methods in terms of bias, efficiency, and covariate balance measured via prognostic scores. Our simulations suggest that VBKW is amenable to full automation and is less sensitive to PS model misspecification than other methods used to account for observed confounding in multi-valued treatment analyses.

Background Guidelines recommend discontinuation of antimicrobial prophylaxis within 24 h after incision closure in uninfected patients. However, how facility and surgical specialty factors affect the implementation of these evidence-based surgical prophylaxis guidelines in outpatient surgery is unknown. Thus, we sought to measure how facility complexity, including ambulatory surgical center (ASC) status and availability of ancillary services, impact adherence to guidelines for timely discontinuation of antimicrobial prophylaxis after outpatient surgery. A secondary aim was to measure the association between surgical specialty and guideline compliance. Methods A multi-center, national Veterans Health Administration retrospective cohort from 10/1/2015–9/30/2017 including any Veteran undergoing an outpatient surgical procedure in any of five specialties (general surgery, urology, ophthalmology, ENT, orthopedics) was created. The primary outcome was the association between facility complexity and proportion of surgeries not compliant with discontinuation of antimicrobials within 24 h of incision closure. Data were analyzed using logistic regression with adjustments for patient and procedural factors. Results Among 153,097 outpatient surgeries, 7712 (5.0%) received antimicrobial prophylaxis lasting > 24 h after surgery; rates ranged from 0.4% (eye surgeries) to 13.7% (genitourinary surgeries). Cystoscopies and cystoureteroscopy with lithotripsy procedures had the highest rates (16 and 20%), while hernia repair, cataract surgeries, and laparoscopic cholecystectomies had the lowest (0.2–0.3%). In an adjusted logistic regression model, lower complexity ASC and hospital outpatient departments had higher odds of prolonged antimicrobial prophylaxis compared to complex hospitals (OR ASC, 1.3, 95% CI: 1.2–1.5). Patient factors associated with higher odds of noncompliance with antimicrobial discontinuation included younger age, female sex, and white race. Genitourinary and ear/nose/throat surgeries were associated with the highest odds of prolonged antimicrobial prophylaxis. Conclusions Facility complexity appears to play a role in adherence to surgical infection prevention guidelines. Lower complexity facilities with limited infection prevention and antimicrobial stewardship resources may be important targets for quality improvement. Such interventions may be especially useful for genitourinary and ear/nose/throat surgical subspecialties. Increasing pharmacy, antimicrobial stewardship and/or infection prevention resources to promote more evidence-based care may support surgical providers in lower complexity ambulatory surgery centers and hospital outpatient departments in their efforts to improve this facet of patient safety. Electronic supplementary material The online version of this article (10.1186/s13756-019-0503-9) contains supplementary material, which is available to authorized users.

BACKGROUND Emergency department (ED) use following outpatient surgery may be associated with a surgery-related patient safety problem. We characterized ED use within 7 days of general, urology, orthopedic, ear/nose/throat, and podiatry surgical procedures and assessed factors associated with these visits by specialty. METHODS We calculated the 2011-2013 postoperative ED visit rate for Veterans older than 65 years dually enrolled in the Veterans Health Administration (VA) and Medicare, examined diagnoses, and used logistic regression to model patient, procedure, and facility factors associated with ED care. RESULTS Among 63 279 outpatient surgical procedures, 2778 (4.4%) resulted in an ED visit within 7 days; 23% of these were to non-VA facilities. Rates varied from more than 5% for urology and ear/nose/throat, to less than 3% for orthopedic and podiatry specialties. Genitourinary symptoms and surgical complications were common diagnoses across specialties. No patient, procedure, or facility factors were associated with ED use for every specialty. CONCLUSIONS A small proportion of VA outpatient surgical procedures result in ED use. Notably, nearly one-fourth of the postoperative ED visits may be missed by the VA because they occur in non-VA facilities. ED visits for urinary issues or surgical complications may be preventable; however, factors associated with ED use vary by specialty, suggesting different approaches may be needed to improve outcomes.

Aims To characterize the relationship between HbA1c variability and adverse health outcomes among US military veterans with Type 2 diabetes. Methods This retrospective cohort study used Veterans Affairs and Medicare claims for veterans with Type 2 diabetes taking metformin who initiated a second diabetes medication (n = 50 861). The main exposure of interest was HbA1c variability during a 3-year baseline period. HbA1c variability, categorized into quartiles, was defined as standard deviation, coefficient of variation and adjusted standard deviation, which accounted for the number and mean number of days between HbA1c tests. Cox proportional hazard models predicted mortality, hospitalization for ambulatory care-sensitive conditions, and myocardial infarction or stroke and were controlled for mean HbA1c levels and the direction of change in HbA1c levels during the baseline period. Results Over a mean 3.3 years of follow-up, all HbA1c variability measures significantly predicted each outcome. Using the adjusted standard deviation measure for HbA1c variability, the hazard ratios for the third and fourth quartile predicting mortality were 1.14 (95% CI 1.04, 1.25) and 1.42 (95% CI 1.28, 1.58), for myocardial infarction and stroke they were 1.25 (95% CI 1.10, 1.41) and 1.23 (95% CI 1.07, 1.42) and for ambulatory-care sensitive condition hospitalization they were 1.10 (95% CI 1.03, 1.18) and 1.11 (95% CI 1.03, 1.20). Higher baseline HbA1c levels independently predicted the likelihood of each outcome. Conclusions In veterans with Type 2 diabetes, greater HbA1c variability was associated with an increased risk of adverse long-term outcomes, independently of HbA1c levels and direction of change. Limiting HbA1c fluctuations over time may reduce complications.

We evaluate consumption responses to the non-linear Medicare Part D prescription drug benefit. We compare propensity-matched older patients with diabetes and Part D Standard or low-income-subsidy (LIS) coverage. We evaluate monthly adherence to branded oral anti-diabetics, with high end-of-year donut hole prices (>$200) for Standard patients and consistent, low (≤$6) prices for LIS. As an additional control, we examine adherence to generic anti-diabetics, with relatively low, consistent prices for Standard patients. If Standard patients are forward looking, they will reduce branded adherence in January, and LIS-Standard differences will be constant through the year. Contrary to this expectation, branded adherence is lower for Standard patients in January and diverges from LIS as the coverage year progresses. Standard-LIS generic adherence differences are minimal. Our findings suggest that seniors with chronic conditions respond myopically to the nonlinear Part D benefit, reducing consumption in response to high deductible, initial coverage and gap prices. Thus, when the gap is fully phased out in 2020, cost-related nonadherence will likely remain in the face of higher spot prices for more costly branded medications. These results contribute to studies of Part D plan choice and medication adherence that suggest that seniors may not make optimal healthcare decisions. Copyright © 2016 John Wiley & Sons, Ltd.

Background Opioid-related adverse drug events are common following inpatient surgical procedures. Little is known about opioid prescribing after outpatient surgical procedures and if opioid use is associated with short term risks of outpatient surgical adverse events (AEs). Methods VA Corporate Data Warehouse was used to identify opioid use within 48 h for FY2012-14 chart-reviewed cases from a larger VA study of AEs in outpatient surgeries. We estimated a multilevel logistic regression model to determine the effect of opioid exposure on risk of AEs between 2 and 30 days postoperatively. Results Of the 1730 outpatient surgical cases, 628 (36%) had postoperative opioid use and 12% had an AE. Opioid use following outpatient surgery was not significantly associated with higher surgical AE rates after controlling for relevant covariates (OR = 1.1 95% CI 0.79–1.54). Only procedure RVUs were associated with higher odds of postoperative AEs. Conclusions Postoperative opioid use following outpatient surgery is not a significant driver of postoperative AEs.

PURPOSE: To examine associations between patient perceptions that their provider was knowledgeable of their medical history and clinicians’ early adoption of an application that presents providers with an integrated longitudinal view of a patient’s electronic health records (EHR) from multiple healthcare systems. METHOD: This retrospective analysis utilizes provider audit logs from the Veterans Health Administration Joint Legacy Viewer (JLV) and patient responses to the Survey of Patient Healthcare Experiences Patient-Centered Medical Home (SHEP/PCMH) patient satisfaction survey (FY2016) to assess the relationship between the primary care provider being an early adopter of JLV and patient perception of the provider’s knowledge of their medical history. Multivariate logistic regression models were used to control for patient age, race, sex education, health status, duration of patient-provider relationship, and provider characteristics. RESULTS: The study used responses from 203,903 patients to the SHEP-PCMH survey in FY2016 who received outpatient primary care services from 11,421 unique providers. Most (91%) clinicians had no JLV utilization in the 6 months prior to the studied patient visit. Controlling for patient demographics, length of the patient-provider relationship, and provider and facility characteristics, being an early adopter of the JLV system was associated with a 14% (adj OR 1.14, p

Objective Veterans' utilization of Veterans Affairs (VA) health care is likely influenced by community factors external to the VA, including Medicaid eligibility and unemployment, although such factors are rarely considered in models predicting such utilization. We measured the sensitivity of VA utilization to changes in such community factors (hereafter, "external determinants"), including the 2014 Medicaid expansion following the Affordable Care Act. Data sources/study setting We merged VA health care enrollment and utilization data with area-level data on Medicaid policy, unemployment, employer-sponsored insurance, housing prices, and non-VA physician availability (2008-2014). Study design For veterans aged 18-64 and ≥65, we estimated the sensitivity of annual individual VA health care utilization, measured by the cost ($) of care received, to changes in external determinants using longitudinal regression models controlling for individual fixed effects. Principal findings All external determinants were associated with small but significant changes in VA health care utilization. In states that expanded Medicaid in 2014, this expansion was associated with 9.1 percent ($826 million) reduction in VA utilization among those aged 18-64; sizable changes occurred in all services used (inpatient, outpatient, and prescription drugs). Conclusions Changes in alternative insurance coverage and other external determinants may affect VA health care spending. Policy makers should consider these factors in allocating VA resources to meet local demand.

Objective To examine factors associated with 0- to 7-day admission after outpatient surgery in high-volume specialties: general surgery, orthopedics, urology, ear/nose/throat, and podiatry. Study design We calculated rates and assessed diagnosis codes for 0- to 7-day admission after outpatient surgery for Centers for Medicare and Medicaid Services (CMS) and Veterans Health Administration (VA) dually enrolled patients age 65 and older. We also estimated separate multilevel logistic regression models to compare patient, procedure, and facility characteristics associated with postoperative admission. Data collection 2011-2013 surgical encounter data from the VA Corporate Data Warehouse; geographic data from the Area Health Resources File; CMS enrollment and hospital admission data. Principal findings Among 63,585 outpatient surgeries in 124 facilities, 0- to 7-day admission rates ranged from 5 percent (podiatry) to 28 percent (urology); nearly 66 percent of the admissions occurred on the day of surgery. Only 97 admissions were detected in the CMS data (1 percent). Surgical complications were diagnosed in 4 percent of admissions. Procedure complexity, measured by relative value units or anesthesia risk score, was associated with admission across all specialties. Conclusion As many as 20 percent of VA outpatient surgeries result in an admission. Complex procedures are more likely to be followed by admission, but more evidence is required to determine how many of these reflect potential safety or quality problems.

Objectives To demonstrate how falsification tests can be used to evaluate instrumental variables methods applicable to a wide variety of comparative effectiveness research questions. Study Design Brief conceptual review of instrumental variables and falsification testing principles and techniques accompanied by an empirical application. Sample STATA code related to the empirical application is provided in the Appendix. Empirical Application Comparative long-term risks of sulfonylureas and thiazolidinediones for management of type 2 diabetes. Outcomes include mortality and hospitalization for an ambulatory care–sensitive condition. Prescribing pattern variations are used as instrumental variables. Conclusions Falsification testing is an easily computed and powerful way to evaluate the validity of the key assumption underlying instrumental variables analysis. If falsification tests are used, instrumental variables techniques can help answer a multitude of important clinical questions.

A path-breaking example of the interplay between geriatrics and learning healthcare systems is the Veterans Health Administration's (VHA's) planned roll-out of a program for providing participant-directed home- and community-based services to veterans with cognitive and functional limitations. We describe the design of a large-scale, stepped-wedge, cluster-randomized trial of the Veteran-Directed Home- and Community-Based Services (VD-HCBS) program. From March 2017 through December 2019, up to 77 Veterans Affairs Medical Centers will be randomized to times to begin offering VD-HCBS to veterans at risk of nursing home placement. Services will be provided to community-dwelling participants with support from Aging and Disability Network Agencies. The VHA Partnered Evidence-based Policy Resource Center (PEPReC) is coordinating the evaluation, which includes collaboration from operational stakeholders from the VHA and Administration for Community Living and interdisciplinary researchers from the Center of Innovation in Long-Term Services and Supports and the Center for Health Services Research in Primary Care. For older veterans with functional limitations who are eligible for VD-HCBS, we will evaluate health outcomes (hospitalizations, emergency department visits, nursing home admissions, days at home) and healthcare costs associated with VD-HCBS availability. Learning healthcare systems facilitate diffusion of innovation while enabling rigorous evaluation of effects on patient outcomes. The VHA's randomized rollout of VD-HCBS to veterans at risk of nursing home placement is an example of how to achieve these goals simultaneously. PEPReC's experience designing an evaluation with researchers and operations stakeholders may serve as a framework for others seeking to develop rapid, rigorous, large-scale evaluations of delivery system innovations targeted to older adults.

OBJECTIVES: Satisfaction with care is an important patient-centered domain of health system quality. However, satisfaction measures are costly to collect and not directly modifiable. Therefore, we assessed the relationships between veterans’ satisfaction and measures of modifiable aspects of Veterans Health Administration (VHA) mental health care programs. STUDY DESIGN: For a sample of 6990 patients who received mental health care from the VHA in 2013, we used survey and administrative data to investigate the association of a suite of access and encounter satisfaction measures with a large collection of measures of program characteristics. METHODS: We estimated risk-adjusted correlations between 6 satisfaction measures (across 2 domains: access and encounter satisfaction) and 28 mental health care program characteristics (across 4 domains: program reach, psychosocial service access, program intensity, and treatment continuity). RESULTS: We found that satisfaction with access to care was higher than experiences with care encounters, but that broad measures of mental health care program reach and intensity were positively associated with both kinds of satisfaction. No measures of psychosocial service access were positively associated with access and encounter satisfaction. Most measures of treatment continuity were consistently and positively associated with both kinds of satisfaction. CONCLUSIONS: As the VHA strives to increase access to, and provision of, mental health care, policy makers and program managers should be aware that satisfaction with care, as it is currently measured, may not rise as more patients initiate treatment, unless continuity of care is maintained or enhanced.

Background Adverse event (AE) rates in outpatient surgery are inconsistently reported, partly because of the lack of a standard definition of outpatient surgery. We compared the types and rates of surgical procedures defined by two national healthcare agencies: Health Care Cost Institute (HCCI) and the Healthcare Cost and Utilization Project (HCUP) and considered implications for quality measurement. Methods We used HCCI and HCUP definitions to identify FY2012-14 VA outpatient surgeries. Results There were six times as many HCCI surgeries as HCUP (6,575,830 versus 1,086,640). Ninety-nine percent of HCUP-defined surgeries were also identified by HCCI. More HCUP surgeries had higher average Medicare Relative Value Units then HCCI surgeries [5.3 (SD = 4.4) versus 1.6 (SD = 2.3) RVUs]. Conclusions Rates and types of procedures vary widely between definitions. Quality measurement using HCCI versus HCUP may produce significantly lower AE rates because many of the surgeries included reflect low complexity and potentially low risk of AEs.

The recently established Center for Innovation for Care and Payment will give the U.S. Department of Veterans Affairs (VA) the ability to test novel payment and service delivery models; will facili...

Long waits for appointments decrease patient satisfaction. Administrative wait-time measures are used by managers, but relationships between these measures and satisfaction have not been studied. Data from the Veterans Health Administration are used to examine the relationship between wait times and satisfaction. Outcome measures include patient-reported satisfaction and timely appointment access. Capacity and retrospective and prospective time stamp measures are calculated separately for new and returning patients. The time stamp measures consist of the date when the appointment was created in the scheduling system (create date [CD]) or the date the appointment was desired as the start date for wait-time computation. Logistic regression models predict patient satisfaction using these measures. The new-patient capacity, new-patient time stamp measures using CD, and the returning-patient desired-date prospective measure were significantly associated with patient satisfaction. Standard practices can be improved by targeting wait-time measures to patient subpopulations.