Telehealth Access and Substitution in the VHA.

BACKGROUND: In response to COVID-19, the Veterans Health Administration (VHA) expanded telehealth availability, allowing veterans to receive care at home. We explore the extent of substitution of telehealth for in-person care among medical centers (facilities), providers, and patients. We explore the extent to which patient preferences drive telehealth utilization, and compare access to care (as measured by waiting times) for telehealth and in-person visits. METHODS: We use VHA electronic health records to identify scheduled outpatient mental health (MH) appointments from January 2019 through February 2023 focusing on care delivered by social workers, psychologists, and psychiatrists. For each quarter, we compute the proportion of completed appointments that were delivered via phone or video by each facility, provider, and patient and show the changes in these proportions before, during, and after the onset of COVID-19. To explore patient preferences, we match providers of patients with high rates of telehealth utilization and examine the extent to which those providers deliver in-person care. To examine access to care, we compute waiting times for in-person, video, and phone new patient appointments. We investigate differences between urban and rural patients, and patients of different ages. KEY RESULTS: Telehealth for MH grew dramatically in the VHA after the onset of COVID-19. While some facilities provided more telehealth than others, all facilities (as of early 2023) provided some telehealth MH services. Approximately 86% of individual providers provided telehealth, with 27% scheduling MH appointments almost exclusively as telehealth appointments and 59% providing a mix. Patients exhibited more polarization, with 36% scheduling only in-person visits for almost all their MH visits and 56% of them scheduling exclusively telehealth, and only 8% of them utilizing a mix of modalities. Of those who exclusively received telehealth care, a majority of them utilized video (80%) over phone (20%). Take-up of MH among younger patients was higher relative to older patients. Urban patients used telehealth more than rural patients. Patient preferences rather than provider preferences drove utilization of patients who almost exclusively utilized telehealth. Between April 2021 and February 2023, the average difference in waiting time for in-person and video appointments was less than 1 day, with comparable appointment volumes, suggesting that the supply of and demand for in-person and video were not different enough to merit waiting longer. Telehealth was chosen over in-person more among urban and younger patients, as older and rural patients exhibited higher willingness to wait for in-person over video appointments. By contrast, appointment volumes and waiting times for phone appointments were lower across all groups, suggesting that phone may not be as substitutable for in-person visits in MH. CONCLUSIONS: We find that the VHA has made telehealth widely available, providing access to many veterans. While telehealth utilization has increased, face-to-face care persists for MH services, suggesting that one modality may not serve all purposes and preferences for care. Patient preferences drive the modality decision among those who exclusively use MH care via telehealth. For those who persist in mostly utilizing in-person care, there may be various factors influencing those preferences such as issues with limited internet connectivity, language barriers, and digital literacy, especially for older and rural patients who utilize in-person care more than those who are younger and more urban. Further investigation is required to investigate the optimal mix of modalities which may allow for potential increases in patient satisfaction, quality of care, and clinic efficiency.

Clinical effectiveness and cost-impact after 2 years of a ketogenic diet and virtual coaching intervention for patients with diabetes.

AIM: We previously evaluated the impacts at 5 months of a digitally delivered coaching intervention in which participants are instructed to adhere to a very low carbohydrate, ketogenic diet. With extended follow-up (24 months), we assessed the longer-term effects of this intervention on changes in clinical outcomes, health care utilization and costs associated with outpatient, inpatient and emergency department use in the Veterans Health Administration. MATERIALS AND METHODS: We employed a difference-in-differences model with a waiting list control group to estimate the 24-month change in glycated haemoglobin, body mass index, blood pressure, prescription medication use, health care utilization rates and associated costs. The analysis included 550 people with type 2 diabetes who were overweight or obese and enrolled in the Veterans Health Administration for health care. Data were obtained from electronic health records from 2018 to 2021. RESULTS: The virtual coaching and ketogenic diet intervention was associated with significant reductions in body mass index [-1.56 (SE 0.390)] and total monthly diabetes medication usage [-0.35 (SE 0.054)]. No statistically significant differences in glycated haemoglobin, blood pressure, outpatient visits, inpatient visits, or emergency department visits were observed. The intervention was associated with reductions in per-patient, per-month outpatient spending [-USD286.80 (SE 97.175)] and prescription drug costs (-USD105.40 (SE 30.332)]. CONCLUSIONS: A virtual coaching intervention with a ketogenic diet component offered modest effects on clinical and cost parameters in people with type 2 diabetes and with obesity or overweight. Health care systems should develop methods to assess participant progress and engagement over time if they adopt such interventions, to ensure continued patient engagement and goal achievement.

Costs and Productivity Benefits of the Department of Veterans Affairs Maintaining Internal Systems and Strengthening Integrated Outside Networks Act Scribes Trial.

OBJECTIVES: To improve access, the VA Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act of 2018 mandated a 2-year study of medical scribes in Veterans Health Administration specialty clinics and emergency departments. Medical scribes are employed in clinical settings with the goals of increasing provider productivity and satisfaction by minimizing physicians' documentation burden. Our objective is to quantify the economic outcomes of the MISSION Act scribes trial. METHODS: A cluster-randomized trial was designed with 12 Department of Veterans Affairs (VA) medical centers randomized into the intervention. We estimated the total cost of the trial, cost per scribe-year, and projected cost of hiring additional physicians to achieve the observed scribe productivity benefits in relative value units and visits per full-time-equivalent over the 2-year intervention period (June 30, 2020 to July 1, 2022). RESULTS: The estimated cost of the trial was $4.6 million, below the Congressional Budget Office estimate of $5 million. A full-time scribe-year cost approximately $74 600 through contracting and $62 900 through VA hiring. Randomization into the trial led to an approximate 30% increase in productivity in cardiology and 20% in orthopedics. The projected incremental cost of using additional physicians instead of scribes to achieve the same productivity benefits was nearly $1.7 million more, or 75% higher, than the observed cost of scribes in cardiology and orthopedics. CONCLUSIONS: As the largest randomized trial of scribes to date, the MISSION Act scribes trial provides important evidence on the costs and benefits of scribes. Improving productivity enhances access and scribes may give VA a new tool to improve productivity in specialty care at a lower cost than hiring additional providers.

Effect of the Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act Scribes Trial on Emergency Department Provider Productivity and Patient Throughput Times.

BACKGROUND: To help improve access to care, section 507 of the VA MISSION (Maintaining Internal Systems and Strengthening Integrated Outside Networks) Act of 2018 mandated a 2-year trial of medical scribes in the Veterans Health Administration (VHA). OBJECTIVE: The impact of scribes on provider productivity and patient throughput time in VHA emergency departments (EDs) was evaluated. METHODS: A clustered randomized trial was designed using intent-to-treat difference-in-differences analysis. The intervention period was from June 30, 2020 to July 1, 2022. The trial included six intervention and six comparison ED clinics. Two ED providers who volunteered to participate in the trial were assigned two scribes each. Scribes assisted providers with documentation and visit-related activities. The outcomes were provider productivity and patient throughput time per clinic-pay period. RESULTS: Randomization to intervention resulted in decreased provider productivity and increased patient throughput time. In adjusted regression models, randomization to scribes was associated with a decrease of 8.4 visits per full-time equivalent (95% confidence interval [CI] 12.4-4.3; p < 0.001) and 0.5 patients per day per provider (95% CI 0.8-0.3; p < 0.001). Intervention was associated with increases in length of stay of 29.1 min (95% CI 21.2-36.9 min; p < 0.001), 6.3 min in door to doctor (95% CI 2.9-9.6 min; p < 0.001), 19.5 min in door to disposition (95% CI 13.2-25.9 min; p < 0.001), and 13.7 min in doctor to disposition (95% CI 8.8-18.6 min; p < 0.001). CONCLUSIONS: Scribes were associated with decreased provider productivity and increased patient throughput time in VHA EDs. Although scribes may have contributed to improvements in other dimensions of quality, further examination of the ways in which scribes were used is advisable before widespread adoption in VHA EDs.

Effect of a National VHA Medical Scribe Pilot on Provider Productivity, Wait Times, and Patient Satisfaction in Cardiology and Orthopedics.

BACKGROUND: Section 507 of the VA MISSION Act of 2018 mandated a 2-year pilot study of medical scribes in the Veterans Health Administration (VHA), with 12 VA Medical Centers randomly selected to receive scribes in their emergency departments or high wait time specialty clinics (cardiology and orthopedics). The pilot began on June 30, 2020, and ended on July 1, 2022. OBJECTIVE: Our objective was to evaluate the impact of medical scribes on provider productivity, wait times, and patient satisfaction in cardiology and orthopedics, as mandated by the MISSION Act. DESIGN: Cluster randomized trial, with intent-to-treat analysis using difference-in-differences regression. PATIENTS: Veterans using 18 included VA Medical Centers (12 intervention and 6 comparison sites). INTERVENTION: Randomization into MISSION 507 medical scribe pilot. MAIN MEASURES: Provider productivity, wait times, and patient satisfaction per clinic-pay period. KEY RESULTS: Randomization into the scribe pilot was associated with increases of 25.2 relative value units (RVUs) per full-time equivalent (FTE) (p < 0.001) and 8.5 visits per FTE (p = 0.002) in cardiology and increases of 17.3 RVUs per FTE (p = 0.001) and 12.5 visits per FTE (p = 0.001) in orthopedics. We found that the scribe pilot was associated with a decrease of 8.5 days in request to appointment day wait times (p < 0.001) in orthopedics, driven by a 5.7-day decrease in appointment made to appointment day wait times (p < 0.001), and observed no change in wait times in cardiology. We also observed no declines in patient satisfaction with randomization into the scribe pilot. CONCLUSIONS: Given the potential improvements in productivity and wait times with no change in patient satisfaction, our results suggest that scribes may be a useful tool to improve access to VHA care. However, participation in the pilot by sites and providers was voluntary, which could have implications for scalability and what effects could be expected if scribes were introduced to the care process without buy-in. Cost was not considered in this analysis but is an important factor for future implementation. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04154462.

Effect of a Predictive Analytics-Targeted Program in Patients on Opioids: a Stepped-Wedge Cluster Randomized Controlled Trial.

BACKGROUND: 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. OBJECTIVE: To evaluate the impact of the case review mandate on serious adverse events (SAEs) and all-cause mortality among high-risk Veterans. DESIGN: A 23-month stepped-wedge cluster randomized controlled trial in all 140 VHA medical centers between 2018 and 2020. PARTICIPANTS: 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. INTERVENTION: A mandate requiring providers to perform case reviews on opioid analgesic-prescribed patients at high risk of overdose/suicide. MAIN MEASURES: Nine serious adverse events (SAEs), case review completion, number of risk mitigation strategies, and all-cause mortality. KEY RESULTS: 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). CONCLUSIONS: 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. TRIAL REGISTRATION: ISRCTN16012111.

Grading Evidence to Support Legislative and Budget Proposals-Veterans Health Administration's Key to Implementing the Evidence Act.

OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Regional Economic Conditions and Preventable Hospitalization Among Older Patients With Diabetes.

OBJECTIVE: 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. SUBJECTS: 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. MEASURES: 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. RESULTS: 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. CONCLUSIONS: 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.

Randomized Policy Evaluation of the Veterans Health Administration Stratification Tool for Opioid Risk Mitigation (STORM).

BACKGROUND: The Veterans Health Administration (VHA) developed a dashboard Stratification Tool for Opioid Risk Mitigation (STROM) to guide clinical practice interventions. VHA released a policy mandating that high-risk patients of an adverse event based on the STORM dashboard are to be reviewed by an interdisciplinary team of clinicians. AIM: Randomized program evaluation to evaluate if patients in the oversight arm had a lower risk of opioid-related serious adverse events (SAEs) or death compared to those in the non-oversight arm. SETTING AND PARTICIPANTS: One-hundred and forty VHA facilities (aka medical centers) were randomly assigned to two groups: oversight and non-oversight arms. VHA patients who were prescribed opioids between April 18, 2018, and November 8, 2019, were included in the cohort. PROGRAM DESCRIPTION: We hypothesized that patients cared for by VHA facilities that received the policy with the oversight accountability language would achieve lower opioid-related SAEs or death. PROGRAM EVALUATION: We did not observe a relationship between the oversight arm and opioid-related SAEs or death. Patients in the non-oversight arm had a significantly higher chance of receiving a case review compared to those in the oversight arm. DISCUSSION: Even though our findings were unexpected, the STORM policy overall was likely successful in focusing the provider's attention on very high-risk patients.

Provider supply and access to primary care.

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.

Effectiveness of a ketogenic diet and virtual coaching intervention for patients with diabetes: A difference-in-differences analysis.

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.

Vector-based kernel weighting: A simple estimator for improving precision and bias of average treatment effects in multiple treatment settings.

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 (1000 replications) to examine sensitivity of multivalued treatment inferences to propensity score weighting or matching strategies. We consider five variants of propensity score adjustment: inverse probability of treatment weights, generalized propensity score matching, kernel weights (KW), 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 KW 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 multivalued treatment analyses.

The persistence of medicare advantage spillovers in the post-Affordable Care Act era.

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 Relationship Between Follow-up Appointments and Access to Primary Care.

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 < 0.001) lower odds of reporting being able to access urgent care within 1 day and 13% (p < 0.001) lower odds of reporting usually or always being able to access routine care when needed. CONCLUSION: Facilities with higher average follow-up times are more likely to have patients report that they are unable to quickly access urgent or routine primary care.

Medicare's Bundled Payment Initiatives for Hospital-Initiated Episodes: Evidence and Evolution.

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.

Effect on VA Patient Satisfaction of Provider's Use of an Integrated Viewer of Multiple Electronic Health Records.

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 < 0.000) increased odds that patients felt their provider was knowledgeable about their medical history. When evaluating the interaction between duration of patient-provider relationship and being an early adopter of JLV, a greater effect was seen with patient-provider relationships that were greater than 3 years (adj OR 1.23, p < 0.000), compared to those less than 3 years. CONCLUSIONS: Increasing the interoperability of medical information systems has the potential to improve both patient care and patient experience of care. This study demonstrates that early adopters of an integrated view of electronic health records from multiple delivery systems are more likely to have their patients report that their clinician was knowledgeable of their medical history. With provider payments often linked to patient satisfaction performance metrics, investments in interoperability may be worthwhile.

Recommendations for the Evaluation of Cross-System Care Coordination from the VA State-of-the-art Working Group on VA/Non-VA Care.

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.

Randomized program evaluation of the Veterans Health Administration Stratification Tool for Opioid Risk Mitigation (STORM): A research and clinical operations partnership to examine effectiveness.

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.

Myopic and Forward Looking Behavior in Branded Oral Anti-Diabetic Medication Consumption: An Example from Medicare Part D.

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.

Metrics That Matter.

Increasingly, performance metrics are seen as key components for accurately measuring and improving health care value. Disappointment in the ability of chosen metrics to meet these goals is exemplified in a recent Institute of Medicine report that argues for a consensus-building process to determine a simplified set of reliable metrics. Overall health care goals should be defined and then metrics to measure these goals should be considered. If appropriate data for the identified goals are not available, they should be developed. We use examples from our work in the Veterans Health Administration (VHA) on validating waiting time and mental health metrics to highlight other key issues for metric selection and implementation. First, we focus on the need for specification and predictive validation of metrics. Second, we discuss strategies to maintain the fidelity of the data used in performance metrics over time. These strategies include using appropriate incentives and data sources, using composite metrics, and ongoing monitoring. Finally, we discuss the VA's leadership in developing performance metrics through a planned upgrade in its electronic medical record system to collect more comprehensive VHA and non-VHA data, increasing the ability to comprehensively measure outcomes.