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Medicare private fee-for-service (PFFS) plans are paid like other Medicare Advantage (MA) plans but are exempt from many MA requirements. Recently, Congress set average payments well above the costs of traditional fee-for-service (FFS) Medicare, inducing dramatic increases in PFFS plan enrollment. This has significant implications for Medicare's budget, provoking calls for policy change. We predict the effect of proposals to cut PFFS payments on PFFS plan participation and enrollment. We find that small reductions in payment rates would reduce PFFS participation and enrollment; if Congress reduces payments to traditional FFS levels it would cause the vast majority (85 percent) of PFFS plans to exit the market. [ABSTRACT FROM AUTHOR]

Objective: To estimate a causal relationship between mental health staffing and time to initiation of mental health care for new patients., Data Sources and Study Setting: As the largest integrated health care delivery system in the United States, the Veterans Health Administration (VHA) provides a unique setting for isolating the effects of staffing on initiation of mental health care where demand is high and out-of-pocket costs are not a relevant confounder. We use data from the Department of Defense and VHA to obtain patient and facility characteristics and health care use., Study Design: To isolate exogenous variation in mental health staffing, we used an instrumental variables approach-two-stage residual inclusion with a discrete time hazard model. Our outcome is time to initiation of mental health care after separation from active duty (first appointment) and our exposure is mental health staffing (standardized clinic time per 1000 VHA enrollees per pay period)., Data Collection/extraction Methods: Our cohort consists of all Veterans separating from active duty between July 2014 and September 2017, who were enrolled in the VHA, and had at least one diagnosis of post-traumatic stress disorder, major depressive disorder, and/or substance use disorder in the year prior to separation from active duty (N = 54,209)., Principal Findings: An increase of 1 standard deviation in mental health staffing results in a higher likelihood of initiating mental health care (adjusted hazard ratio: 3.17, 95% confidence interval: 2.62, 3.84, p < 0.001). Models stratified by tertile of mental health staffing exhibit decreasing returns to scale., Conclusions: Increases in mental health staffing led to faster initiation of care and are especially beneficial in facilities where staffing is lower, although initiation of care appears capacity-limited everywhere., (© 2024 The Author(s). Health Services Research published by Wiley Periodicals LLC on behalf of Health Research and Educational Trust.)

Objective: The objective of this analysis was to evaluate the effect of resident program training size on clinician productivity and turnover in the Veterans Health Administration (VHA), the largest education and training platform for medical professionals in the United States., Data Sources: We retrieved administrative data on training programs and training facilities from the VA Office of Academic Affiliations and the VHA Corporate Data Warehouse. Data on primary care physician shortage areas were retrieved from the Health Resources and Services Administration., Study Design: We used a quasi-experimental instrumental variables 2SLS design and constructed an exogenous predicted training allocation treatment variable as a function of the total national training program allocation. The outcome was clinical staff productivity and turnover. Secondary analyses stratified results using Health Professional Shortage Areas data (HPSA)., Data Collection/extraction Methods: Data were obtained for a national dataset of 141 VHA medical facilities and 26 specialties that hosted training programs across 11 years from 2011 to 2021 (N = 132,177)., Principal Findings: Instrumental variables results showed that on average, an increase of one training slot in a specialty leads to a decrease of 0.039 visits per standardized clinic day (p < 0.001) and a 0.02 percentage point increase in turnover (p < 0.001). The direction of this association varied by specialty: while psychiatry and psychology specialties saw a decline in productivity, fields such as primary care and cardiology experienced an increase in productivity. HPSA stratified results indicate that negative effects on productivity and turnover are driven by areas with little to no primary care physician shortage, whereas shortage areas experienced a small increase in productivity and no effect on turnover., Conclusions: This quasi-experimental evaluation indicates that resident training program size is associated with reduced productivity and increased turnover in specialties such as psychiatry and in facilities with high baseline productivity. However, in specialties like primary care and cardiology, as well as areas with shortages of primary care, larger training programs are associated with increased productivity., (© 2024 Health Research and Educational Trust.)

Objective: To investigate whether the Veterans Health Administration's (VA) 2019 Referral Coordination Initiative (RCI) was associated with changes in the proportion of VA specialty referrals completed by community-based care (CC) providers and mean appointment waiting times for VA and CC providers., Data Sources/study Settings: Monthly facility level VA data for 3,097,366 specialty care referrals for eight high-volume specialties (cardiology, dermatology, gastroenterology, neurology, ophthalmology, orthopedics, physical therapy, and podiatry) from October 1, 2019 to May 30, 2022., Study Design: We employed a staggered difference-in-differences approach to evaluate RCI's effects on referral patterns and wait times. Our unit of analysis was facility-month. We dichotomized facilities into high and low RCI use based on the proportion of total referrals for a specialty. We stratified our analysis by specialty and the staffing model that high RCI users adopted: centralized, decentralized, and hybrid., Data Collection/extraction Methods: Administrative data on referrals and waiting times were extracted from the VA's corporate data warehouse. Data on staffing models were provided by the VA's Office of Integrated Veteran Care., Principal Findings: We did not reject the null hypotheses that high RCI use do not change CC referral rates or waiting times in any of the care settings for most specialties. For example, high RCI use for physical therapy-the highest volume specialty studied-was associated with -0.054 (95% confidence interval [CI]: -0.114 to 0.006) and 2.0 days (95% CI: -4.8 to 8.8) change in CC referral rate and waiting time at CC providers, respectively, among centralized staffing model adopters., Conclusions: In the initial years of the RCI program, RCI does not have a measurable effect on waiting times or CC referral rates. Our findings do not support concerns that RCI might be impeding Veterans' access to CC providers. Future evaluations should examine whether RCI facilitates Veterans' ability to receive care in their preferred setting., (© 2024 Health Research and Educational Trust.)

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., (© 2024. The Author(s).)

Objective: To develop and validate a measure of provider network restrictiveness in the Medicare Advantage (MA) population., Data Sources: Prescription drug event data and beneficiary information for Part D enrollees from the Center for Medicare and Medicaid Services, along with prescriber identifiers; geographic variables from the Area Health Resources Files., Study Design: A prediction model was used to predict the unique number of primary care providers that would have been seen by MA beneficiaries absent network restrictions. The model was trained and validated on Traditional Medicare (TM) beneficiaries. A pseudo-Poisson and a random forest model were evaluated. An observed-to-expected (O/E) ratio was calculated as the number of unique providers seen by MA beneficiaries divided by the number expected based the TM prediction model. Multivariable linear models were used to assess the relationship between network restrictiveness and plan and market factors., Data Collection/extraction Methods: Prescription drug event data were obtained for a 20% random sample of beneficiaries enrolled in prescription drug coverage from 2011 to 2017., Principal Findings: Health Maintenance Organization plans were more restrictive (O/E = 55.5%; 95% CI 55.3%-55.7%) than Health Maintenance Organization-Point of Service plans (67.2%; 95% CI 66.7%-67.8%) or Preferred Provider Organization plans (74.7%; 95% CI 74.3%-75.1%), and rural areas had more restrictive networks (31.6%; 95% CI 29.0%-34.2%) than metropolitan areas (61.5%; 95% CI 61.3%-61.7%). Multivariable results confirmed these findings, and also indicated that increased provider supply was associated with less restrictive networks., Conclusions: We developed a means of estimating provider network restrictiveness in MA from claims data. Our results validate the approach, providing confidence for wider application (e.g., for other markets and specialties) and use for regulation., (© 2023 Health Research and Educational Trust.)

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., (© 2023. The author(s).)

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., (Copyright © 2023. Published by Elsevier Inc.)

Objective: To investigate the relationship between community care (CC) treatment and a postoperative surgical complication in elective hernia surgery among Veterans using multiple approaches to control for potential selection bias., Data Sources and Study Setting: Veterans Health Administration (VHA) data sources included Corporate Data Warehouse (VHA encounters and patient data), the Program Integrity Tool and Fee tables (CC encounters), the Planning Systems Support Group (geographic information), and the Paid file (VHA primary care providers)., Study Design: Prior works suggest patient outcomes are better in VHA than in CC settings; however, these studies may not have appropriately accounted for the selection of higher-risk cases into CC. We estimated (1) a naïve logistic regression model to calculate the effect of CC setting on the probability of a complication, controlling for facility fixed effects and patient and procedure characteristics, and (2) a 2-stage model using the hernia patient's primary care provider's 1-year prior CC referral rate as the instrument., Data Collection: We identified patients residing ≤40 miles from a VHA surgical facility with elective VHA or CC hernia surgery from 2018 to 2019., Principal Findings: Of 7991 hernia surgeries, 772 (9.7%) were in CC. The overall complication rate was 4.2%; 286/7219 (4.0%) among VHA surgeries versus 51/5772 (6.6%, p < 0.05) in CC. We observed a 2.8 percentage point increase in the probability of postoperative complication given CC surgery (95% confidence interval: 0.7, 4.8) in the naïve model. After accounting for the VHA provider's historical rate of CC referral, we no longer observed a relationship between surgery setting and risk of postoperative complication., Conclusions: After accounting for the selection of higher-risk patients to CC settings, we found no difference in hernia surgery postoperative complications between CC and VHA. Future VHA and non-VHA comparisons should account for unobserved as well as observed differences in patients seen in each setting., (Published 2022. This article is a U.S. Government work and is in the public domain in the USA.)

Background: Care leakage from health systems can affect quality and cost of health care delivery. Identifying modifiable predictors of care leakage may help health systems avoid adverse consequences. Out-of-system emergency department (ED) use may be one modifiable cause of care leakage. Our objective was to investigate the relationship between out-of-system ED use and subsequent specialty care leakage., Methods: We used the Veterans Health Administration's (VA) Corporate Data Warehouse data from January 2021 to July 2021. A total of 330,547 patients who had at least one ED visit (in-house or community care [CC]) in the index period (January 2021-March 2021) were included. Outcomes were the proportions of specialty care visits in the community within 30, 60, 90, and 120 days from the index ED visit. Instrumental-variables regressions, using VA ED physician capacity as an instrument for Veterans' CC ED use, were utilized to estimate the proportions of subsequent specialty care visits in the community. Estimates were adjusted for patient and facility characteristics., Results: A CC ED visit was associated with increases in the proportions of specialty care visits in the community within 30, 60, 90, and 120 days from index visit. Within 30 days from index visit, CC ED patients were estimated to have a 45-percentage-point (pp; 95% confidence interval [CI], 43-47 pp) higher proportion of CC specialty care visits than patients with an in-house ED visit (p < 0.001). We observed similar, though slightly attenuated, results over long time periods since the index visit., Conclusions: Veterans who have a CC ED visit have a greater proportion of subsequent specialty care visits in CC hospitals and clinics than Veterans with a VA ED visit. This relationship persists when we examine Veterans whose decision to go to a CC ED is influenced by VA ED physician capacity rather than general preferences for CC., (© 2023 Society for Academic Emergency Medicine.)

Objective: To estimate the effects of changes in Veterans Health Administration (VHA) mental health services staffing levels on suicide-related events among a cohort of Veterans., Data Sources: Data were obtained from the VHA Corporate Data Warehouse, the Department of Defense and Veterans Administration Infrastructure for Clinical Intelligence, the VHA survey of enrollees, and customized VHA databases tracking suicide-related events. Geographic variables were obtained from the Area Health Resources Files and the Centers for Medicare and Medicaid Services., Study Design: We used an instrumental variables (IV) design with a Heckman correction for non-random partial observability of the use of mental health services. The principal predictor was a measure of provider staffing per 10,000 enrollees. The outcome was the probability of a suicide-related event., Data Collection/extraction Methods: Data were obtained for a cohort of Veterans who recently separated from active service., Principal Findings: From 2014 to 2018, the per-pay period probability of a suicide-related event among our cohort was 0.05%. We found that a 1% increase in mental health staffing led to a 1.6 percentage point reduction in suicide-related events. This was driven by the first tertile of staffing, suggesting diminishing returns to scale for mental health staffing., Conclusions: VHA facilities appear to be staffing-constrained when providing mental health care. Targeted increases in mental health staffing would be likely to reduce suicidality., (© 2022 Health Research and Educational Trust.)

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., (© 2022. The Author(s), under exclusive licence to Society of General Internal Medicine.)

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., (© 2022. The Author(s), under exclusive licence to Society of General Internal Medicine.)

Objective: 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., Data Sources: 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 Medicare & Medicaid Services., Study Design: 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., Data Collection/extraction Methods: 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., Principal Findings: 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., Conclusions: 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., (© 2022 Health Research and Educational Trust.)

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.

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., (© 2020 Milbank Memorial Fund.)

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.

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.

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.

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., Competing Interests: This study was approved by the VA Boston IRB prior to data collection and analysis. Given the retrospective nature of the work, waiver of consent was obtained.Not applicable.KI Received an investigator-initiated award from Pfizer to study the epidemiology of Staphylococcus aureus surgical site infections. All other authors have no conflicts to report.Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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., (© Health Research and Educational Trust.)

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.

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., (Published 2018. This article is a U.S. Government work and is in the public domain in the USA.)

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., (Published 2018. This article is a U.S. Government work and is in the public domain in the USA.)

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., (© Health Research and Educational Trust.)

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., (Published 2018. This article is a U.S. Government work and is in the public domain in the USA.)

Introduction: There is an epidemic of opioid use related to adverse events and deaths in the USA. The rates of chronic pain, mental illness and substance use disorder are higher at the Veterans Health Administration (VHA) compared with the general US population. The 2016 Comprehensive Addiction and Recovery Act requires the VHA to improve opioid therapy strategies in treating patients and to ensure responsible prescribing practices. The Stratification Tool for Opioid Risk Mitigation (STORM) is a web-based dashboard that prioritises review of VHA patients receiving opioids based on their risk. The VHA Partnered Evidence-based Policy Resource Center is coordinating a multiyear evaluation of STORM and aspects of the VHA policy that mandate case review of patients identified by STORM as very high risk., Methods and Analysis: This stepped-wedge cluster randomised controlled trial will test two hypotheses: (1) VHA medical centres randomised to facilitation for not meeting the targeted case review rate will achieve lower opioid-related serious adverse events (SAEs), relative to facilities not randomised to facilitation and (2) Patients whose cases are required to be reviewed will have a lower rate of opioid-related SAEs compared with comparable risk patients whose cases are not required to be reviewed. Patients who receive an opioid prescription at VHA medical centres will be followed for a minimum of 3 months after their first opioid prescription. Follow-up will continue until the last day of the project or death. The data will be analysed using an intention-to-treat approach with patient-month-level Cox proportional hazards models for both interventions., Ethics and Dissemination: Evaluation of the randomised roll-out was approved by the VA Boston Healthcare System Institutional Review Board (IRB) and Research & Development Committees (Protocol # 3069). Findings will be published in peer-reviewed journals and presentations at national conference meetings., Trial Registration Number: ISRCTN16012111., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

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.

Objectives: The Medicare accountable care organization (ACO) program financially rewards ACOs for providing high-quality healthcare, and also factors in the patient experience of care. This study examined whether administrative measures of wait times for specialist consults are associated with self-reported patient satisfaction., Study Design: Analyses used administrative and survey data from a clinically integrated healthcare system similar to an ACO., Methods: Veterans Health Administration (VHA) data from 2012 was obtained. Administrative access metrics included the number of days between the creation of the consult request and: 1) first action taken on the consult, 2) scheduling of the consult, and 3) completion of the consult. The Survey of Healthcare Experiences of Patients-which is modeled after the Consumer Assessment of Healthcare Providers and Systems family of survey instruments used by ACOs to measure patient experience-provided the outcome measures. Outcomes included general VHA satisfaction measures and satisfaction with timeliness of care, including wait times for specialists and treatments. Logistic regression models predicted the likelihood of patients reporting being satisfied on each outcome. Models were risk adjusted for demographics, self-reported health, and healthcare use., Results: Longer waits for the scheduling of consults and completed consults were found to be significantly associated with decreased patient satisfaction., Conclusions: Because patients often report high levels of powerlessness and uncertainty while waiting for consultation, these wait times are an important patient-centered access metric for ACOs to consider. ACOs should have systems and tools in place to streamline the specialist consult referral process and increase care coordination., Competing Interests: Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

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., (© Health Research and Educational Trust.)

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.

Background: Accurate estimates of the effects of cost sharing on adherence to medications prescribed for use together, also called concurrent adherence, are important for researchers, payers, and policymakers who want to reduce barriers to adherence for chronic condition patients prescribed multiple medications concurrently. But measure definition consensus is lacking, and the effects of different definitions on estimates of cost-related nonadherence are unevaluated., Objectives: To (a) compare estimates of cost-related nonadherence using different measure definitions and (b) provide guidance for analyses of the effects of cost sharing on concurrent adherence., Methods: This is a retrospective cohort study of Medicare Part D beneficiaries aged 65 years and older who used multiple oral antidiabetics concurrently in 2008 and 2009. We compared patients with standard coverage, which contains cost-sharing requirements in deductible (100%), initial (25%), and coverage gap (100%) phases, to patients with a low-income subsidy (LIS) and minimal cost-sharing requirements. Data source was the IMS Health Longitudinal Prescription Database. Patients with standard coverage were propensity matched to controls with LIS coverage. Propensity score was developed using logistic regression to model likelihood of Part D standard enrollment, controlling for sociodemographic and health status characteristics. For analysis, 3 definitions were used for unadjusted and adjusted estimates of adherence: (1) patients adherent to All medications; (2) patients adherent on Average; and (3) patients adherent to Any medication. Analyses were conducted using the full study sample and then repeated in analytic subgroups where patients used (a) 1 or more costly branded oral antidiabetics or (b) inexpensive generics only., Results: We identified 12,771 propensity matched patients with Medicare Part D standard (N = 6,298) or LIS (N = 6,473) coverage who used oral antidiabetics in 2 or more of the same classes in 2008 and 2009. In this sample, estimates of the effects of cost sharing on concurrent adherence varied by measure definition, coverage type, and proportion of patients using more costly branded drugs. Adherence rates ranged from 37% (All: standard patients using 1+ branded) to 97% (Any: LIS using generics only). In adjusted estimates, standard patients using branded drugs had 0.63 (95% CI = 0.57-0.70) and 0.70 (95% CI = 0.63-0.77) times the odds of concurrent adherence using All and Average definitions, respectively. The Any subgroup was not significant (OR = 0.89, 95% CI = 0.87-1.17). Estimates also varied in the full-study sample (All: OR = 0.79, 95% CI = 0.74-0.85; Average: OR = 0.83, 95% CI = 0.77-0.89) and generics-only subgroup, although cost-sharing effects were smaller. The Any subgroup generated no significant estimates., Conclusions: Different concurrent adherence measure definitions lead to markedly different findings of the effects of cost sharing on concurrent adherence, with All and Average subgroups sensitive to these effects. However, when more study patients use inexpensive generics, estimates of these effects on adherence to branded medications with higher cost-sharing requirements may be diluted. When selecting a measure definition, researchers, payers, and policy analysts should consider the range of medication prices patients face, use a measure sensitive to the effects of cost sharing on adherence, and perform subgroup analyses for patients prescribed more medications for which they must pay more, since these patients are most vulnerable to cost-related nonadherence.

Background: Long-acting insulin analogues (eg, insulin glargine and insulin detemir) are an alternative to neutral protamine Hagedorn (NPH) insulin for maintaining glycemic control in patients with diabetes. Clinical trials comparing analogue insulin and NPH have neither been adequately powered nor had sufficient follow-up to examine long-term health outcomes., Objectives: To compare the effects of NPH and long-acting insulin analogues on long-term outcomes., Study Design: This retrospective observational study relied on administrative data from the Veterans Health Administration and Medicare from 2000 to 2010. Local variations in analogue insulin prescribing rates were used in instrumental variable models to control for confounding. Outcomes were assessed using survival models., Methods: The study population included US veterans dually enrolled in Medicare who received at least 1 prescription for oral diabetes medication and then initiated long-acting insulin between 2001 and 2009. Outcomes included ambulatory care-sensitive condition (ACSC) hospitalizations and mortality., Results: There was no significant relationship between type of insulin and ACSC hospitalization or mortality. The hazard ratio for mortality of individuals starting a long-acting analogue insulin was 0.97 (95% CI, 0.85-1.11), and was 1.05 (95% CI, 0.95-1.16) for ACSC hospitalization. Differences in risk remained insignificant when predicting diabetes-specific ACSC hospitalizations, but starting on long-acting analogue insulin significantly increased the risk of a cardiovascular-specific ACSC hospitalization., Conclusions: We found no consistent difference in long-term health outcomes when comparing use of long-acting insulin analogues and NPH insulin. The higher cost of analogue insulin without demonstrable clinical benefit raises questions of its cost-effectiveness in the treatment of patients with diabetes.

Background: Clinical trials often compare hypoglycemic medications on the basis of glycemic control but do not examine long-term outcomes (e.g., mortality). This study demonstrates an alternative approach to lengthening clinical trials to assess these long-term outcomes., Objective: To use observational quasi-experimental methods using instrumental variables (IVs) to compare the effect of two hypoglycemic medications, sulfonylureas (SUs) and thiazolidinediones (TZDs), on long-term outcomes., Methods: This study used administrative data from the Veterans Health Administration and Medicare from 2000 to 2010. The study population included US veterans dually enrolled in Medicare who received a prescription for metformin and then initiated SUs or TZDs. Patients could either continue on or discontinue metformin after the initiation of the second agent. Treatment was defined as starting either a SU or a TZD. Local variations in SU prescribing rates were used as instruments in IV models to control for selection bias. Survival models predicted all-cause mortality, ambulatory care sensitive condition hospitalizations, and stroke or heart attack (acute myocardial infarction)., Results: Starting on SUs compared to TZDs significantly increased the likelihood of experiencing mortality and ACSC hospitalization. The estimated hazard ratio for the effect of starting on SUs compared to TZDs was 1.50 (95% confidence interval [CI] 1.09-2.09) for all-cause mortality, 1.68 (95% CI 1.31-2.15) for ambulatory care sensitive condition hospitalization, and 1.15 (95% CI 0.80-1.66) for acute myocardial infarction or stroke., Conclusions: Our findings suggest increased risk of major adverse events associated with SUs as a second-line agent. Quasi-experimental IV methods may be an important alternative to lengthening clinical trials to assess long-term outcomes., (Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.)

Objective: To investigate how integration between Medicare Advantage plans and health care providers is related to plan premiums and quality ratings., Data Source: We used public data from the Centers for Medicare and Medicaid Services (CMS) and the Area Resource File and private data from one large insurer. Premiums and quality ratings are from 2009 CMS administrative files and some control variables are historical., Study Design: We estimated ordinary least-squares models for premiums and plan quality ratings, with state fixed effects and firm random effects. The key independent variable was an indicator of plan-provider integration., Data Collection: With the exception of Medigap premium data, all data were publicly available. We ascertained plan-provider integration through examination of plans' websites and governance documents., Principal Findings: We found that integrated plan-providers charge higher premiums, controlling for quality. Such plans also have higher quality ratings. We found no evidence that integration is associated with more generous benefits., Conclusions: Current policy encourages plan-provider integration, although potential effects on health insurance products and markets are uncertain. Policy makers and regulators may want to closely monitor changes in premiums and quality after integration and consider whether quality improvement (if any) justifies premium increases (if they occur)., (© Health Research and Educational Trust.)

Background: Medicare payment reforms will reimburse accountable care organizations (ACOs) for providing high-quality healthcare. Quality measures that reliably predict health outcomes are required., Objectives: To compare the ability of alternative wait time measures to predict glycated hemoglobin (A1C) levels among diabetes patients., Study Design: This retrospective observational study relied on Veterans Health Administration utilization data and Medicare claims data from 2005 to 2010., Methods: Outcomes included an average A1C level and uncontrolled A1C. Heckman selection models simultaneously predicted the presence of an A1C value and its level. Models were risk adjusted for prior individual health status. The main explanatory variables of interest were facility-level primary care wait times measured in days. Several measures were tested, including capacity measures and retrospective and prospective time stamp measures. The time stamp measures used either the date the appointment was created in the scheduling system (create date) or the date the patient or provider desired the appointment (desired date) as the start date for wait time computation. All measures were calculated separately for new and returning patients., Results: New patient capacity and create date measures significantly predicted outcomes, but desired date measures did not. The returning patient retrospective create date and desired date wait time measures significantly predicted higher and uncontrolled A1C, but capacity and prospective create date measures did not., Conclusions: Different administrative wait times predict A1C for new and returning patients. To properly measure quality, ACOs should use wait time measures that demonstrate relationships with outcomes for subpopulations of patients.

Background: Although the Medicare Part D coverage gap phase-out should reduce cost-related nonadherence (CRN) among seniors with diabetes, preferential generic prescribing may have already decreased CRN, while smaller numbers of patients using more costly branded oral anti-diabetic (OAD) medications remain vulnerable to CRN., Objective: To estimate the effects of cost sharing in the Part D standard (non-LIS) benefit on adherence to different OAD classes, comparing two classes dominated by inexpensive generic medications and two by more costly branded medications., Design and Patients: Retrospective cohort study using dispensed prescription data for elderly non-LIS (N=81,047) and LIS (low-income subsidy) (N=150,359) beneficiaries using same class OAD(s) in 2008 and 2009. Logistic regression modeled non-LIS likelihood; LIS and non-LIS patients matched using propensity outcome (N=38,054). Logistic regression, controlling for demographic and health status characteristics, modeled effects of non-LIS coverage on 2009 OAD class adherence., Main Measures: Main outcome measures were within-class OAD coverage year adherence, with patients considered adherent when days supplied to calendar days ratio at least 0.8., Key Results: Non-LIS patients had 0.52 and 0.57 times the odds of branded-only DPP-4 Inhibitor (N=1,812; 95 % CI: 0.43, 0.63; P<0.001) and Thiazolidinedione (TZD) (N=6,290; 95 % CI: 0.52, 0.63; P<0.001) adherence. Most patients (N=32,510; 82 %) used OADs in primarily generic classes, where we found no significant (Biguanides; N=21,377) or small differences (Sulfonylureas/Glinides [N=19,240; OR: 0.91; 95 % CI: 0.86, 0.97; P=0.002]) in adherence odds. Crude adherence rates were sub-optimal when CRN was not a factor (Non-LIS/LIS: Biguanides: 65 %/65 %; Sulfonylureas/Glinides: 66 %/68 %; LIS: DPP-4 Inhibitors: 66 %; TZDs: 67 %)., Conclusions: Gap elimination would not affect generic, but should reduce branded OAD CRN. Branded copayments may continue to lead to CRN. Policy initiatives and benefit changes targeting both cost deterrents for patients with more complex disease and non-cost generic OAD underuse are recommended.

Private insurance firms participating in Medicare can offer up to three principal plan types: coordinated care plans (CCPs), prescription drug plans (PDPs), and private fee-for-service (PFFS) plans. Firms can make entry and marketing decisions separately across plan types and geographic regions. In this study, we estimate firm-level models of Medicare private plan entry using data from the years 2007 to 2009. Our models include a measure of market structure and separately identify CCP, PDP, and PFFS entry. We find evidence that entry barriers associated with CCP market concentration affect all three product types. We also find evidence of cross-product competition and common cost or demand factors that make entry with certain product combinations more likely. We predict that the market presence of CCPs and PFFS plans will decrease and that of PDPs will increase in response to payment reductions included in the new health reform law.

Objective: The aim of this study was to measure the relationship between days spent waiting for primary care and health outcomes among patients diagnosed with diabetes, especially among the elderly population., Data Source: Secondary data from VA administrative databases and Medicare claims., Study Design: This is a retrospective observational study. Outcome variables include primary care utilization, mortality, heart attack, stroke, and ambulatory-care sensitive condition (ACSC) hospitalization. The main explanatory variable of interest is VA primary care wait time. Negative binomial models predict utilization and stacked logistic regression models predict the probability of experiencing each health outcome. Models are stratified by the presence of a selected health condition and age., Principal Findings: Longer wait times were predicted to decrease utilization between 2 and 4 percent. There was no significant relationship between wait times and health outcomes for the overall sample. In stratified analyses, longer waits were associated with undesirable outcomes for those over age 70 with one of the selected health conditions or in certain narrower 5-year age groups, but the overall pattern of results does not indicate a systematic and significant effect., Conclusions: There was a modest effect of long wait times on primary care utilization but no robust effect of longer wait times on health outcomes. Waiting for care did not significantly compromise long-term health outcomes for veterans with diabetes., (© Health Research and Educational Trust.)

National health reform is expected to increase how long individuals have to wait between requests for appointments and when their appointment is scheduled. The increase in demand for care due to more widespread insurance will result in longer waits if there is not also a concomitant increase in supply of healthcare services. Long waits for healthcare are hypothesized to compromise health because less frequent outpatient visits result in delays in diagnosis and treatment. Research testing this hypothesis is scarce due to a paucity of data on how long individuals wait for healthcare in the United States. The main exception is the Veterans Health Administration (VA) that has been routinely collecting data on how long veterans wait for outpatient care for over a decade. This narrative review summarizes the results of studies using VA wait time data to answer two main questions: 1) How much do longer wait times decrease healthcare utilization and 2) Do longer wait times cause poorer health outcomes? Longer VA wait times lead to small, yet statistically significant decreases in utilization and are related to poorer health in elderly and vulnerable veteran populations. Both long-term outcomes (e.g. mortality, preventable hospitalizations) and intermediate outcomes such as hemoglobin A1C levels are worse for veterans who seek care at facilities with longer waits compared to veterans who visit facilities with shorter waits. Further research is needed on the mechanisms connecting longer wait times and poorer outcomes including identifying patient sub-populations whose risks are most sensitive to delayed access to care. If wait times increase for the general patient population with the implementation of national reform as expected, U.S. healthcare policymakers and clinicians will need to consider policies and interventions that minimize potential harms for all patients.

Americans finance health care through a variety of private insurance plans and public programs. This organizational fragmentation could threaten continuity of care and adversely affect outcomes. Using a large sample of veterans who were eligible for mixtures of Veterans Health Administration- and Medicare-financed care, we estimate a system of equations to account for simultaneity in the determination of financing configuration and the probability of hospitalization for an ambulatory care sensitive condition. We find that a change of one standard deviation in financing fragmentation increases the risk of an adverse outcome by one-fifth.

Objective: To examine the relationship between glycated hemoglobin (A1C) levels and the number of days spent waiting for primary care appointments., Study Design: Retrospective observational study that relied on Department of Veterans Affairs (VA) utilization data and Medicare claims data from 2001 to 2003. The outcome was A1C levels. The main explanatory variable of interest was facility-level primary care wait times measured in days., Methods: Heckman selection models simultaneously predicted the presence of an A1C value and its level. Models were risk adjusted for prior individual health status. Separate models were estimated on the entire sample and on subsamples stratified by baseline A1C levels., Results: Veterans who visited VA facilities with wait times of longer than 32.5 days had small significant increases in A1C levels of 0.14 percentage point for the whole sample, 0.07 percentage point for patients with baseline A1C levels less than 7%, 0.11 percentage point for patients with baseline A1C levels between 7% and 8%, and 0.18 percentage point for patients with baseline A1C levels greater than 8%., Conclusions: Decreasing wait times has the potential to reduce A1C levels by 0.18 percentage point for patients with baseline A1C levels exceeding 8%. This effect is roughly one-third of what is achieved with the most successful existing quality improvement strategies. Ensuring timely access to outpatient care could be an important addition to future diabetes care quality improvement programs.

The Medicare Modernization Act of 2003 added a new outpatient prescription drug benefit to Medicare and increased payments to HMOs. We estimate a nested logit model of plan choice to quantify the welfare benefits from these two expansion paths. We find that the addition of stand-alone prescription drug plans was welfare improving and produced nine times as much value per government dollar as the increase in payments to HMOs. In light of these results, we suggest that HMO bidding procedures should be modified to reduce payments to HMOs by about $67 billion over the next 10 years.