Disparities in Access to Outpatient Surgery Related to Removal of Procedures from Medicare's Inpatient Only List.

OBJECTIVE: We assessed the shift from inpatient to outpatient surgical care related to changes to the Inpatient Only List in 2020 and 2021 compared to 2019. SUMMARY BACKGROUND DATA: The extent to which procedures shift from the inpatient to outpatient setting following removal from Medicare's Inpatient Only List is unknown. Many health systems also encouraged a shift from inpatient to outpatient surgery during the COVID-19 pandemic. Assessing the relative change in outpatient surgical utilization for procedures removed from the Inpatient Only List during COVID-19 would provide empirical data on whether reimbursement policy changes or inpatient capacity needs during the pandemic were more likely to shift care from the inpatient to outpatient setting. METHODS: We used administrative data from the PINC AI Healthcare Database across 723 hospitals to determine the within-facility relative change in outpatient vs inpatient procedural volume in 2020 and 2021 compared to 2019 using a multivariable conditional fixed-effects Poisson regression model. We also assessed whether outpatient surgical utilization varied by race and ethnicity. Using a multivariable linear probability model, we assessed the absolute change in risk-adjusted 30-day complication, readmission, and mortality rates for inpatient and outpatient surgical procedures. RESULTS: In 2020 and 2021 compared to 2019 respectively, there was a 5.3% (95% CI, 1.4% to 9.5%) and 41.3% (95% CI 33.1% to 50.0%) relative increase in outpatient elective procedural volume. Outpatient procedural volume increased most significantly for hip replacement which was removed from the Inpatient Only List in 2020 (increase in outpatient surgical utilization of 589.3% (95% CI, 524.9% to 660.3%)). The shift to outpatient hip replacement procedures was concentrated among White patients; in 2021, hip replacement procedural volume increased by 271.1% (95% CI, 241.2% and 303.7%) for White patients and 29.5% (95% CI, 24.4% and 34.9%) for Black patients compared to 2019 levels. There were no consistent or large changes in 30-day complication, readmission, or mortality risk in 2020 and 2021 compared to 2019. CONCLUSION: There was a modest increase in elective outpatient surgeries and a pronounced increase in outpatient orthopedic surgeries which were removed from the Inpatient Only List during the COVID-19 pandemic. Utilization of outpatient surgical procedures was concentrated among White patients.

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.

Differences in adverse outcomes across race and ethnicity among Veterans with similar predicted risks of an overdose or suicide-related event.

OBJECTIVE: To evaluate the degree to which differences in incidence of mortality and serious adverse events exist across patient race and ethnicity among Veterans Health Administration (VHA) patients receiving outpatient opioid prescriptions and who have similar predicted risks of adverse outcomes. Patients were assigned scores via the VHA Stratification Tool for Opioid Risk Mitigation (STORM), a model used to predict the risk of experiencing overdose- or suicide-related health care events or death. Individuals with the highest STORM risk scores are targeted for case review. DESIGN: Retrospective cohort study of high-risk veterans who received an outpatient prescription opioid between 4/2018-3/2019. SETTING: All VHA medical centers. PARTICIPANTS: In total, 84 473 patients whose estimated risk scores were between 0.0420 and 0.0609, the risk scores associated with the top 5%-10% of risk in the STORM development sample. METHODS: We examined the expected probability of mortality and serious adverse events (SAEs; overdose or suicide-related events) given a patient's risk score and race. RESULTS: Given a similar risk score, Black patients were less likely than White patients to have a recorded SAE within 6 months of risk score calculation. Black, Hispanic, and Asian patients were less likely than White patients with similar risk scores to die within 6 months of risk score calculation. Some of the mortality differences were driven by age differences in the composition of racial and ethnic groups in our sample. CONCLUSIONS: Our results suggest that relying on the STORM model to identify patients who may benefit from an interdisciplinary case review may identify patients with clinically meaningful differences in outcome risk across race and ethnicity.

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.

Impact of Mandated Case Review Policy on Opioid Discontinuation and Mortality Among High-Risk Long-Term Opioid Therapy Patients: The STORM Stepped-Wedge Cluster Randomized Controlled Trial.

BACKGROUND: Although long-term opioid therapy (LTOT) has its own risks, opioid discontinuation could pose harm for high-risk Veterans Health Administration (VHA) patients receiving LTOT. There is limited information on the impact of a mandate requiring providers to perform case reviews on high-risk patients with an active opioid prescription (ie, mandated case review policy) on opioid discontinuation and mortality. METHODS: Our study is a secondary data analysis of a 23-month stepped-wedge cluster randomized controlled trial between April 2018 and March 2020. The study included 10 685 LTOT patients with a predicted risk of a serious adverse event between the top 1% to 5% nationally who entered the risk range between 4/18/2018 and 11/9/2019. We examined whether the mandated case review policy had an impact on opioid discontinuation and mortality for the patients. RESULTS: Among 10 685 LTOT patients (88.2% male; mean [SD] age, 61.1 [11.7] years), 29.1% experienced discontinuation and the mortality rate was 9.5%. Patients under mandated case review had a decreased risk of opioid discontinuation (average marginal effect [AME], -11.16 [95% CI, -15.30 to -7.01] percentage points) and all-cause mortality (AME, -3.31 [95% CI, -5.63 to -1.00] percentage points), relative to patients who were not under the mandate. CONCLUSIONS: The VHA mandated case review policy was associated with lower probability of discontinuation and all-cause mortality for high-risk patients receiving LTOT. Interventions that maintain care engagement while optimizing pain management for high-risk patients may be beneficial for minimizing mortality and other risks associated with discontinuation.

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.

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.

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.

Opioid Discontinuation Among Patients Receiving High-Dose Long-Term Opioid Therapy in the Veterans Health Administration.

BACKGROUND: Prior opioid discontinuation studies have focused on one of two characteristics of opioid prescribing, its duration (long term vs not) or dosage (high vs low). Questions remain about the experience of patients with high-dose, long-term opioid therapy (HLOT) prescriptions who are likely to be at the highest risk for adverse events. OBJECTIVE: We address the following questions among the Veterans Health Administration (VHA) patients receiving HLOT: 1), How has the prevalence of discontinuation of opioids changed over time? 2), How do patient characteristics vary between those who do and do not discontinue? And 3), how does the prevalence of discontinuation vary geographically? DESIGN: A retrospective observational study of VHA patients with HLOT between fiscal year (FY) 2014 and FY2018. PARTICIPANTS: We identified 1,281,330 patients from VHA outpatient opioid prescription data with at least a 1-day opioid supply between FY2014 and FY2018. We identified and excluded those receiving palliative care or diagnosed with metastatic cancer. MAIN MEASURES: For a given patient and month, a patient having a 3-month moving average of ≥ 90 daily morphine milligram equivalent (MME) was defined as having HLOT. Similarly, we used a three-month average MME of zero as discontinuation. KEY RESULTS: The prevalence of discontinuation among patients with HLOT increased from 6.3% in FY2014 to 7.8% in FY2018. Across the years, patients who discontinued were younger, less likely to be married, and more likely to have comorbidities related to substance use disorders compared with patients who continued to receive HLOT. Incidence of discontinuation among those with HLOT increased in more than half (64%) of the 129 VHA medical centers. CONCLUSION: Prevalence of patients receiving HLOT in the VHA decreased as the incidence of discontinuation increased. Further research is needed to understand the process by which patients are discontinued and to assess the relationship between discontinuation and health outcomes.

Research Lifecycle to Increase the Substantial Real-world Impact of Research: Accelerating Innovations to Application.

BACKGROUND: US health care systems face a growing demand to incorporate innovations that improve patient outcomes at a lower cost. Funding agencies increasingly must demonstrate the impact of research investments on public health. The Learning Health System promotes continuous institutional innovation, yet specific processes to develop innovations for further research and implementation into real-world health care settings to maximize health impacts have not been specified. OBJECTIVE: We describe the Research Lifecycle and how it leverages institutional priorities to support the translation of research discoveries to clinical application, serving as a broader operational approach to enhance the Learning Health System. METHODS: Developed by the US Department of Veterans Affairs Office of Research and Development Research-to-Real-World Workgroup, the Research Lifecycle incorporates frameworks from product development, translational science, and implementation science methods. The Lifecycle is based on Workgroup recommendations to overcome barriers to more direct translation of innovations to clinical application and support practice implementation and sustainability. RESULTS: The Research Lifecycle posits 5 phases which support a seamless pathway from discovery to implementation: prioritization (leadership priority alignment), discovery (innovation development), validation (clinical, operational feasibility), scale-up and spread (implementation strategies, performance monitoring), and sustainability (business case, workforce training). An example of how the Research Lifecycle has been applied within a health system is provided. CONCLUSIONS: The Research Lifecycle aligns research and health system investments to maximize real-world practice impact via a feasible pathway, where priority-driven innovations are adapted for effective clinical use and supported through implementation strategies, leading to continuous improvement in real-world health care.

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.

Association Between Teaching Status and Mortality in US Hospitals.

IMPORTANCE: Few studies have analyzed contemporary data on outcomes at US teaching hospitals vs nonteaching hospitals. OBJECTIVE: To examine risk-adjusted outcomes for patients admitted to teaching vs nonteaching hospitals across a broad range of medical and surgical conditions. DESIGN, SETTING, AND PARTICIPANTS: Use of national Medicare data to compare mortality rates in US teaching and nonteaching hospitals for all hospitalizations and for common medical and surgical conditions among Medicare beneficiaries 65 years and older. EXPOSURES: Hospital teaching status: major teaching hospitals (members of the Council of Teaching Hospitals), minor teaching hospitals (other hospitals with medical school affiliation), and nonteaching hospitals (remaining hospitals). MAIN OUTCOMES AND MEASURES: Primary outcome was 30-day mortality rate for all hospitalizations and for 15 common medical and 6 surgical conditions. Secondary outcomes included 30-day mortality stratified by hospital size and 7-day mortality and 90-day mortality for all hospitalizations as well as for individual medical and surgical conditions. RESULTS: The sample consisted of 21 451 824 total hospitalizations at 4483 hospitals, of which 250 (5.6%) were major teaching, 894 (19.9%) were minor teaching, and 3339 (74.3%) were nonteaching hospitals. Unadjusted 30-day mortality was 8.1% at major teaching hospitals, 9.2% at minor teaching hospitals, and 9.6% at nonteaching hospitals, with a 1.5% (95% CI, 1.3%-1.7%; P < .001) mortality difference between major teaching hospitals and nonteaching hospitals. After adjusting for patient and hospital characteristics, the same pattern persisted (8.3% mortality at major teaching vs 9.2% at minor teaching and 9.5% at nonteaching), but the difference in mortality between major and nonteaching hospitals was smaller (1.2% [95% CI, 1.0%-1.4%]; P < .001). After stratifying by hospital size, 187 large (≥400 beds) major teaching hospitals had lower adjusted overall 30-day mortality relative to 76 large nonteaching hospitals (8.1% vs 9.4%; 1.2% difference [95% CI, 0.9%-1.5%]; P < .001). This same pattern of lower overall 30-day mortality at teaching hospitals was observed for medium-sized (100-399 beds) hospitals (8.6% vs 9.3% and 9.4%; 0.8% difference between 61 major and 1207 nonteaching hospitals [95% CI, 0.4%-1.3%]; P = .003). Among small (≤99 beds) hospitals, 187 minor teaching hospitals had lower overall 30-day mortality relative to 2056 nonteaching hospitals (9.5% vs 9.9%; 0.4% difference [95% CI, 0.1%-0.7%]; P = .01). CONCLUSIONS AND RELEVANCE: Among hospitalizations for US Medicare beneficiaries, major teaching hospital status was associated with lower mortality rates for common conditions compared with nonteaching hospitals. Further study is needed to understand the reasons for these differences.

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.

Geographic variation in cancer-related imaging: Veterans Affairs health care system versus Medicare.

BACKGROUND: Geographic variations in use of medical services have been interpreted as indirect evidence of wasteful care. Less overuse of services, however, may not be reliably associated with less geographic variation. OBJECTIVE: To compare average use and geographic variation in use of cancer-related imaging between fee-for-service Medicare and the Department of Veterans Affairs (VA) health care system. DESIGN: Observational analysis of cancer-related imaging from 2003 to 2005 using Medicare and VA utilization data linked to cancer registry data. Multilevel models, adjusted for sociodemographic and tumor characteristics, were used to estimate mean differences in annual imaging use between cohorts of Medicare and VA patients within geographic areas and variation in use across areas for each cohort. SETTING: 40 hospital referral regions. PATIENTS: Older men with lung, colorectal, or prostate cancer, including 34,475 traditional Medicare beneficiaries (Medicare cohort) and 6835 VA patients (VA cohort). MEASUREMENTS: Per-patient count of imaging studies for which lung, colorectal, or prostate cancer was the primary diagnosis (each study weighted by a standardized price), and a direct measure of overuse-advanced imaging for prostate cancer at low risk for metastasis. RESULTS: Adjusted annual use of cancer-related imaging was lower in the VA cohort than in the Medicare cohort (price-weighted count, $197 vs. $379 per patient; P < 0.001), as was annual use of advanced imaging for prostate cancer at low risk for metastasis ($41 vs. $117 per patient; P < 0.001). Geographic variation in cancer-related imaging use was similar in magnitude in the VA and Medicare cohorts. LIMITATION: Observational study design. CONCLUSION: Use of cancer-related imaging was lower in the VA health care system than in fee-for-service Medicare, but lower use was not associated with less geographic variation. Geographic variation in service use may not be a reliable indicator of the extent of overuse. PRIMARY FUNDING SOURCE: Doris Duke Charitable Foundation and Department of Veterans Affairs Office of Policy and Planning.