Measuring Equity in Readmission as a Distinct Assessment of Hospital Performance.

Importance: Equity is an essential domain of health care quality. The Centers for Medicare & Medicaid Services (CMS) developed 2 Disparity Methods that together assess equity in clinical outcomes. Objectives: To define a measure of equitable readmissions; identify hospitals with equitable readmissions by insurance (dual eligible vs non-dual eligible) or patient race (Black vs White); and compare hospitals with and without equitable readmissions by hospital characteristics and performance on accountability measures (quality, cost, and value). Design, Setting, and Participants: Cross-sectional study of US hospitals eligible for the CMS Hospital-Wide Readmission measure using Medicare data from July 2018 through June 2019. Main Outcomes and Measures: We created a definition of equitable readmissions using CMS Disparity Methods, which evaluate hospitals on 2 methods: outcomes for populations at risk for disparities (across-hospital method); and disparities in care within hospitals' patient populations (within-a-single-hospital method). Exposures: Hospital patient demographics; hospital characteristics; and 3 measures of hospital performance-quality, cost, and value (quality relative to cost). Results: Of 4638 hospitals, 74% served a sufficient number of dual-eligible patients, and 42% served a sufficient number of Black patients to apply CMS Disparity Methods by insurance and race. Of eligible hospitals, 17% had equitable readmission rates by insurance and 30% by race. Hospitals with equitable readmissions by insurance or race cared for a lower percentage of Black patients (insurance, 1.9% [IQR, 0.2%-8.8%] vs 3.3% [IQR, 0.7%-10.8%], P < .01; race, 7.6% [IQR, 3.2%-16.6%] vs 9.3% [IQR, 4.0%-19.0%], P = .01), and differed from nonequitable hospitals in multiple domains (teaching status, geography, size; P < .01). In examining equity by insurance, hospitals with low costs were more likely to have equitable readmissions (odds ratio, 1.57 [95% CI, 1.38-1.77), and there was no relationship between quality and value, and equity. In examining equity by race, hospitals with high overall quality were more likely to have equitable readmissions (odds ratio, 1.14 [95% CI, 1.03-1.26]), and there was no relationship between cost and value, and equity. Conclusion and Relevance: A minority of hospitals achieved equitable readmissions. Notably, hospitals with equitable readmissions were characteristically different from those without. For example, hospitals with equitable readmissions served fewer Black patients, reinforcing the role of structural racism in hospital-level inequities. Implementation of an equitable readmission measure must consider unequal distribution of at-risk patients among hospitals.

Impact of Visit Volume on the Effectiveness of Electronic Tools to Improve Heart Failure Care.

BACKGROUND: Electronic health record (EHR) tools can improve prescribing of guideline-recommended therapies for heart failure with reduced ejection fraction (HFrEF), but their effectiveness may vary by physician workload. OBJECTIVES: This paper aims to assess whether physician workload modifies the effectiveness of EHR tools for HFrEF. METHODS: This was a prespecified subgroup analysis of the BETTER CARE-HF (Building Electronic Tools to Enhance and Reinforce Cardiovascular Recommendations for Heart Failure) cluster-randomized trial, which compared effectiveness of an alert vs message vs usual care on prescribing of mineralocorticoid antagonists (MRAs). The trial included adults with HFrEF seen in cardiology offices who were eligible for and not prescribed MRAs. Visit volume was defined at the cardiologist-level as number of visits per 6-month study period (high = upper tertile vs non-high = remaining). Analysis at the patient-level used likelihood ratio test for interaction with log-binomial models. RESULTS: Among 2,211 patients seen by 174 cardiologists, 932 (42.2%) were seen by high-volume cardiologists (median: 1,853; Q1-Q3: 1,637-2,225 visits/6 mo; and median: 10; Q1-Q3: 9-12 visits/half-day). MRA was prescribed to 5.5% in the high-volume vs 14.8% in the non-high-volume groups in the usual care arm, 10.3% vs 19.6% in the message arm, and 31.2% vs 28.2% in the alert arm, respectively. Visit volume modified treatment effect (P for interaction = 0.02) such that the alert was more effective in the high-volume group (relative risk: 5.16; 95% CI: 2.57-10.4) than the non-high-volume group (relative risk: 1.93; 95% CI: 1.29-2.90). CONCLUSIONS: An EHR-embedded alert increased prescribing by >5-fold among patients seen by high-volume cardiologists. Our findings support use of EHR alerts, especially in busy practice settings. (Building Electronic Tools to Enhance and Reinforce Cardiovascular Recommendations for Heart Failure [BETTER CARE-HF]; NCT05275920).

Efficacy and Impact of a Multimodal Intervention on CT Pulmonary Angiography Ordering Behavior in the Emergency Department.

OBJECTIVE: To evaluate the efficacy of a multimodal intervention in reducing CT pulmonary angiography (CTPA) overutilization in the evaluation of suspected pulmonary embolism in the emergency department (ED). METHODS: Previous mixed-methods analysis of barriers to guideline-concordant CTPA ordering results was used to develop a provider-focused behavioral intervention consisting of a clinical decision support tool and an audit and feedback system at a multisite, tertiary academic network. The primary outcome (guideline concordance) and secondary outcomes (yield and CTPA and D-dimer order rates) were compared using a pre- and postintervention design. ED encounters for adult patients from July 5, 2017, to January 3, 2019, were included. Fisher's exact tests and statistical process control charts were used to compare the pre- and postintervention groups for each outcome. RESULTS: Of the 201,912 ED patient visits evaluated, 3,587 included CTPA. Guideline concordance increased significantly after the intervention, from 66.9% to 77.5% (P < .001). CTPA order rate and D-dimer order rate also increased significantly, from 17.1 to 18.4 per 1,000 patients (P = .035) and 30.6 to 37.3 per 1,000 patients (P < .001), respectively. Percent yield showed no significant change (12.3% pre- versus 10.8% postintervention; P = .173). Statistical process control analysis showed sustained special-cause variation in the postintervention period for guideline concordance and D-dimer order rates, temporary special-cause variation for CTPA order rates, and no special-cause variation for percent yield. CONCLUSION: Our success in increasing guideline concordance demonstrates the efficacy of a mixed-methods, human-centered approach to behavior change. Given that neither of the secondary outcomes improved, our results may demonstrate potential limitations to the guidelines directing the ordering of CTPA studies and D-dimer ordering.

Researching COVID to enhance recovery (RECOVER) pregnancy study: Rationale, objectives and design.

IMPORTANCE: Pregnancy induces unique physiologic changes to the immune response and hormonal changes leading to plausible differences in the risk of developing post-acute sequelae of SARS-CoV-2 (PASC), or Long COVID. Exposure to SARS-CoV-2 during pregnancy may also have long-term ramifications for exposed offspring, and it is critical to evaluate the health outcomes of exposed children. The National Institutes of Health (NIH) Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC aims to evaluate the long-term sequelae of SARS-CoV-2 infection in various populations. RECOVER-Pregnancy was designed specifically to address long-term outcomes in maternal-child dyads. METHODS: RECOVER-Pregnancy cohort is a combined prospective and retrospective cohort that proposes to enroll 2,300 individuals with a pregnancy during the COVID-19 pandemic and their offspring exposed and unexposed in utero, including single and multiple gestations. Enrollment will occur both in person at 27 sites through the Eunice Kennedy Shriver National Institutes of Health Maternal-Fetal Medicine Units Network and remotely through national recruitment by the study team at the University of California San Francisco (UCSF). Adults with and without SARS-CoV-2 infection during pregnancy are eligible for enrollment in the pregnancy cohort and will follow the protocol for RECOVER-Adult including validated screening tools, laboratory analyses and symptom questionnaires followed by more in-depth phenotyping of PASC on a subset of the overall cohort. Offspring exposed and unexposed in utero to SARS-CoV-2 maternal infection will undergo screening tests for neurodevelopment and other health outcomes at 12, 18, 24, 36 and 48 months of age. Blood specimens will be collected at 24 months of age for SARS-CoV-2 antibody testing, storage and anticipated later analyses proposed by RECOVER and other investigators. DISCUSSION: RECOVER-Pregnancy will address whether having SARS-CoV-2 during pregnancy modifies the risk factors, prevalence, and phenotype of PASC. The pregnancy cohort will also establish whether there are increased risks of adverse long-term outcomes among children exposed in utero. CLINICAL TRIALS.GOV IDENTIFIER: Clinical Trial Registration: http://www.clinicaltrials.gov. Unique identifier: NCT05172011.

Perceptions of Factors Associated With Sustainability of Health Care Innovation Centers.

Importance: Innovation centers in US health care systems are increasingly common but variably successful and sustainable. Few studies have examined how and why some centers achieve sustainable success but others do not. Objective: To explore whether and how innovation centers in US health care systems are able to successfully sustain themselves over multiple years. Design, Setting, and Participants: In this qualitative study, semistructured, qualitative interviews of leaders at 9 innovation centers across the US were conducted from January 1, 2019, to December 31, 2020. Data analysis was conducted from December 2020 to April 2021 using qualitative methods and a deductive framework based on the Consolidated Framework for Implementation Research. Centers were identified through purposeful sampling. The 9 study centers had a mean age of 6 years (range, 2-15 years); most were affiliated with an academic teaching hospital and half with a medical school. Two were wholly separate from the health care system. Two-thirds had fewer than 10 full-time staff members. Exposures: All interviewees were staff of a US-based innovation center. This study did not evaluate particular interventions or innovations. Main Outcomes and Measures: Perceptions of and views on factors associated with the success and sustainability of innovation centers. Results: Staff interviewed at 9 innovation centers across the US described 3 key activities that appeared to be associated with long-term sustainability: facilitating innovation projects that were valued for quality improvement and cost avoidance, not just return on investment; acting as networking nodes for their institutions; and upskilling staff. These activities were associated with improved institutional culture. Two structural characteristics underpinned successful centers: finding an effective balance between being "internal" and being "external" to the organization and providing practical support and skills otherwise lacking within the wider institution. Conclusions and Relevance: This qualitative study of 9 innovation centers explored how centers sustained themselves within US health care institutions and showed that success was often associated with interpersonal relationships and cultural benefits. Independent financial sustainability was not always essential to longevity; systems also valued how centers could create cultures of innovation and upskill staff.

Medicaid Value-Based Payments and Health Care Use for Patients With Mental Illness.

Importance: Medicaid patients with mental illness comprise one of the most high-need and complex patient populations. Value-based reforms aim to improve care, but their efficacy in the Medicaid program is unclear. Objective: To investigate if New York state's Medicaid value-based payment reform was associated with improved utilization patterns for patients with mental illness. Design, Setting, and Participants: This retrospective cohort study used a difference-in-differences analysis to compare changes in utilization between Medicaid beneficiaries whose outpatient practices participated in value-based payment reform and beneficiaries whose practices did not participate from before (July 1, 2013-June 30, 2015) to after reform (July 1, 2015-June 30, 2019). Participants were Medicaid beneficiaries in New York state aged 18 to 64 years with major depression disorder, bipolar disorder, and/or schizophrenia. Data analysis was performed from April 2021 to July 2023. Exposure: Beneficiaries were exposed to value-based payment reforms if their attributed outpatient practice participated in value-based payment reform at baseline (July 1, 2015). Main Outcomes and Measures: Primary outcomes were the number of outpatient primary care visits and the number of behavioral health visits per year. Secondary outcomes were the number of mental health emergency department visits and hospitalizations per year. Results: The analytic population comprised 306 290 individuals with depression (67.4% female; mean [SD] age, 38.6 [11.9] years), 85 105 patients with bipolar disorder (59.6% female; mean [SD] age, 38.0 [11.6] years), and 71 299 patients with schizophrenia (45.1% female; mean [SD] age, 40.3 [12.2] years). After adjustment, analyses estimated a statistically significant, positive association between value-based payments and behavioral health visits for patients with depression (0.91 visits; 95% CI, 0.51-1.30) and bipolar disorder (1.01 visits; 95% CI, 0.22-1.79). There was no statistically significant changes to primary care visits for patients with depression and bipolar disorder, but value-based payments were associated with reductions in primary care visits for patients with schizophrenia (-1.31 visits; 95% CI, -2.51 to -0.12). In every diagnostic population, value-based payment was associated with significant reductions in mental health emergency department visits (population with depression: -0.01 visits [95% CI, -0.02 to -0.002]; population with bipolar disorder: -0.02 visits [95% CI, -0.05 to -0.001]; population with schizophrenia: -0.04 visits [95% CI, -0.07 to -0.01]). Conclusions and Relevance: In this cohort study, Medicaid value-based payment reform was statistically significantly associated with an increase in behavioral health visits and a reduction in mental health emergency department visits for patients with mental illness. Medicaid value-based payment may be effective at altering health care utilization in patients with mental illness.

Researching COVID to Enhance Recovery (RECOVER) adult study protocol: Rationale, objectives, and design.

IMPORTANCE: SARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or other health effects after the acute phase of infection; termed post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are ill-defined. The objectives of the Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC in Adults (RECOVER-Adult) are to: (1) characterize PASC prevalence; (2) characterize the symptoms, organ dysfunction, natural history, and distinct phenotypes of PASC; (3) identify demographic, social and clinical risk factors for PASC onset and recovery; and (4) define the biological mechanisms underlying PASC pathogenesis. METHODS: RECOVER-Adult is a combined prospective/retrospective cohort currently planned to enroll 14,880 adults aged ≥18 years. Eligible participants either must meet WHO criteria for suspected, probable, or confirmed infection; or must have evidence of no prior infection. Recruitment occurs at 86 sites in 33 U.S. states, Washington, DC and Puerto Rico, via facility- and community-based outreach. Participants complete quarterly questionnaires about symptoms, social determinants, vaccination status, and interim SARS-CoV-2 infections. In addition, participants contribute biospecimens and undergo physical and laboratory examinations at approximately 0, 90 and 180 days from infection or negative test date, and yearly thereafter. Some participants undergo additional testing based on specific criteria or random sampling. Patient representatives provide input on all study processes. The primary study outcome is onset of PASC, measured by signs and symptoms. A paradigm for identifying PASC cases will be defined and updated using supervised and unsupervised learning approaches with cross-validation. Logistic regression and proportional hazards regression will be conducted to investigate associations between risk factors, onset, and resolution of PASC symptoms. DISCUSSION: RECOVER-Adult is the first national, prospective, longitudinal cohort of PASC among US adults. Results of this study are intended to inform public health, spur clinical trials, and expand treatment options. REGISTRATION: NCT05172024.

Researching COVID to enhance recovery (RECOVER) pregnancy study: Rationale, objectives and design.

Importance: Pregnancy induces unique physiologic changes to the immune response and hormonal changes leading to plausible differences in the risk of developing post-acute sequelae of SARS-CoV-2 (PASC), or Long COVID. Exposure to SARS-CoV-2 during pregnancy may also have long-term ramifications for exposed offspring, and it is critical to evaluate the health outcomes of exposed children. The National Institutes of Health (NIH) Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC aims to evaluate the long-term sequelae of SARS-CoV-2 infection in various populations. RECOVER- Pregnancy was designed specifically to address long-term outcomes in maternal-child dyads. Methods: RECOVER-Pregnancy cohort is a combined prospective and retrospective cohort that proposes to enroll 2,300 individuals with a pregnancy during the COVID-19 pandemic and their offspring exposed and unexposed in utero, including single and multiple gestations. Enrollment will occur both in person at 27 sites through the Eunice Kennedy Shriver National Institutes of Health Maternal-Fetal Medicine Units Network and remotely through national recruitment by the study team at the University of California San Francisco (UCSF). Adults with and without SARS-CoV-2 infection during pregnancy are eligible for enrollment in the pregnancy cohort and will follow the protocol for RECOVER-Adult including validated screening tools, laboratory analyses and symptom questionnaires followed by more in-depth phenotyping of PASC on a subset of the overall cohort. Offspring exposed and unexposed in utero to SARS-CoV-2 maternal infection will undergo screening tests for neurodevelopment and other health outcomes at 12, 18, 24, 36 and 48 months of age. Blood specimens will be collected at 24 months of age for SARS-CoV-2 antibody testing, storage and anticipated later analyses proposed by RECOVER and other investigators. Discussion: RECOVER-Pregnancy will address whether having SARS-CoV-2 during pregnancy modifies the risk factors, prevalence, and phenotype of PASC. The pregnancy cohort will also establish whether there are increased risks of adverse long-term outcomes among children exposed in utero. Registration: NCT05172024.

Cluster-Randomized Trial Comparing Ambulatory Decision Support Tools to Improve Heart Failure Care.

BACKGROUND: Mineralocorticoid receptor antagonists (MRAs) are underprescribed for patients with heart failure with reduced ejection fraction (HFrEF). OBJECTIVES: This study sought to compare effectiveness of 2 automated, electronic health record-embedded tools vs usual care on MRA prescribing in eligible patients with HFrEF. METHODS: BETTER CARE-HF (Building Electronic Tools to Enhance and Reinforce Cardiovascular Recommendations for Heart Failure) was a 3-arm, pragmatic, cluster-randomized trial comparing the effectiveness of an alert during individual patient encounters vs a message about multiple patients between encounters vs usual care on MRA prescribing. This study included adult patients with HFrEF, no active MRA prescription, no contraindication to MRAs, and an outpatient cardiologist in a large health system. Patients were cluster-randomized by cardiologist (60 per arm). RESULTS: The study included 2,211 patients (alert: 755, message: 812, usual care [control]: 644), with average age 72.2 years, average ejection fraction 33%, who were predominantly male (71.4%) and White (68.9%). New MRA prescribing occurred in 29.6% of patients in the alert arm, 15.6% in the message arm, and 11.7% in the control arm. The alert more than doubled MRA prescribing compared to usual care (relative risk: 2.53; 95% CI: 1.77-3.62; P < 0.0001) and improved MRA prescribing compared to the message (relative risk: 1.67; 95% CI: 1.21-2.29; P = 0.002). The number of patients with alert needed to result in an additional MRA prescription was 5.6. CONCLUSIONS: An automated, patient-specific, electronic health record-embedded alert increased MRA prescribing compared to both a message and usual care. These findings highlight the potential for electronic health record-embedded tools to substantially increase prescription of life-saving therapies for HFrEF. (Building Electronic Tools to Enhance and Reinforce Cardiovascular Recommendations-Heart Failure [BETTER CARE-HF]; NCT05275920).

Assessment of Patient Education Delivered at Time of Hospital Discharge.

Importance: Patient education at time of hospital discharge is critical for smooth transitions of care; however, empirical data regarding discharge communication are limited. Objective: To describe whether key communication domains (medication changes, follow-up appointments, disease self-management, red flags, question solicitation, and teach-back) were addressed at the bedside on the day of hospital discharge, by whom, and for how long. Design, Setting, and Participants: This quality improvement study was conducted from September 2018 through October 2019 at inpatient medicine floors in 2 urban, tertiary-care teaching hospitals and purposefully sampled patients designated as "discharge before noon." Data analysis was performed from September 2018 to May 2020. Exposures: A trained bedside observer documented all content and duration of staff communication with a single enrolled patient from 7 am until discharge. Main Outcomes and Measures: Presence of the key communication domains, role of team members, and amount of time spent at the bedside. Results: Discharge days for 33 patients were observed. Patients had a mean (SD) age of 63 (18) years; 14 (42%) identified as White, 15 (45%) were female, and 6 (18%) had a preferred language of Spanish. Thirty patients were discharged with at least 1 medication change. Of these patients, 8 (27%) received no verbal instruction on the change, while 16 of 30 (53%) were informed but not told the purpose of the changes. About half of the patients (15 of 31, 48%) were not told the reason for follow-up appointments, and 18 of 33 (55%) were not given instructions on posthospital disease self-management. Most patients (27 of 33, 81%) did not receive guidance on red-flag signs. While over half of the patients (19 of 33, 58%) were asked if they had any questions, only 1 patient was asked to teach back his understanding of the discharge plan. Median (IQR) total time spent with patients on the day of discharge by interns, senior residents, attending physicians, and nurses was 4.0 (0.75-6.0), 1.0 (0-2.0), 3.0 (0.5-7.0), and 22.5 (15.5-30.0) minutes, respectively. Most of the time was spent discussing logistics rather than discharge education. Conclusions and Relevance: In this quality improvement study, patients infrequently received discharge education in key communication domains, potentially leaving gaps in patient knowledge. Interventions to improve the hospital discharge process should address the content, method of delivery, and transparency among team members regarding patient education.

Design and pilot implementation for the BETTER CARE-HF trial: A pragmatic cluster-randomized controlled trial comparing two targeted approaches to ambulatory clinical decision support for cardiologists.

BACKGROUND: Beart failure with reduced ejection fraction (HFrEF) is a leading cause of morbidity and mortality. However, shortfalls in prescribing of proven therapies, particularly mineralocorticoid receptor antagonist (MRA) therapy, account for several thousand preventable deaths per year nationwide. Electronic clinical decision support (CDS) is a potential low-cost and scalable solution to improve prescribing of therapies. However, the optimal timing and format of CDS tools is unknown. METHODS AND RESULTS: We developed two targeted CDS tools to inform cardiologists of gaps in MRA therapy for patients with HFrEF and without contraindication to MRA therapy: (1) an alert that notifies cardiologists at the time of patient visit, and (2) an automated electronic message that allows for review between visits. We designed these tools using an established CDS framework and findings from semistructured interviews with cardiologists. We then pilot tested both CDS tools (n = 596 patients) and further enhanced them based on additional semistructured interviews (n = 11 cardiologists). The message was modified to reduce the number of patients listed, include future visits, and list date of next visit. The alert was modified to improve noticeability, reduce extraneous information on guidelines, and include key information on contraindications. CONCLUSIONS: The BETTER CARE-HF (Building Electronic Tools to Enhance and Reinforce CArdiovascular REcommendations for Heart Failure) trial aims to compare the effectiveness of the alert vs. the automated message vs. usual care on the primary outcome of MRA prescribing. To our knowledge, no study has directly compared the efficacy of these two different types of electronic CDS interventions. If effective, our findings can be rapidly disseminated to improve morbidity and mortality for patients with HFrEF, and can also inform the development of future CDS interventions for other disease states. (Trial registration: Clinicaltrials.gov NCT05275920).

Using Rapid Randomized Trials to Improve Health Care Systems.

Rapid randomized controlled trials have been surprisingly rare in health care quality improvement (QI) and systems interventions. Applying clinical trials methodology QI work brings two distinct fields together, applying the robustness of randomized controlled trials (RCTs) to the practical, operational learnings of the well-established QI field. Rapid trials also add a third element-speed-that enables health care systems to rapidly test multiple variations of an intervention in much the same way that A/B testing is done in the technology sector. When performed well, these rapid trials free researchers and health care systems from the requirement to be correct the first time (because it is low cost and quick to try something else) while offering a standard of evidence often absent in QI. Here we outline the historical underpinnings of this approach, provide guidance about how best to implement it, and describe lessons learned from running more than 20 randomized projects in the NYU Langone Health system.

"I Am Not the Same as I Was Before": A Qualitative Analysis of COVID-19 Survivors.

BACKGROUND: Little is known about the illness experience of patients' long-term emotional and physical recovery from severe COVID-19 infection. This study aimed to expand upon the recovery process of COVID-19 survivors up to 6 months after hospital discharge. METHODS: Qualitative analysis of free-response answers from a cohort study of 152 patients ≥ 18 years hospitalized with laboratory-confirmed SARS-CoV-2 surveyed at 1-month post hospital discharge and 6-months post hospital discharge. Responses were analyzed with a grounded theory approach to identify overarching themes. RESULTS: Participants described persistent complications, both physical and mental, that have affected their recovery from COVID-19. Five overarching themes of post-acute patient experiences were generated: (1) an increased awareness of a mind and body connection, (2) feelings of premature aging, (3) an overall decline in quality of life, (4) a continued fear of infection, and (5) methods of coping. CONCLUSIONS: Patients described lasting changes to their mental health and overall quality of life in connection to physical complications after severe COVID-19 infection. Patients' reports of their experience call for a greater awareness of the psychological aspects of COVID-19 recovery to provide both physical and psychological rehabilitation services. Additional resources such as education around re-infection and financial resources are needed.

The impact of COVID-19 monoclonal antibodies on clinical outcomes: A retrospective cohort study.

PURPOSE: Despite progress in the treatment of coronavirus disease 2019 (COVID-19), including the development of monoclonal antibodies (mAbs), more clinical data to support the use of mAbs in outpatients with COVID-19 is needed. This study is designed to determine the impact of bamlanivimab, bamlanivimab/etesevimab, or casirivimab/imdevimab on clinical outcomes within 30 days of COVID-19 diagnosis. METHODS: A retrospective cohort study was conducted at a single academic medical center with 3 campuses in Manhattan, Brooklyn, and Long Island, NY. Patients 12 years of age or older who tested positive for COVID-19 or were treated with a COVID-19-specific therapy, including COVID-19 mAb therapies, at the study site between November 24, 2020, and May 15, 2021, were included. The primary outcomes included rates of emergency department (ED) visit, inpatient admission, intensive care unit (ICU) admission, or death within 30 days from the date of COVID-19 diagnosis. RESULTS: A total of 1,344 mAb-treated patients were propensity matched to 1,344 patients with COVID-19 patients who were not treated with mAb therapy. Within 30 days of diagnosis, among the patients who received mAb therapy, 101 (7.5%) presented to the ED and 79 (5.9%) were admitted. Among the patients who did not receive mAb therapy, 165 (12.3%) presented to the ED and 156 (11.6%) were admitted (relative risk [RR], 0.61 [95% CI, 0.50-0.75] and 0.51 [95% CI, 0.40-0.64], respectively). Four mAb patients (0.3%) and 2.64 control patients (0.2%) were admitted to the ICU (RR, 01.51; 95% CI, 0.45-5.09). Six mAb-treated patients (0.4%) and 3.37 controls (0.3%) died and/or were admitted to hospice (RR, 1.61; 95% CI, 0.54-4.83). mAb therapy in ambulatory patients with COVID-19 decreases the risk of ED presentation and hospital admission within 30 days of diagnosis.

Effects of Real-time Prescription Benefit Recommendations on Patient Out-of-Pocket Costs: A Cluster Randomized Clinical Trial.

Importance: Rising drug costs contribute to medication nonadherence and adverse health outcomes. Real-time prescription benefit (RTPB) systems present prescribers with patient-specific out-of-pocket cost estimates and recommend lower-cost, clinically appropriate alternatives at the point of prescribing. Objective: To investigate whether RTPB recommendations lead to reduced patient out-of-pocket costs for medications. Design, Setting, and Participants: In this cluster randomized trial, medical practices in a large, urban academic health system were randomly assigned to RTPB recommendations from January 13 to July 31, 2021. Participants were adult patients receiving outpatient prescriptions during the study period. The analysis was limited to prescriptions for which RTPB could recommend an available alternative. Electronic health record data were used to analyze the intervention's effects on prescribing. Data analyses were performed from August 20, 2021, to June 8, 2022. Interventions: When a prescription was initiated in the electronic health record, the RTPB system recommended available lower-cost, clinically appropriate alternatives for a different medication, length of prescription, and/or choice of pharmacy. The prescriber could select either the initiated order or one of the recommended options. Main Outcomes and Measures: Patient out-of-pocket cost for a prescription. Secondary outcomes were whether a mail-order prescription and a 90-day supply were ordered. Results: Of 867 757 outpatient prescriptions at randomized practices, 36 419 (4.2%) met the inclusion criteria of having an available alternative. Out-of-pocket costs were $39.90 for a 30-day supply in the intervention group and $67.80 for a 30-day supply in the control group. The intervention led to an adjusted 11.2%; (95% CI, -15.7% to -6.4%) reduction in out-of-pocket costs. Mail-order pharmacy use was 9.6% and 7.6% in the intervention and control groups, respectively (adjusted 1.9 percentage point increase; 95% CI, 0.9 to 3.0). Rates of 90-day supply were not different. In high-cost drug classes, the intervention reduced out-of-pocket costs by 38.9%; 95% CI, -47.6% to -28.7%. Conclusions and Relevance: This cluster randomized clinical trial showed that RTPB recommendations led to lower patient out-of-pocket costs, with the largest savings occurring for high-cost medications. However, RTPB recommendations were made for only a small percentage of prescriptions. Trial Registration: ClinicalTrials.gov Identifier: NCT04940988; American Economic Association Registry: AEARCTR-0006909.

Missed opportunities in medical therapy for patients with heart failure in an electronically-identified cohort.

BACKGROUND: National registries reveal significant gaps in medical therapy for patients with heart failure and reduced ejection fraction (HFrEF), but may not accurately (or fully) characterize the population eligible for therapy. OBJECTIVE: We developed an automated, electronic health record-based algorithm to identify HFrEF patients eligible for evidence-based therapy, and extracted treatment data to assess gaps in therapy in a large, diverse health system. METHODS: In this cross-sectional study of all NYU Langone Health outpatients with EF ≤ 40% on echocardiogram and an outpatient visit from 3/1/2019 to 2/29/2020, we assessed prescription of the following therapies: beta-blocker (BB), angiotensin converting enzyme inhibitor (ACE-I)/angiotensin receptor blocker (ARB)/angiotensin receptor neprilysin inhibitor (ARNI), and mineralocorticoid receptor antagonist (MRA). Our algorithm accounted for contraindications such as medication allergy, bradycardia, hypotension, renal dysfunction, and hyperkalemia. RESULTS: We electronically identified 2732 patients meeting inclusion criteria. Among those eligible for each medication class, 84.8% and 79.7% were appropriately prescribed BB and ACE-I/ARB/ARNI, respectively, while only 23.9% and 22.7% were appropriately prescribed MRA and ARNI, respectively. In adjusted models, younger age, cardiology visit and lower EF were associated with increased prescribing of medications. Private insurance and Medicaid were associated with increased prescribing of ARNI (OR = 1.40, 95% CI = 1.02-2.00; and OR = 1.70, 95% CI = 1.07-2.67). CONCLUSIONS: We observed substantial shortfalls in prescribing of MRA and ARNI therapy to ambulatory HFrEF patients. Subspecialty care setting, and Medicaid insurance were associated with higher rates of ARNI prescribing. Further studies are warranted to prospectively evaluate provider- and policy-level interventions to improve prescribing of these evidence-based therapies.

Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial.

BACKGROUND: We previously developed and validated a predictive model to help clinicians identify hospitalized adults with coronavirus disease 2019 (COVID-19) who may be ready for discharge given their low risk of adverse events. Whether this algorithm can prompt more timely discharge for stable patients in practice is unknown. OBJECTIVES: The aim of the study is to estimate the effect of displaying risk scores on length of stay (LOS). METHODS: We integrated model output into the electronic health record (EHR) at four hospitals in one health system by displaying a green/orange/red score indicating low/moderate/high-risk in a patient list column and a larger COVID-19 summary report visible for each patient. Display of the score was pseudo-randomized 1:1 into intervention and control arms using a patient identifier passed to the model execution code. Intervention effect was assessed by comparing LOS between intervention and control groups. Adverse safety outcomes of death, hospice, and re-presentation were tested separately and as a composite indicator. We tracked adoption and sustained use through daily counts of score displays. RESULTS: Enrolling 1,010 patients from May 15, 2020 to December 7, 2020, the trial found no detectable difference in LOS. The intervention had no impact on safety indicators of death, hospice or re-presentation after discharge. The scores were displayed consistently throughout the study period but the study lacks a causally linked process measure of provider actions based on the score. Secondary analysis revealed complex dynamics in LOS temporally, by primary symptom, and hospital location. CONCLUSION: An AI-based COVID-19 risk score displayed passively to clinicians during routine care of hospitalized adults with COVID-19 was safe but had no detectable impact on LOS. Health technology challenges such as insufficient adoption, nonuniform use, and provider trust compounded with temporal factors of the COVID-19 pandemic may have contributed to the null result. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04570488.

Identifying drivers of health care value: a scoping review of the literature.

BACKGROUND: As health care spending reaches unsustainable levels, improving value has become an increasingly important policy priority. Relatively little research has explored factors driving value. As a first step towards filling this gap, we performed a scoping review of the literature to identify potential drivers of health care value. METHODS: Searches of PubMed, Embase, Google Scholar, Policy File, and SCOPUS were conducted between February and March 2020. Empirical studies that explored associations between any range of factors and value (loosely defined as quality or outcomes relative to cost) were eligible for inclusion. We created a template in Microsoft Excel for data extraction and evaluated the quality of included articles using the Critical Appraisal Skills Programme (CASP) quality appraisal tool. Data was synthesized using narrative methods. RESULTS: Twenty-two studies were included in analyses, of which 20 focused on low value service utilization. Independent variables represented a range of system-, hospital-, provider-, and patient-level characteristics. Although results were mixed, several consistent findings emerged. First, insurance incentive structures may affect value. For example, patients in Accountable Care Organizations had reduced rates of low value care utilization compared to patients in traditionally structured insurance plans. Second, higher intensity of care was associated with higher rates of low value care. Third, culture is likely to contribute to value. This was suggested by findings that recent medical school graduation and allopathic training were associated with reduced low value service utilization and that provider organizations had larger effects on value than did individual physicians. CONCLUSIONS: System, hospital, provider, and community characteristics influence low value care provision. To improve health care value, strategies aiming to reduce utilization of low value services and promote high value care across various levels will be essential.

Identifying high-value care for Medicare beneficiaries: a cross-sectional study of acute care hospitals in the USA.

OBJECTIVES: High-value care is providing high quality care at low cost; we sought to define hospital value and identify the characteristics of hospitals which provide high-value care. DESIGN: Retrospective observational study. SETTING: Acute care hospitals in the USA. PARTICIPANTS: All Medicare beneficiaries with claims included in Center for Medicare & Medicaid Services Overall Star Ratings or in publicly available Medicare spending per beneficiary data. PRIMARY AND SECONDARY OUTCOME MEASURES: Our primary outcome was value defined as the difference between Star Ratings quality score and Medicare spending; the secondary outcome was classification as a 4 or 5 star hospital with lowest quintile Medicare spending ('high value') or 1 or 2 star hospital with highest quintile spending ('low value'). RESULTS: Two thousand nine hundred and fourteen hospitals had both quality and spending data, and were included. The value score had a mean (SD) of 0.58 (1.79). A total of 286 hospitals were classified as high value; these represented 28.6% of 999 4 and 5 star hospitals and 46.8% of 611 low cost hospitals. A total of 258 hospitals were classified as low value; these represented 26.6% of 970 1 and 2 star hospitals and 49.3% of 523 high cost hospitals. In regression models ownership, non-teaching status, beds, urbanity, nurse to bed ratio, percentage of dual eligible Medicare patients and percentage of disproportionate share hospital payments were associated with the primary value score. CONCLUSIONS: There are high quality hospitals that are not high value, and a number of factors are strongly associated with being low or high value. These findings can inform efforts of policymakers and hospitals to increase the value of care.