SARS-CoV-2 Sequelae and Postdischarge Health Care Visits Over 5 Months Follow-up Among Children Hospitalized for COVID-19 or MIS-C.

Although post-acute sequelae of COVID-19 among adult survivors has gained significant attention, data in children hospitalized for severe acute respiratory syndrome coronavirus 2 is limited. This study of commercially insured US children shows that those hospitalized with COVID-19 or multisystem inflammatory syndrome in children have a substantial burden of severe acute respiratory syndrome coronavirus 2 sequelae and associated health care visits postdischarge.

DLMM as a lossless one-shot algorithm for collaborative multi-site distributed linear mixed models.

Linear mixed models are commonly used in healthcare-based association analyses for analyzing multi-site data with heterogeneous site-specific random effects. Due to regulations for protecting patients' privacy, sensitive individual patient data (IPD) typically cannot be shared across sites. We propose an algorithm for fitting distributed linear mixed models (DLMMs) without sharing IPD across sites. This algorithm achieves results identical to those achieved using pooled IPD from multiple sites (i.e., the same effect size and standard error estimates), hence demonstrating the lossless property. The algorithm requires each site to contribute minimal aggregated data in only one round of communication. We demonstrate the lossless property of the proposed DLMM algorithm by investigating the associations between demographic and clinical characteristics and length of hospital stay in COVID-19 patients using administrative claims from the UnitedHealth Group Clinical Discovery Database. We extend this association study by incorporating 120,609 COVID-19 patients from 11 collaborative data sources worldwide.

Schizophrenia population health management: perspectives of and lessons learned from population health decision makers.

BACKGROUND: Despite therapeutic advances for patients with schizophrenia, improving patient outcomes and reducing the cost of care continue to challenge formulary decision makers. OBJECTIVES: To (1) understand the perspectives of formulary decision makers on challenges to optimal schizophrenia population management and (2) identify best practices and recommendations for mitigating these challenges. METHODS: This mixed-methods study, conducted in a double-blind manner, comprised in-depth telephone interviews with formulary decision makers from February through May 2020, and a web-based follow-on survey that was sent to all participants in October 2020. US-based formulary decision makers were recruited if they were directly involved in schizophrenia drug formulary or coverage decision making for national or regional payers, health systems, or behavioral health centers. Formulary decision makers' perceptions of challenges, policies, and programs related to schizophrenia population health management were assessed generally and in the context of the COVID-19 pandemic. RESULTS: 19 formulary decision makers participated in the interviews and 18 (95%) completed the survey. Participants reported a spectrum of patient- and payer-driven challenges in schizophrenia population health management, including medication nonadherence, high pharmacy and medical costs, and frequent hospitalizations and emergency department visits. Participants noted that COVID-19 had worsened all identified challenges, although patient unemployment (mean score of 2.00 on a scale of 1 [made much worse] to 5 [made much better]) and reduced access to psychiatric care (mean score, 2.12) were most negatively affected. The most common strategies implemented in order to improve schizophrenia population health management included case management (89%), telemedicine (83%), care coordination programs (72%), strategies to mitigate barriers to accessing medication (61%), and providing nonmedical services to address social determinants of health (56%). Participants noted that, ideally, all treatments for schizophrenia would be available on their formularies without utilization management policies in place in order to increase accessibility to medication, but cost to the health plans made that difficult. Whereas 61% of respondents believed that long-acting injectable antipsychotics (LAIs) were currently underused in their organizations, only 28% represented organizations with open access policies for LAIs. Participants believed that among patients with schizophrenia, LAIs were most beneficial for those with a history of poor or uncertain adherence to oral medications (mean score of 4.50 on a scale of 1 [not at all beneficial] to 5 [extremely beneficial]) and those with recurring emergency department visits and inpatient stays (mean score, 3.94). Study participants reported slightly increased use of LAIs (mean score of 3.17 on a scale of 1 [negatively impacted] to 5 [positively impacted]) among their patients with schizophrenia in response to the COVID-19 pandemic; 29% of participants reported easing access restrictions for LAIs. CONCLUSIONS: Participants described persisting challenges and various approaches intended to improve schizophrenia population health management. They also recommended strategies to optimize future health management for this population, including expanding programs to address social determinants of health and mitigating barriers to accessing treatment. DISCLOSURES: This study was funded by Janssen Scientific Affairs, LLC. Roach, Graf, Pednekar, and Chou are employees of PRECISIONheor, which received financial support from Janssen Scientific Affairs, LLC, to conduct this study. Chou owns equity in Precision Medicine Group, the parent company of PRECISIONheor. Lin and Benson are employees of Janssen Scientific Affairs, LLC. Doshi has served as a consultant, advisory board member, or both, for Acadia, Allergan, Boehringer Ingelheim, Janssen, Merck, Otsuka, and Sage Therapeutics and has received research funding from AbbVie, Biogen, Humana, Janssen, Novartis, Merck, Pfizer, PhRMA, Regeneron, Sanofi, and Valeant.

Patient and Hospital Factors Associated With Differences in Mortality Rates Among Black and White US Medicare Beneficiaries Hospitalized With COVID-19 Infection.

Importance: Black patients hospitalized with COVID-19 may have worse outcomes than White patients because of excess individual risk or because Black patients are disproportionately cared for in hospitals with worse outcomes for all. Objectives: To examine differences in COVID-19 hospital mortality rates between Black and White patients and to assess whether the mortality rates reflect differences in patient characteristics by race or by the hospitals to which Black and White patients are admitted. Design, Setting, and Participants: This cohort study assessed Medicare beneficiaries admitted with a diagnosis of COVID-19 to 1188 US hospitals from January 1, 2020, through September 21, 2020. Exposure: Hospital admission for a diagnosis of COVID-19. Main Outcomes and Measures: The primary composite outcome was inpatient death or discharge to hospice within 30 days of admission. We estimated the association of patient-level characteristics (including age, sex, zip code-level income, comorbidities, admission from a nursing facility, and days since January 1, 2020) with differences in mortality or discharge to hospice among Black and White patients. To examine the association with the hospital itself, we adjusted for the specific hospitals to which patients were admitted. We used simulation modeling to estimate the mortality among Black patients had they instead been admitted to the hospitals where White patients were admitted. Results: Of the 44 217 Medicare beneficiaries included in the study, 24 281 (55%) were women; mean (SD) age was 76.3 (10.5) years; 33 459 participants (76%) were White, and 10 758 (24%) were Black. Overall, 2634 (8%) White patients and 1100 (10%) Black patients died as inpatients, and 1670 (5%) White patients and 350 (3%) Black patients were discharged to hospice within 30 days of hospitalization, for a total mortality-equivalent rate of 12.86% for White patients and 13.48% for Black patients. Black patients had similar odds of dying or being discharged to hospice (odds ratio [OR], 1.06; 95% CI, 0.99-1.12) in an unadjusted comparison with White patients. After adjustment for clinical and sociodemographic patient characteristics, Black patients were more likely to die or be discharged to hospice (OR, 1.11; 95% CI, 1.03-1.19). This difference became indistinguishable when adjustment was made for the hospitals where care was delivered (odds ratio, 1.02; 95% CI, 0.94-1.10). In simulations, if Black patients in this sample were instead admitted to the same hospitals as White patients in the same distribution, their rate of mortality or discharge to hospice would decline from the observed rate of 13.48% to the simulated rate of 12.23% (95% CI for difference, 1.20%-1.30%). Conclusions and Relevance: This cohort study found that Black patients hospitalized with COVID-19 had higher rates of hospital mortality or discharge to hospice than White patients after adjustment for the personal characteristics of those patients. However, those differences were explained by differences in the hospitals to which Black and White patients were admitted.

Variation in US Hospital Mortality Rates for Patients Admitted With COVID-19 During the First 6 Months of the Pandemic.

Importance: It is unknown how much the mortality of patients with coronavirus disease 2019 (COVID-19) depends on the hospital that cares for them, and whether COVID-19 hospital mortality rates are improving. Objective: To identify variation in COVID-19 mortality rates and how those rates have changed over the first months of the pandemic. Design, Setting, and Participants: This cohort study assessed 38 517 adults who were admitted with COVID-19 to 955 US hospitals from January 1, 2020, to June 30, 2020, and a subset of 27 801 adults (72.2%) who were admitted to 398 of these hospitals that treated at least 10 patients with COVID-19 during 2 periods (January 1 to April 30, 2020, and May 1 to June 30, 2020). Exposures: Hospital characteristics, including size, the number of intensive care unit beds, academic and profit status, hospital setting, and regional characteristics, including COVID-19 case burden. Main Outcomes and Measures: The primary outcome was the hospital's risk-standardized event rate (RSER) of 30-day in-hospital mortality or referral to hospice adjusted for patient-level characteristics, including demographic data, comorbidities, community or nursing facility admission source, and time since January 1, 2020. We examined whether hospital characteristics were associated with RSERs or their change over time. Results: The mean (SD) age among participants (18 888 men [49.0%]) was 70.2 (15.5) years. The mean (SD) hospital-level RSER for the 955 hospitals was 11.8% (2.5%). The mean RSER in the worst-performing quintile of hospitals was 15.65% compared with 9.06% in the best-performing quintile (absolute difference, 6.59 percentage points; 95% CI, 6.38%-6.80%; P < .001). Mean RSERs in all but 1 of the 398 hospitals improved; 376 (94%) improved by at least 25%. The overall mean (SD) RSER declined from 16.6% (4.0%) to 9.3% (2.1%). The absolute difference in rates of mortality or referral to hospice between the worst- and best-performing quintiles of hospitals decreased from 10.54 percentage points (95% CI, 10.03%-11.05%; P < .001) to 5.59 percentage points (95% CI, 5.33%-5.86%; P < .001). Higher county-level COVID-19 case rates were associated with worse RSERs, and case rate declines were associated with improvement in RSERs. Conclusions and Relevance: Over the first months of the pandemic, COVID-19 mortality rates in this cohort of US hospitals declined. Hospitals did better when the prevalence of COVID-19 in their surrounding communities was lower.