All-cause nursing home mortality rates have remained above pre-pandemic levels after accounting for decline in occupancy.

During the initial year of the COVID-19 pandemic, a disproportionate share of COVID-19-related deaths occurred among nursing home residents. Initial estimates of all-cause mortality rates also spiked in early and late 2020 before falling to near or below historical rates by early 2021. During the first 3 years of the pandemic, the US nursing home resident population also decreased by 18% (239 000 fewer residents) compared with pre-pandemic levels.

Revisiting diabetes risk of olanzapine versus aripiprazole in serious mental illness care.

Background: Exposure to second-generation antipsychotics (SGAs) carries a risk of type 2 diabetes, but questions remain about the diabetogenic effects of SGAs.

Aims: To assess the diabetes risk associated with two frequently used SGAs.

Method: This was a retrospective cohort study of adults with schizophrenia, bipolar I disorder or severe major depressive disorder (MDD) exposed during 2008-2013 to continuous monotherapy with aripiprazole or olanzapine for up to 24 months, with no pre-period exposure to other antipsychotics.

Learning implementation of a guideline based decision support system to improve hypertension treatment in primary care in China: pragmatic cluster randomised controlled trial.

Objective: To evaluate the effectiveness of a clinical decision support system (CDSS) in improving the use of guideline accordant antihypertensive treatment in primary care settings in China.

Design: Pragmatic, open label, cluster randomised trial.

Setting: 94 primary care practices in four urban regions of China between August 2019 and July 2022: Luoyang (central China), Jining (east China), and Shenzhen (south China, including two regions).

Racial and Ethnic Differences in Telemedicine Use.

Importance: Individuals of racial and ethnic minority groups may be less likely to use telemedicine in part due to lack of access to technology (ie, digital divide). To date, some studies have found less telemedicine use by individuals of racial and ethnic minority groups compared with White individuals, and others have found the opposite. What explains these different findings is unclear.

Questioning a Sensible Result.

Contemporary data collection strategies, storage capabilities, and modern statistical methodology have made retrospective analyses of observational databases commonplace. Such databases afford opportunities to learn about the effectiveness and risks of interventions or health behaviors that generally cannot be randomized. In this issue of , Cho et al.

Classification Algorithm to Distinguish Between Type 1 and Type 2 Myocardial Infarction in Administrative Claims Data.

Background: Type 2 myocardial infarction (T2MI) and type 1 myocardial infarction (T1MI) differ with respect to demographics, comorbidities, treatments, and clinical outcomes. Reliable quality and outcomes assessment depends on the ability to distinguish between T1MI and T2MI in administrative claims data. As such, we aimed to develop a classification algorithm to distinguish between T1MI and T2MI that could be applied to claims data.

Trends in Use of Telemedicine for Stimulant Initiation Among Children and Adults.

Objective: The authors sought to examine trends in stimulant initiation and follow-up care for attention-deficit hyperactivity disorder (ADHD) via telemedicine.

Methods: This retrospective longitudinal study used national, deidentified commercial health insurance outpatient claims among children (ages 2-17 years; N=535,629) and adults (ages 18-64 years; N=2,116,160) from January 2019 through April 2022. Regression analyses were used to examine risk for stimulant initiation, whether initiation occurred via telemedicine or in-person care, and receipt of a follow-up visit.

Use of Telemedicine and Quality of Care Among Medicare Enrollees With Serious Mental Illness.

Importance: During the COVID-19 pandemic, a large fraction of mental health care was provided via telemedicine. The implications of this shift in care for use of mental health service and quality of care have not been characterized.

Objective: To compare changes in care patterns and quality during the first year of the pandemic among Medicare beneficiaries with serious mental illness (schizophrenia or bipolar I disorder) cared for at practices with higher vs lower telemedicine use.

Antipsychotics and the risk of diabetes and death among adults with serious mental illnesses.

Background: Individuals with schizophrenia exposed to second-generation antipsychotics (SGA) have an increased risk for diabetes, with aripiprazole purportedly a safer drug. Less is known about the drugs' mortality risk or whether serious mental illness (SMI) diagnosis or race/ethnicity modify these effects.

Methods: Authors created a retrospective cohort of non-elderly adults with SMI initiating monotherapy with an SGA (olanzapine, quetiapine, risperidone, and ziprasidone, aripiprazole) or haloperidol during 2008-2013.

Relationship Between In-Hospital Adverse Events and Hospital Performance on 30-Day All-cause Mortality and Readmission for Patients With Heart Failure.

Background: Hospitals with high mortality and readmission rates for patients with heart failure (HF) might also perform poorly in other quality concepts. We sought to evaluate the association between hospital performance on mortality and readmission with hospital performance rates of safety adverse events.

Methods: This cross-sectional study linked the 2009 to 2019 patient-level adverse events data from the Medicare Patient Safety Monitoring System, a randomly selected medical records-abstracted patient safety database, to the 2005 to 2016 hospital-level HF-specific 30-day all-cause mortality and readmissions data from the United States Centers for Medicare & Medicaid Services.

Healthcare Access for a Diverse Population with Schizophrenia Following the Onset of the COVID-19 Pandemic.

COVID-19 has had a disproportionate impact on the most disadvantaged members of society, including minorities and those with disabling chronic illnesses such as schizophrenia. We examined the pandemic's impacts among New York State's Medicaid beneficiaries with schizophrenia in the immediate post-pandemic surge period, with a focus on equity of access to critical healthcare. We compared changes in utilization of key behavioral health outpatient services and inpatient services for life-threatening conditions between the pre-pandemic and surge periods for White and non-White beneficiaries.

Evaluating The Accuracy Of Medicare Risk Adjustment For Alzheimer's Disease And Related Dementias.

In 2020 Medicare reintroduced Alzheimer's disease and related dementias (ADRD) Hierarchical Condition Categories (HCCs) to risk-adjust Medicare Advantage and accountable care organization (ACO) payments. The potential for Medicare spending increases from this policy change are not well understood because the baseline accuracy of ADRD HCCs is uncertain. Using linked 2016-18 claims and electronic health record data from a large ACO, we evaluated the accuracy of claims-based ADRD HCCs against a reference standard of clinician-adjudicated disease.

Analysis of Hospital-Level Readmission Rates and Variation in Adverse Events Among Patients With Pneumonia in the United States.

Importance: It is known that hospitalized patients who experience adverse events are at greater risk of readmission; however, it is unknown whether patients admitted to hospitals with higher risk-standardized readmission rates had a higher risk of in-hospital adverse events.

Objective: To evaluate whether patients with pneumonia admitted to hospitals with higher risk-standardized readmission rates had a higher risk of adverse events.

Design, Setting, And Participants: This cross-sectional study linked patient-level adverse events data from the Medicare Patient Safety Monitoring System (MPSMS), a randomly selected medical record abstracted database, to the hospital-level pneumonia-specific all-cause readmissions data from the Centers for Medicare & Medicaid Services.

Statistical Approaches for Quantifying the Quality of Neurosurgical Care.

Background: Quantifying quality of health care can provide valuable information to patients, providers, and policy makers. However, the observational nature of measuring quality complicates assessments.

Methods: We describe a conceptual model for defining quality and its implications about the data collected, how to make inferences about quality, and the assumptions required to provide statistically valid estimates.

Mortality Prediction After Cardiac Surgery in Children: An STS Congenital Heart Surgery Database Analysis.

Background: The Society of Thoracic Surgeons (STS) Congenital Heart Surgery Database (CHSD) provides risk-adjusted operative mortality rates to approximately 120 North American congenital heart centers. Optimal case-mix adjustment methods for operative mortality risk prediction in this population remain unclear.

Methods: A panel created diagnosis-procedure combinations of encounters in the CHSD.

Reevaluating Congenital Heart Surgery Center Performance Using Operative Mortality.

Background: The Society of Thoracic Surgeons Congenital Heart Surgery Database (STS-CHSD) provides observed-to-expected (O/E) operative mortality ratios to more than 100 congenital heart centers in North America. We compared the current approach for estimating O/E ratios to approaches incorporating information on diagnosis as moderators of procedures, other unused risk factors, and additional variation in confidence interval construction to characterize center performance.

Methods: Bayesian additive regression trees (BART) and lasso models linked operative mortality to diagnosis-procedure categories, procedure-specific risk factors, and syndromes/abnormalities.

Performance Metrics for the Comparative Analysis of Clinical Risk Prediction Models Employing Machine Learning.

Background: New methods such as machine learning techniques have been increasingly used to enhance the performance of risk predictions for clinical decision-making. However, commonly reported performance metrics may not be sufficient to capture the advantages of these newly proposed models for their adoption by health care professionals to improve care. Machine learning models often improve risk estimation for certain subpopulations that may be missed by these metrics.

All-Cause Mortality and Progression to End-Stage Kidney Disease Following Percutaneous Revascularization or Surgical Coronary Revascularization in Patients with CKD.

Introduction: Relative impacts of coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) on mortality and end-stage kidney disease (ESKD) in chronic kidney disease (CKD) are uncertain.

Methods: Data from Massachusetts residents with CKD undergoing CABG or PCI from 2003 to 2012 were linked to the United States Renal Data System. Associations with death, ESKD, and combined death and ESKD were analyzed in propensity score-matched multivariable survival models.

Factors Associated With Off-Label Utilization of Second-Generation Antipsychotics Among Publicly Insured Adults.

Objective: Off-label utilization of second-generation antipsychotic medications may expose patients to significant risks. The authors examined the prevalence, temporal trends, and factors associated with off-label utilization of second-generation antipsychotics among publicly insured adults.

Methods: A retrospective repeated panel was used to examine monthly off-label utilization of second-generation antipsychotics among fee-for-service Medicare, Medicaid, and dually eligible White, Black, and Latino adult beneficiaries filling prescriptions for second-generation antipsychotics in California, Georgia, Mississippi, and Oklahoma from July 2008 through June 2013.

Significance and Factors Associated with Antipsychotic Polypharmacy Utilization Among Publicly Insured US Adults.

Antipsychotic polypharmacy (APP) lacks evidence of effectiveness in the care of schizophrenia or other disorders for which antipsychotic drugs are indicated, also exposing patients to more risks. Authors assessed APP prevalence and APP association with beneficiary race/ethnicity and payer among publicly-insured adults regardless of diagnosis. Retrospective repeated panel study of fee-for-service (FFS) Medicare, Medicaid, and dually-eligible white, black, and Latino adults residing in California, Georgia, Iowa, Mississippi, Oklahoma, South Dakota, or West Virginia, filling antipsychotic prescriptions between July 2008 and June 2013.

Medication Utilization for Alcohol Use Disorder in a Commercially Insured Population.

Objective: Examine patterns of alcohol use disorder (AUD) medication use and identify factors associated with prescription fill among commercially insured individuals with an index AUD visit.

Design: Using 2008-2018 claims data from a large national insurer, estimate days to first AUD medication using cause-specific hazards approach to account for competing risk of benefits loss.

Participants: Aged 17-64 with ≥ 1 AUD visit.