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Background: Driven by quality outcomes and economic incentives, predicting 30-day hospital readmissions remains important for healthcare systems. The Cleveland Clinic Health System (CCHS) implemented an internally validated readmission risk score in the electronic medical record (EMR)., Objective: We evaluated the predictive accuracy of the readmission risk score across CCHS hospitals, across primary discharge diagnosis categories, between surgical/medical specialties, and by race and ethnicity., Design: Retrospective cohort study., Participants: Adult patients discharged from a CCHS hospital April 2017-September 2020., Main Measures: Data was obtained from the CCHS EMR and billing databases. All patients discharged from a CCHS hospital were included except those from Oncology and Labor/Delivery, patients with hospice orders, or patients who died during admission. Discharges were categorized as surgical if from a surgical department or surgery was performed. Primary discharge diagnoses were classified per Agency for Healthcare Research and Quality Clinical Classifications Software Level 1 categories. Discrimination performance predicting 30-day readmission is reported using the c-statistic., Results: The final cohort included 600,872 discharges from 11 Northeast Ohio and Florida CCHS hospitals. The readmission risk score for the cohort had a c-statistic of 0.6875 with consistent yearly performance. The c-statistic for hospital sites ranged from 0.6762, CI [0.6634, 0.6876], to 0.7023, CI [0.6903, 0.7132]. Medical and surgical discharges showed consistent performance with c-statistics of 0.6923, CI [0.6807, 0.7045], and 0.6802, CI [0.6681, 0.6925], respectively. Primary discharge diagnosis showed variation, with lower performance for congenital anomalies and neoplasms. COVID-19 had a c-statistic of 0.6387. Subgroup analyses showed c-statistics of > 0.65 across race and ethnicity categories., Conclusions: The CCHS readmission risk score showed good performance across diverse hospitals, across diagnosis categories, between surgical/medical specialties, and by patient race and ethnicity categories for 3 years after implementation, including during COVID-19. Evaluating clinical decision-making tools post-implementation is crucial to determine their continued relevance, identify opportunities to improve performance, and guide their appropriate use., (© 2022. The Author(s) under exclusive licence to Society of General Internal Medicine.)

Background: The restructuring of healthcare systems to cope with the demands of the COVID-19 pandemic has led to a reduction in clinical services such as cancer screening and diagnostics., Methods: Data from the four Northern Ireland pathology laboratories were used to assess trends in pathological cancer diagnoses from 1st March to 12th September 2020 overall and by cancer site, sex and age. These trends were compared to the same timeframe from 2017 to 2019., Results: Between 1st March and 12th September 2020, there was a 23% reduction in cancer diagnoses compared to the same time period in the preceding 3 years. Although some recovery occurred in August and September 2020, this revealed inequalities across certain patient groups. Pathological diagnoses of lung, prostate and gynaecological malignancies remained well below pre-pandemic levels. Males and younger/middle-aged adults, particularly the 50-59-year-old patient group, also lagged behind other population demographic groups in terms of returning to expected numbers of pathological cancer diagnoses., Conclusions: There is a critical need to protect cancer diagnostic services in the ongoing pandemic to facilitate timely investigation of potential cancer cases. Targeted public health campaigns may be needed to reduce emerging inequalities in cancer diagnoses as the COVID-19 pandemic continues., (© 2021. The Author(s).)

Background: The clinical characteristics and outcomes associated with non-intensive care unit (non-ICU) hospitalizations for coronavirus disease 2019 (COVID-19) outside disease epicenters remain poorly characterized., Methods: Systematic analysis of all non-ICU patient hospitalizations for COVID-19 completing discharge between March 13 and May 1, 2020, in a large US health care system utilizing off-site central monitoring. Variables of interest were examined in relation to a composite event rate of death, ICU transfer, or increased oxygen requirement to high-flow nasal cannula, noninvasive ventilation, or mechanical ventilation., Results: Among 350 patients (age, 64 ± 16 years; 55% male), most (73%) required 3 L/min or less of supplemental oxygen during admission. Telemetry was widely utilized (79%) yet arrhythmias were uncommon (14%) and were predominantly (90%) among patients with abnormal troponin levels or known cardiovascular disease. Ventricular tachycardia was rare (5%), nonsustained, and not associated with hydroxychloroquine/azithromycin treatment. Adverse events occurred in 62 patients (18%), including 22 deaths (6%), 48 ICU transfers (14%), and 49 patients with increased oxygen requirement (14%) and were independently associated with elevated C-reactive protein (odds ratio, 1.09 per 1 mg/dL; 95% CI, 1.01-1.18; P = .04) and lactate dehydrogenase (OR, 1.006 per 1U/L; 95% CI, 1.001-1.012; P = .03) in multivariable analysis., Conclusion: Among non-critically ill patients hospitalized within a nonepicenter health care system, overall survival was 94% with the development of more severe illness or death independently associated with higher levels of C-reactive protein and lactate dehydrogenase on admission. Clinical decompensation was largely respiratory-related, while serious cardiac arrhythmias were rare, which suggests that telemetry can be prioritized for high-risk patients.