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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., Competing Interests: None declared., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Importance: To date, the association of psychiatric diagnoses with mortality in patients infected with coronavirus disease 2019 (COVID-19) has not been evaluated., Objective: To assess whether a diagnosis of a schizophrenia spectrum disorder, mood disorder, or anxiety disorder is associated with mortality in patients with COVID-19., Design, Setting, and Participants: This retrospective cohort study assessed 7348 consecutive adult patients for 45 days following laboratory-confirmed COVID-19 between March 3 and May 31, 2020, in a large academic medical system in New York. The final date of follow-up was July 15, 2020. Patients without available medical records before testing were excluded., Exposures: Patients were categorized based on the following International Statistical Classification of Diseases, Tenth Revision, Clinical Modification diagnoses before their testing date: (1) schizophrenia spectrum disorders, (2) mood disorders, and (3) anxiety disorders. Patients with these diagnoses were compared with a reference group without psychiatric disorders., Main Outcomes and Measures: Mortality, defined as death or discharge to hospice within 45 days following a positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) test result., Results: Of the 26 540 patients tested, 7348 tested positive for SARS-CoV-2 (mean [SD] age, 54 [18.6] years; 3891 [53.0%] women). Of eligible patients with positive test results, 75 patients (1.0%) had a history of a schizophrenia spectrum illness, 564 (7.7%) had a history of a mood disorder, and 360 (4.9%) had a history of an anxiety disorder. After adjusting for demographic and medical risk factors, a premorbid diagnosis of a schizophrenia spectrum disorder was significantly associated with mortality (odds ratio [OR], 2.67; 95% CI, 1.48-4.80). Diagnoses of mood disorders (OR, 1.14; 95% CI, 0.87-1.49) and anxiety disorders (OR, 0.96; 95% CI, 0.65-1.41) were not associated with mortality after adjustment. In comparison with other risk factors, a diagnosis of schizophrenia ranked behind only age in strength of an association with mortality., Conclusions and Relevance: In this cohort study of adults with SARS-CoV-2-positive test results in a large New York medical system, adults with a schizophrenia spectrum disorder diagnosis were associated with an increased risk for mortality, but those with mood and anxiety disorders were not associated with a risk of mortality. These results suggest that schizophrenia spectrum disorders may be a risk factor for mortality in patients with COVID-19.

We previously identified significantly decreased rates of peer discussion and deviation detection in virtual radiotherapy (RT) peer review (PR) conferences during the COVID-19 pandemic. We performed a follow-up analysis of these outcomes (totaling 5,559 cases across both studies) and surveyed participants before and after transition back to in-person PR at the end of the COVID-19 public health emergency. A prospectively maintained PR database was queried for consecutive cases reviewed before and after the transition from virtual to in-person conferences. Rates of PR discussion and deviation detection were summarized and compared between the virtual and in-person groups. A survey of conference participants' perceptions and preferences on the format of our weekly PR conference was developed and conducted during virtual PR and after 3 months after the transition to in-person PR. In total, 2,110 RT plans were reviewed, 1,592 virtually and 518 after the transition back to in-person. Two hundred eighty-six cases (13.6%) had at least one PR discussion topic recorded. The most common discussion topics included dose/fractionation (4.6%), normal tissue exposure (3.6%), and target coverage (2.2%). Peer discussion significantly increased after transition from virtual format (no discussion: 90.3%; 1 topic discussed: 8.0%; 2+ topics discussed: 1.7%) to in-person format (no discussion = 74.7%; 1 topic = 15.8%; and 2+ topics = 9.5%; P < 0.001). There was also a significant increase in the rate of deviation detection from virtual (1.5%) to in-person (3.3%, P = 0.016) conferences. Of 35 invited participants (faculty, residents, physicists, dosimetrists, and staff), 31 completed a baseline survey during virtual PR and 28 completed the in-person follow-up survey. Compared to virtual, in-person PR was associated with a significant decrease in perceived distraction (P = 0.003). There were no significant differences in perceived level of engagement in, absorption by, or concentration on the conference. During virtual PR, 43% of respondents preferred in-person compared with 52% after 3-months of in-person PR (P = 0.529). At both timepoints, most respondents believed that in-person format was best for encouraging PR discussion (61-65%) and detecting/correcting errors (54-58%). In this follow-up analysis of a longitudinal RT PR database, the transition from virtual to in-person PR resulted in increased rates of peer discussion and deviation detection, and decreased rates of self-reported distraction. These results suggest that an in-person component to PR is important and that efforts should be made to improve discussion and reduce distraction when performing virtual PR. [ABSTRACT FROM AUTHOR]