ArticlePloS one2020
Automated EHR score to predict COVID-19 outcomes at US Department of Veterans Affairs.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed, 49 citations in OpenAlex.
- Effectiveness of COVID-19 Treatment With Nirmatrelvir-Ritonavir or Molnupiravir Among U.S. Veterans: Target Trial Emulation Studies With One-Month and Six-Month Outcomes.Annals of internal medicine · 2023Trial
- Predicting Falls With the Morse Fall Scale: A Retrospective Assessment at the Veterans Health Administration.Clinical nursing research · 2026Article
- Effectiveness of the 2024-2025 KP.2 COVID-19 vaccines in the United States during long-term follow-up.Nature communications · 2025Article
- GPT, ontology, and CAABAC: A tripartite personalized access control model anchored by compliance, context and attribute.PloS one · 2025Article
- Exploring the Relation between Contextual Social Determinants of Health and COVID-19 Occurrence and Hospitalization.Informatics (MDPI) · 2024Article
- Observational
- Article
- Unhealthy alcohol use and brief intervention rates among high and low complexity veterans seeking primary care services in the Veterans Health Administration.Journal of substance use and addiction treatment · 2023Article
- Evaluating resilience in response to COVID-19 pandemic stressors among veteran mental health outpatients.Journal of psychopathology and clinical science · 2023Article
- Sentiment analysis of medical record notes for lung cancer patients at the Department of Veterans Affairs.PloS one · 2023Article
- Leveraging A Clinical Dashboard and Process Mappings to Improve Treatment Access and Outcomes for Women Veterans with Urinary Incontinence.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- Effectiveness of COVID-19 treatment with nirmatrelvir-ritonavir or molnupiravir among U.S. Veterans: target trial emulation studies with one-month and six-month outcomes.medRxiv : the preprint server for health sciences · 2022Article
- Translational Bioinformatics to Enable Precision Medicine for All: Elevating Equity across Molecular, Clinical, and Digital Realms.Yearbook of medical informatics · 2022Review
- The Power of Patient Engagement With Electronic Health Records as Research Participants.JMIR medical informatics · 2022Article
- Comparison of Moderna versus Pfizer-BioNTech COVID-19 vaccine outcomes: A target trial emulation study in the U.S. Veterans Affairs healthcare system.EClinicalMedicine · 2022Article
- Peeking into a black box, the fairness and generalizability of a MIMIC-III benchmarking model.Scientific data · 2022Article
- Impact of the COVID-19 Pandemic on HIM Professionals in a Rural State.Perspectives in health information managemen · 2022Article
- Natural Language Processing Enhances Prediction of Functional Outcome After Acute Ischemic Stroke.Journal of the American Heart Association · 2021Article
- Article
- Designing COVID-19 mortality predictions to advance clinical outcomes: Evidence from the Department of Veterans Affairs.BMJ health & care informatics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The sudden emergence of COVID-19 has brought significant challenges to the care of Veterans. An improved ability to predict a patient's clinical course would facilitate optimal care decisions, resource allocation, family counseling, and strategies for safely easing distancing restrictions. The Care Assessment Need (CAN) score is an existing risk assessment tool within the Veterans Health Administration (VA), and produces a score from 0 to 99, with a higher score correlating to a greater risk. The model was originally designed for the nonacute outpatient setting and is automatically calculated from structured data variables in the electronic health record. This multisite retrospective study of 6591 Veterans diagnosed with COVID-19 from March 2, 2020 to May 26, 2020 was designed to assess the utility of repurposing the CAN score as objective and automated risk assessment tool to promptly enhance clinical decision making for Veterans diagnosed with COVID-19. We performed bivariate analyses on the dichotomized CAN 1-year mortality score (high vs. low risk) and each patient outcome using Chi-square tests of independence. Logistic regression models using the continuous CAN score were fit to assess its predictive power for outcomes of interest. Results demonstrated that a CAN score greater than 50 was significantly associated with the following outcomes after positive COVID-19 test: hospital admission (OR 4.6), prolonged hospital stay (OR 4.5), ICU admission (3.1), prolonged ICU stay (OR 2.9), mechanical ventilation (OR 2.6), and mortality (OR 7.2). Repurposing the CAN score offers an efficient way to risk-stratify COVID-19 Veterans. As a result of the compelling statistical results, and automation, this tool is well positioned for broad use across the VA to enhance clinical decision-making.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.