ArticleHealth information science and systems2026
Inter-clinician diagnostic agreement of shock etiology: a multicenter observational study.
Article in Health information science and systems, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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18 authors.
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Abstract
Purpose: We sought to (1) quantify lack of inter-clinician diagnostic agreement of shock etiology and (2) predict patients without complete inter-clinician diagnostic agreement of shock etiology. Methods: This multicenter retrospective, cohort study identified patients evaluated by two or more clinicians who documented a shock diagnosis from 2018 to 2023 across intensive care units (ICU) at 9 acute care hospitals. Shock etiology was abstracted using regular expression from clinician notes in the electronic health record then was made into a 9-dimensional vector representing 9 different shock etiologies. Inter-clinician diagnostic agreement of these vectors was calculated for each patient using Cosine Similarity Scores. Measure of agreement was based on cosine similarity of etiology vectors, not clinical adjudication. Patients without complete inter-clinician diagnostic agreement (Cosine Similarity Score < 1) were compared to patients with diagnostic agreement. Machine learning models were tested to predict patients without complete inter-clinician diagnostic agreement. Results: Of 7302 patients, 1327 (18.2%) never had complete inter-clinician diagnostic agreement. Patients without diagnostic agreement were more often Black (20.5 vs 16.2%, Conclusion: Patients without complete inter-clinician diagnostic agreement of shock etiology can be successfully predicted. Supplementary Information: The online version contains supplementary material available at 10.1007/s13755-025-00423-w.
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