Abstract
We evaluated disagreement between reported symptoms and a final diagnosis of depression, anxiety, withdrawal, psychosis, or delirium through regression models assessing individual and combined diagnoses. Highest disagreement rates were reported for services classified as others (88.2%), general surgery (78.5%), and bone marrow transplant (77.7%). Disagreement rates varied widely across different diagnoses, with anxiety having the highest disagreement rate (63.3%), whereas psychosis had the lowest disagreement rate (10.6%). When evaluating kappa coefficients, the highest agreement occurred with diagnoses of withdrawal and psychosis (0.66% and 0.51%, respectively), whereas anxiety and depression presented the lowest values (0.31% and 0.11%, respectively). The best-performing predictive model for most outcomes was random forest, with the most important predictors being specialties other than the ones focused on single systems, older age, lack of social support, and the requester being a resident. Monitoring disagreement rates and their predictors provides information that could lead to quality improvement and safety programs.
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