%0 Journal Article
%A Muñoz, Monica A
%A Jeon, Nakyung
%A Staley, Benjamin
%A Henriksen, Carl
%A Xu, Dandan
%A Weberpals, Janick
%A Winterstein, Almut G
%T Predicting medication-associated altered mental status in hospitalized patients: Development and validation of a risk model.
%J American journal of health system pharmacy
%V 76
%N 13
%@ 1535-2900
%C Bethesda, Md.
%I Soc.
%M DKFZ-2019-01814
%P 953 - 963
%D 2019
%X This study presents a medication-associated altered mental status (AMS) risk model for real-time implementation in inpatient electronic health record (EHR) systems.We utilized a retrospective cohort of patients admitted to 2 large hospitals between January 2012 and October 2013. The study population included admitted patients aged ≥18 years with exposure to an AMS risk-inducing medication within the first 5 hospitalization days. AMS events were identified by a measurable mental status change documented in the EHR in conjunction with the administration of an atypical antipsychotic or haloperidol. AMS risk factors and AMS risk-inducing medications were identified from the literature, drug information databases, and expert opinion. We used multivariate logistic regression with a full and backward eliminated set of risk factors to predict AMS. The final model was validated with 100 bootstrap samples.During 194,156 at-risk days for 66,875 admissions, 262 medication-associated AMS events occurred (an event rate of 0.13
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:31361885
%R 10.1093/ajhp/zxz119
%U https://inrepo02.dkfz.de/record/144361