Health informatics journal
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Health Informatics J · Sep 2020
Multicenter StudyMulticenter validation of a machine-learning algorithm for 48-h all-cause mortality prediction.
In order to evaluate mortality predictions based on boosted trees, this retrospective study uses electronic medical record data from three academic health centers for inpatients 18 years or older with at least one observation of each vital sign. Predictions were made 12, 24, and 48 hours before death. Models fit to training data from each institution were evaluated using hold-out test data from the same institution, and from the other institutions. ⋯ When trained and tested on data from different hospitals, GBT AUROCs achieved up to 0.98, 0.96, and 0.96, for 12-, 24-, and 48-hour predictions, respectively. Average AUROC for 48-hour predictions for LR, SVM, MEWS, and qSOFA were 0.85, 0.79, 0.86 and 0.82, respectively. GBT predictions may help identify patients who would benefit from increased clinical care.
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Health Informatics J · Jun 2017
Multicenter StudyAn analysis of electronic health record-related patient safety incidents.
The aim of this study was to analyse electronic health record-related patient safety incidents in the patient safety incident reporting database in fully digital hospitals in Finland. We compare Finnish data to similar international data and discuss their content with regard to the literature. We analysed the types of electronic health record-related patient safety incidents that occurred at 23 hospitals during a 2-year period. ⋯ The proportion of electronic health record-related incidents was markedly higher in our study than in previous studies with similar data. Human-computer interaction problems were the most frequently reported. The results show the possibility of error arising from the complex interaction between clinicians and computers.