Using multiclass classification to automate the identification of patient safety incident reports by type and severity.
Journal:
BMC medical informatics and decision making
Published Date:
Jun 12, 2017
Abstract
BACKGROUND: Approximately 10% of admissions to acute-care hospitals are associated with an adverse event. Analysis of incident reports helps to understand how and why incidents occur and can inform policy and practice for safer care. Unfortunately our capacity to monitor and respond to incident reports in a timely manner is limited by the sheer volumes of data collected. In this study, we aim to evaluate the feasibility of using multiclass classification to automate the identification of patient safety incidents in hospitals.