A Decision Support System for Pathology Test Result Reviews in an Emergency Department to Support Patient Safety and Increase Efficiency

• Published in: Studies in health technology and informatics Vol. 264; p. 729
• Main Authors: Nguyen, Anthony, Hassanzadeh, Hamed, Zhang, Yushi, O'Dwyer, John, Conlan, David, Lawley, Michael, Steel, Jim, Loi, Kylynn, Rizzo, Peter
• Format: Journal Article
• Language: English
• Published: Netherlands 21-08-2019
• Subjects: Decision Support Systems, Clinical; Efficiency; Emergency Service, Hospital; Expert Systems; Humans; Patient Safety; Data Mining; Clinical Decision Support Systems; Emergency Medicine
• ISSN: 1879-8365
• DOI: 10.3233/SHTI190319

The review of pathology test results for missed diagnoses in Emergency Departments is time-consuming, laborious, and can be inaccurate. An automated solution, with text mining and clinical terminology semantic capabilities, was developed to provide clinical decision support. The system focused on the review of microbiology test results that contained information on culture strains and their antibiotic sensitivities, both of which can have a significant impact on ongoing patient safety and clinical care. The system was highly effective at identifying abnormal test results, reducing the number of test results for review by 92%. Furthermore, the system reconciled antibiotic sensitivities with documented antibiotic prescriptions in discharge summaries to identify patient follow-ups with a 91% F-measure - allowing for the accurate prioritization of cases for review. The system dramatically increases accuracy, efficiency, and supports patient safety by ensuring important diagnoses are recognized and correct antibiotics are prescribed.