Indication alerts to improve problem list documentation

• Published in: Journal of the American Medical Informatics Association : JAMIA 2022-04, Vol.29 (5), p.909-917
• Main Authors: Grauer, Anne, Kneifati-Hayek, Jerard, Reuland, Brian, Applebaum, Jo R, Adelman, Jason S, Green, Robert A, Lisak-Phillips, Jeanette, Liebovitz, David, Byrd, Thomas F, Kansal, Preeti, Wilkes, Cheryl, Falck, Suzanne, Larson, Connie, Shilka, John, VanDril, Elizabeth, Schiff, Gordon D, Galanter, William L, Lambert, Bruce L
• Format: Article
• Language: English
• Subjects: Decision Support Systems, Clinical; Documentation; Humans; Inpatients; Medical Order Entry Systems; Medication Errors - prevention & control; Research and Applications
• ISSN: 1527-974X; 1067-5027; 1527-974X
• DOI: 10.1093/jamia/ocab285

Abstract Background Problem lists represent an integral component of high-quality care. However, they are often inaccurate and incomplete. We studied the effects of alerts integrated into the inpatient and outpatient computerized provider order entry systems to assist in adding problems to the problem list when ordering medications that lacked a corresponding indication. Methods We analyzed medication orders from 2 healthcare systems that used an innovative indication alert. We collected data at site 1 between December 2018 and January 2020, and at site 2 between May and June 2021. We reviewed random samples of 100 charts from each site that had problems added in response to the alert. Outcomes were: (1) alert yield, the proportion of triggered alerts that led to a problem added and (2) problem accuracy, the proportion of problems placed that were accurate by chart review. Results Alerts were triggered 131 134, and 6178 times at sites 1 and 2, respectively, resulting in a yield of 109 055 (83.2%) and 2874 (46.5%), P< .001. Orders were abandoned, for example, not completed, in 11.1% and 9.6% of orders, respectively, P