Person: Wright, Adam
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Publication Variation in high-priority drug-drug interaction alerts across institutions and electronic health records
(Oxford University Press, 2016) McEvoy, Dustin S; Sittig, Dean F; Hickman, Thu-Trang; Aaron, Skye; Ai, Angela; Amato, Mary; Bauer, David W; Fraser, Gregory M; Harper, Jeremy; Kennemer, Angela; Krall, Michael A; Lehmann, Christoph U; Malhotra, Sameer; Murphy, Daniel R; O’Kelley, Brandi; Samal, Lipika; Schreiber, Richard; Singh, Hardeep; Thomas, Eric J; Vartian, Carl V; Westmorland, Jennifer; McCoy, Allison B; Wright, AdamObjective: The United States Office of the National Coordinator for Health Information Technology sponsored the development of a “high-priority” list of drug-drug interactions (DDIs) to be used for clinical decision support. We assessed current adoption of this list and current alerting practice for these DDIs with regard to alert implementation (presence or absence of an alert) and display (alert appearance as interruptive or passive). Materials and methods: We conducted evaluations of electronic health records (EHRs) at a convenience sample of health care organizations across the United States using a standardized testing protocol with simulated orders. Results: Evaluations of 19 systems were conducted at 13 sites using 14 different EHRs. Across systems, 69% of the high-priority DDI pairs produced alerts. Implementation and display of the DDI alerts tested varied between systems, even when the same EHR vendor was used. Across the drug pairs evaluated, implementation and display of DDI alerts differed, ranging from 27% (4/15) to 93% (14/15) implementation. Discussion: Currently, there is no standard of care covering which DDI alerts to implement or how to display them to providers. Opportunities to improve DDI alerting include using differential displays based on DDI severity, establishing improved lists of clinically significant DDIs, and thoroughly reviewing organizational implementation decisions regarding DDIs. Conclusion: DDI alerting is clinically important but not standardized. There is significant room for improvement and standardization around evidence-based DDIs.
Publication Analysis of clinical decision support system malfunctions: a case series and survey
(Oxford University Press, 2016) Wright, Adam; Hickman, Thu-Trang T; McEvoy, Dustin; Aaron, Skye; Ai, Angela; Andersen, Jan Marie; Hussain, Salman; Ramoni, Rachel; Fiskio, Julie; Sittig, Dean F; Bates, DavidObjective: To illustrate ways in which clinical decision support systems (CDSSs) malfunction and identify patterns of such malfunctions. Materials and Methods We identified and investigated several CDSS malfunctions at Brigham and Women’s Hospital and present them as a case series. We also conducted a preliminary survey of Chief Medical Information Officers to assess the frequency of such malfunctions. Results: We identified four CDSS malfunctions at Brigham and Women’s Hospital: (1) an alert for monitoring thyroid function in patients receiving amiodarone stopped working when an internal identifier for amiodarone was changed in another system; (2) an alert for lead screening for children stopped working when the rule was inadvertently edited; (3) a software upgrade of the electronic health record software caused numerous spurious alerts to fire; and (4) a malfunction in an external drug classification system caused an alert to inappropriately suggest antiplatelet drugs, such as aspirin, for patients already taking one. We found that 93% of the Chief Medical Information Officers who responded to our survey had experienced at least one CDSS malfunction, and two-thirds experienced malfunctions at least annually. Discussion CDSS malfunctions are widespread and often persist for long periods. The failure of alerts to fire is particularly difficult to detect. A range of causes, including changes in codes and fields, software upgrades, inadvertent disabling or editing of rules, and malfunctions of external systems commonly contribute to CDSS malfunctions, and current approaches for preventing and detecting such malfunctions are inadequate. Conclusion: CDSS malfunctions occur commonly and often go undetected. Better methods are needed to prevent and detect these malfunctions.