AMIA Annu Symp Proc - Medical alert management: a real-time adaptive decision support tool to reduce alert fatigue.

Tópicos

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Resumo

With the adoption of electronic medical records (EMRs), drug safety alerts are increasingly recognized as valuable tools for reducing adverse drug events and improving patient safety. However, even with proper tuning of the EMR alert parameters, the volume of unfiltered alerts can be overwhelming to users. In this paper, we design an adaptive decision support tool in which past cognitive overriding decisions of users are learned, adapted and used for filtering actions to be performed on current alerts. The filters are designed and learned based on a moving time window, number of alerts, overriding rates, and monthly overriding fluctuations. Using alerts from two separate years to derive filters and test performance, predictive accuracy rates of 91.3%-100% are achieved. The moving time window works better than a static training approach. It allows continuous learning and capturing of the most recent decision characteristics and seasonal variations in drug usage. The decision support system facilitates filtering of non-essential alerts and adaptively learns critical alerts and highlights them prominently to catch providers' attention. The tool can be plugged into an existing EMR system as an add-on, allowing real-time decision support to users without interfering with existing EMR functionalities. By automatically filtering the alerts, the decision support tool mitigates alert fatigue and allows users to focus resources on potentially vital alerts, thus reducing the occurrence of adverse drug events.

Resumo Limpo

adopt electron medic record emr drug safeti alert increas recogn valuabl tool reduc advers drug event improv patient safeti howev even proper tune emr alert paramet volum unfilt alert can overwhelm user paper design adapt decis support tool past cognit overrid decis user learn adapt use filter action perform current alert filter design learn base move time window number alert overrid rate month overrid fluctuat use alert two separ year deriv filter test perform predict accuraci rate achiev move time window work better static train approach allow continu learn captur recent decis characterist season variat drug usag decis support system facilit filter nonessenti alert adapt learn critic alert highlight promin catch provid attent tool can plug exist emr system addon allow realtim decis support user without interf exist emr function automat filter alert decis support tool mitig alert fatigu allow user focus resourc potenti vital alert thus reduc occurr advers drug event

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