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Effectiveness of non-interruptive nudge interventions in electronic health records to improve the delivery of care in hospitals: a systematic review

2023·38 Zitationen·Journal of the American Medical Informatics AssociationOpen Access
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38

Zitationen

5

Autoren

2023

Jahr

Abstract

OBJECTIVES: To describe the application of nudges within electronic health records (EHRs) and their effects on inpatient care delivery, and identify design features that support effective decision-making without the use of interruptive alerts. MATERIALS AND METHODS: We searched Medline, Embase, and PsychInfo (in January 2022) for randomized controlled trials, interrupted time-series and before-after studies reporting effects of nudge interventions embedded in hospital EHRs to improve care. Nudge interventions were identified at full-text review, using a pre-existing classification. Interventions using interruptive alerts were excluded. Risk of bias was assessed using the ROBINS-I tool (Risk of Bias in Non-randomized Studies of Interventions) for non-randomized studies or the Cochrane Effective Practice and Organization of Care Group methodology for randomized trials. Study results were summarized narratively. RESULTS: We included 18 studies evaluating 24 EHR nudges. An improvement in care delivery was reported for 79.2% (n = 19; 95% CI, 59.5-90.8) of nudges. Nudges applied were from 5 of 9 possible nudge categories: change choice defaults (n = 9), make information visible (n = 6), change range or composition of options (n = 5), provide reminders (n = 2), and change option-related effort (n = 2). Only one study had a low risk of bias. Nudges targeted ordering of medications, laboratory tests, imaging, and appropriateness of care. Few studies evaluated long-term effects. DISCUSSION: Nudges in EHRs can improve care delivery. Future work could explore a wider range of nudges and evaluate long-term effects. CONCLUSION: Nudges can be implemented in EHRs to improve care delivery within current system capabilities; however, as with all digital interventions, careful consideration of the sociotechnical system is crucial to enhance their effectiveness.

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Electronic Health Records SystemsMachine Learning in HealthcareHealthcare cost, quality, practices
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