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EMR-based handoff tool improves completeness of internal medicine residents' handoffs.
BMJ Open Qual. 2018;7(3):e000188
Authors: Tisdale RL, Eggers Z, Shieh L
Abstract
Background: The majority of adverse events in healthcare involve communication breakdown. Physician-to-physician handoffs are particularly prone to communication errors, yet have been shown to be more complete when systematised according to a standardised bundle. Interventions that improve thoroughness of handoffs have not been widely studied.
Aim: To measure the effect of an electronic medical record (EMR)-based handoff tool on handoff completeness.
Intervention: This EMR-based handoff tool included a radio button prompting users to classify patients as stable, a 'watcher' or unstable. It automatically pulled in EMR data on the patient's 24-hour vitals, common lab tests and code status. Finally, it provided text boxes labelled 'Active Issues', 'Action List (To-Dos)' and 'If/Then' to fill in.
Implementation and evaluation: Written handoffs from general and specialty (haematology, oncology, cardiology) Internal Medicine resident-run inpatient wards were evaluated on a randomly chosen representative sample of days in April and May 2015 at Stanford University Medical Center, focusing on a predefined set of content elements. The intervention was then implemented in June 2015 with postintervention data collected in an identical fashion in August to September 2016.
Results: Handoff completeness improved significantly (p<0.0001). Improvement in inclusion of illness severity was notable for its magnitude and its importance in establishing a consistent mental model of a patient. Elements that automatically pulled in data and those prompting users to actively fill in data both improved.
Conclusion: A simple EMR-based handoff tool providing a mix of frameworks for completion and automatic pull-in of objective data improved handoff completeness. This suggests that EMR-based interventions may be effective at improving handoffs, possibly leading to fewer medical errors and better patient care.
PMID: 30019013 [PubMed]