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Identifying clinician-reported medication "Failure modes" in the nursing home setting that are amenable to active
Chenyu Li1, Olga Kravchenko1, Eric Chou1
1Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Objectives:
Nursing home residents are at high-risk for preventable harm and medication errors. This study aimed to identify clinician-reported medication safety failure modes in U.S. nursing homes and prioritize those most suitable for informatics-enabled active monitoring interventions.
Methods:
We conducted a mixed-methods failure mode and effects analysis. Semi-structured interviews and field observations were conducted with 23 nursing home clinicians (duration 60-90 min). Interview anecdotes were translated into stepwise failure modes and represented as Unified Modeling Language (UML) workflow diagrams. Respondents rated each scenario's perceived seriousness, detectability, and frequency of routine monitoring; these ratings were combined to identify high-priority targets for intervention.
Results:
Fourteen failure modes were refined into 10 generalizable clinical scenarios and evaluated via a survey of 61 nursing home healthcare providers from a wide range of sites and roles. Across clinical roles, survey respondents consistently prioritized meclizine/psychotropic co-exposure and diuretic/mobility impairment co-exposure as high-priority scenarios for active monitoring. Scenarios involving psychotropic/CNS-active medications and potential drug-drug interactions were also frequently rated as important and not routinely monitored.
Conclusions:
Clinician-derived medication nursing home safety failure modes have been prioritized using multi-stakeholder survey input, yielding a focused set of targets for medication-safety monitoring in nursing homes.
Implications:
The identified high-priority scenarios can inform the design of automated monitoring tools and pharmacist/nursing workflows. Future work should validate these targets against resident outcomes and evaluate the effectiveness of monitoring interventions.
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