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Process Mining and Ethnography Study of Medication Reconciliation Tasks.

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Analyzing electronic health record (EHR) systems, this study found significant differences in time spent on medication reconciliation (MedRec). One EHR system enabled more efficient MedRec workflows, highlighting the impact of system design on clinical tasks.

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Area of Science:

  • Health Informatics
  • Clinical Workflow Analysis
  • Electronic Health Records (EHR)

Background:

  • Medication reconciliation (MedRec) is a critical patient safety process.
  • Evaluating the efficiency of MedRec within different Electronic Health Record (EHR) systems is essential for optimizing clinical workflows.

Purpose of the Study:

  • To compare the time healthcare providers spent on the MedRec task across two different EHR systems.
  • To assess the feasibility of using computer logs for automated task analysis in healthcare settings.

Main Methods:

  • Analysis of computer logs and ethnographic data from four regional perioperative settings.
  • Comparison of MedRec task duration between two EHR systems, with log data validation.
  • Identification and removal of outliers from collected data.

Main Results:

  • Only one EHR system provided computer logs suitable for automatic MedRec task discovery.
  • After outlier removal, one setting showed a statistically significant lower mean time for MedRec (67.3 seconds) compared to the other (92.1 seconds).
  • The study demonstrated the reusability of a task-based analytic method for EHR workflow analysis.

Conclusions:

  • EHR system design significantly impacts the efficiency of clinical tasks like medication reconciliation.
  • Automated analysis of computer logs, when validated, offers a rapid method for studying healthcare provider workflows.
  • Optimizing EHR systems can lead to substantial time savings in critical clinical processes.