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Related Experiment Video

Updated: Jan 28, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
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Multi-Method Study of Electronic Health Records Workflows.

Adela Grando1,2, Areti Manataki3, Stephanie K Furniss1,2

  • 1Department of Biomedical Informatics, Arizona State University, AZ, US.

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|March 1, 2019
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Summary
This summary is machine-generated.

Electronic Health Records (EHRs) significantly impact clinical workflows. This study analyzed pre-operative EHR use, revealing substantial time spent on EHRs and variations across institutions.

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Area of Science:

  • Health Informatics
  • Clinical Workflow Analysis
  • Human-Computer Interaction

Background:

  • Electronic Health Records (EHRs) are integral to modern healthcare, influencing clinical practices and patient care quality.
  • Understanding the intricacies of EHR workflows, especially in complex settings like pre-operative care, is crucial for optimizing their use.
  • Existing research often lacks in-depth analysis of how EHRs are integrated into daily clinical routines.

Purpose of the Study:

  • To conduct a high-definition analysis of pre-operative workflows within a tertiary referral center.
  • To quantify the time spent by healthcare personnel interacting with EHR systems versus paper-based methods.
  • To compare EHR-based workflows between different hospital settings to identify variations and inefficiencies.

Main Methods:

  • A mixed-methods approach combining 18 interviews, 7 days of direct observation, and process mining of EHR interactions.
  • Data collected from 31 personnel involved in the care of 375 patients.
  • Social network analysis was used to validate observed EHR interactions.

Main Results:

  • Personnel spent 32.2% of their time interacting with the EHR and 4.2% using paper artifacts.
  • Detailed descriptions of pre-operative workflows and personnel roles were established.
  • Significant differences were observed in physical organization, patient flow, roles, EHR utilization, social networks, and time efficiency when comparing two similar pre-operative settings at different hospitals.

Conclusions:

  • EHR implementation profoundly affects healthcare work practices, with significant time investment required for system interaction.
  • Variability in EHR workflow design and implementation across institutions highlights the need for context-specific optimization.
  • Findings provide valuable insights for institutional EHR transitions and inform future workflow comparisons.