AI Article Synopsis
- - The study explores using electronic health record (EHR) systems and Tableau-based visualizations to enhance clinicians' understanding of patient data and improve clinical care.
- - Researchers developed visual tools linked to their EPIC EHR system through 12 quality improvement projects, highlighting 5 key themes relevant to project success.
- - By identifying common visual themes, the team aims to streamline the creation of future visual analytics, ultimately improving collaboration and efficiency in clinical settings.
Article Abstract
Objective: While electronic health record (EHR) systems store copious amounts of patient data, aggregating those data across patients can be challenging. Visual analytic tools that integrate with EHR systems allow clinicians to gain better insight and understanding into clinical care and management. We report on our experience building Tableau-based visualizations and integrating them into our EHR system.
Materials And Methods: Visual analytic tools were created as part of 12 clinician-initiated quality improvement projects. We built the visual analytic tools in Tableau and linked it within our EPIC environment. We identified 5 visual themes that spanned the various projects. To illustrate these themes, we choose 1 exemplary project which aimed to improve obstetric operating room efficiency.
Results: Across our 12 projects, we identified 5 visual themes that are integral to project success: scheduling & optimization (in 11/12 projects); provider assessment (10/12); executive assessment (8/12); patient outcomes (7/12); and control and goal charts (2/12).
Discussion: Many visualizations share common themes. Identification of these themes has allowed our internal team to be more efficient and directed in developing visualizations for future projects.
Conclusion: Organizing visual analytics into themes can allow informatics teams to more efficiently provide visual products to clinical collaborators.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7647303 | PMC |
| http://dx.doi.org/10.1093/jamia/ocaa016 | DOI Listing |
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