Mayo Clinic Registry of Operational Tasks (ROOT)
| Autor: | Matthew M. Burton, Timothy A. Miksch, Bradley N. Doebbeling, Adela Grando, Stepahanie Furniss, David R. Kaufman, Karl A. Poterack, Richard A. Helmers |
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| Rok vydání: | 2019 |
| Předmět: |
lcsh:R5-920
Root (linguistics) HIT health information technology Social network Standardization business.industry Health information technology ROOT Registry of Operational Tasks 030204 cardiovascular system & hematology Data science Video ethnography 03 medical and health sciences 0302 clinical medicine Workflow EHR electronic health record Paradigm shift Medicine Original Article 030212 general & internal medicine lcsh:Medicine (General) business Implementation |
| Zdroj: | Mayo Clinic Proceedings: Innovations, Quality & Outcomes Mayo Clinic Proceedings: Innovations, Quality & Outcomes, Vol 3, Iss 3, Pp 319-326 (2019) |
| ISSN: | 2542-4548 |
| Popis: | Objective To systematically examine clinical workflows before and after a major electronic health record (EHR) implementation, we performed this study. EHR implementation and/or conversion are associated with many challenges, which are barriers to optimal care. Clinical workflows may be significantly affected by EHR implementations and conversions, resulting in provider frustration and reduced efficiency. Patients and Methods Our institution completed a large EHR conversion and workflow standardization converting from 3 EHRs (GE Centricity and 2 versions of Cerner) to a system-wide Epic platform. To study this quantitatively and qualitatively, we collected and curated clinical workflows through rapid ethnography, workflow observation, video ethnography, and log-file analyses of hundreds of providers, patients, and more than 100,000 log files. The study included 5 geographic sites in 4 states (Arizona, Minnesota, Florida, and Wisconsin). This project began in April 2016, and will be completed by December 2019. Our study began on May 1, 2016, and is ongoing. Results Salient themes include the importance of prioritizing clinical areas with the most intensive EHR use, the value of tools to identify bottlenecks in workflow that cause delays, and desire for additional training to optimize navigation. Video microanalyses identified marked differences in patterns of workflow and EHR navigation patterns across sites. Log-file analyses and social network analyses identified differences in personnel roles, which led to differences in patient–clinician interaction, time spent using the EHR, and paper-based artifacts. Conclusion Assessing and curating workflow data before and after EHR conversion may provide opportunities for unexpected efficiencies in workflow optimization and information-system redesign. This project may be a model for capturing significant new knowledge in using EHRs to improve patient care, workflow efficiency, and outcomes. |
| Databáze: | OpenAIRE |
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