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DOI: 10.1055/s-0038-1667000
Simple Workflow Changes Enable Effective Patient Identity Matching in Poison Control
Funding This study was supported by the U.S. Department of Health and Human Services, Agency for Healthcare Research and Quality, grant 5R01HS021472, and the Office of the National Coordinator for Health Information Technology (901 × 003). The authors wish to acknowledge the assistance of the Utah Poison Control Center, Intermountain Healthcare, the Utah Health Information Network, and Dr. Tom H. Greene. Additional assistance was provided by the Center for Clinical and Translational Sciences of the National Institutes of Health under Award Number UL1TR001067. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health (NIH). Support and resources were also provided from the Center for High Performance Computing at The University of Utah, partially funded by the NIH Shared Instrumentation Grant 1S10OD021644–01A1.Publication History
30 January 2018
02 June 2018
Publication Date:
25 July 2018 (online)
Abstract
Background U.S. poison control centers pose a special case for patient identity matching because they collect only minimal patient identifying information.
Methods In early 2017, the Utah Poison Control Center (Utah PCC) initiated participation in regional health information exchange by sending Health Level Seven Consolidated Clinical Document Architecture (C-CDA) documents to the Utah Health Information Network and Intermountain Healthcare. To increase the documentation of patient identifiers by the Utah PCC, we (1) adapted documentation practices to enable more complete and consistent documentation, and (2) implemented staff training to improve collection of identifiers.
Results Compared with the same time period in 2016, the Utah PCC showed an increase of 27% (p < 0.001) in collection of birth date for cases referred to a health care facility, while improvements in the collection of other identifiers ranged from 0 to 8%. Automated patient identity matching was successful for 77% (100 of 130) of the C-CDAs.
Conclusion Historical processes and procedures for matching patient identities require adaptation or added functionality to adequately support the PCC use case.
Keywords
health information exchange - toxicology - delivery of health care - electronic health recordsProtection of Human and Animals Subjects
This study was reviewed and approved by the University of Utah Institutional Review Board.
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