Masoud Hosseini1, Josette Jones2, Anthony Faiola3, Daniel J Vreeman4, Huanmei Wu2, Brian E Dixon5. 1. Department of BioHealth Informatics, School of Informatics and Computing at Indiana University-Purdue University Indianapolis, Walker Plaza (WK), 719 Indiana Avenue, WK 117, Indianapolis, IN 46202, United States. Electronic address: massood.hosseini@gmail.com. 2. Department of BioHealth Informatics, School of Informatics and Computing at Indiana University-Purdue University Indianapolis, Walker Plaza (WK), 719 Indiana Avenue, WK 117, Indianapolis, IN 46202, United States. 3. Biomedical and Health Information Sciences, College of Applied Health Sciences, The University of Illinois at Chicago, United States. 4. School of Medicine, Indiana University, United States. 5. Department of Epidemiology, Richard M. Fairbanks School of Public health, Indiana University-Purdue University Indianapolis, United States.
Abstract
BACKGROUND: Due to the nature of information generation in health care, clinical documents contain duplicate and sometimes conflicting information. Recent implementation of Health Information Exchange (HIE) mechanisms in which clinical summary documents are exchanged among disparate health care organizations can proliferate duplicate and conflicting information. MATERIALS AND METHODS: To reduce information overload, a system to automatically consolidate information across multiple clinical summary documents was developed for an HIE network. The system receives any number of Continuity of Care Documents (CCDs) and outputs a single, consolidated record. To test the system, a randomly sampled corpus of 522 CCDs representing 50 unique patients was extracted from a large HIE network. The automated methods were compared to manual consolidation of information for three key sections of the CCD: problems, allergies, and medications. RESULTS: Manual consolidation of 11,631 entries was completed in approximately 150h. The same data were automatically consolidated in 3.3min. The system successfully consolidated 99.1% of problems, 87.0% of allergies, and 91.7% of medications. Almost all of the inaccuracies were caused by issues involving the use of standardized terminologies within the documents to represent individual information entries. CONCLUSION: This study represents a novel, tested tool for de-duplication and consolidation of CDA documents, which is a major step toward improving information access and the interoperability among information systems. While more work is necessary, automated systems like the one evaluated in this study will be necessary to meet the informatics needs of providers and health systems in the future.
BACKGROUND: Due to the nature of information generation in health care, clinical documents contain duplicate and sometimes conflicting information. Recent implementation of Health Information Exchange (HIE) mechanisms in which clinical summary documents are exchanged among disparate health care organizations can proliferate duplicate and conflicting information. MATERIALS AND METHODS: To reduce information overload, a system to automatically consolidate information across multiple clinical summary documents was developed for an HIE network. The system receives any number of Continuity of Care Documents (CCDs) and outputs a single, consolidated record. To test the system, a randomly sampled corpus of 522 CCDs representing 50 unique patients was extracted from a large HIE network. The automated methods were compared to manual consolidation of information for three key sections of the CCD: problems, allergies, and medications. RESULTS: Manual consolidation of 11,631 entries was completed in approximately 150h. The same data were automatically consolidated in 3.3min. The system successfully consolidated 99.1% of problems, 87.0% of allergies, and 91.7% of medications. Almost all of the inaccuracies were caused by issues involving the use of standardized terminologies within the documents to represent individual information entries. CONCLUSION: This study represents a novel, tested tool for de-duplication and consolidation of CDA documents, which is a major step toward improving information access and the interoperability among information systems. While more work is necessary, automated systems like the one evaluated in this study will be necessary to meet the informatics needs of providers and health systems in the future.
Keywords:
Clinical Document Architecture (CDA); Consolidation; Continuity of Care Document (CCD); De-duplication; Health Information Exchange (HIE); Health Level Seven (HL7)
Authors: Masoud Hosseini; Anthony Faiola; Josette Jones; Daniel J Vreeman; Huanmei Wu; Brian E Dixon Journal: J Am Med Inform Assoc Date: 2019-02-01 Impact factor: 4.497
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