Browsing by Subject "consolidation"

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    Consolidating CCDs from multiple data sources: A modular approach
    (Oxford, 2016-03) Hosseini, Masoud; Meade, Jonathan; Dixon, Brian E.; Epidemiology, School of Public Health
    Background Healthcare providers sometimes receive multiple continuity of care documents (CCDs) for a single patient encompassing the patient’s various encounters and medical history recorded in different information systems. It is cumbersome for providers to explore different pages of CCDs to find specific data which can be duplicated or even conflicted. This study describes initial steps toward a modular system that integrates and de-duplicates multiple CCDs into one consolidated document for viewing or processing patient-level data. Materials and Methods The authors developed a prototype system to consolidate and de-duplicate CCDs. The system is engineered to be scalable, extensible, and open source. Using a corpus of 150 de-identified CCDs synthetically generated from a single data source with a common vocabulary to represent 50 unique patients, the authors tested the system’s performance and output. Performance was measured based on document throughput and reduction in file size and volume of data. The authors further compared the output of the system with manual consolidation and de-duplication. Testing across multiple vendor systems or implementations was not performed. Results All of the input CCDs was successfully consolidated, and no data were lost. De-duplication significantly reduced the number of entries in different sections (49% in Problems, 60.6% in Medications, and 79% in Allergies) and reduced the size of the documents (57.5%) as well as the number of lines in each document (58%). The system executed at a rate of approximately 0.009–0.03 s per rule depending on the complexity of the rule. Discussion and Conclusion Given increasing adoption and use of health information exchange (HIE) to share data and information across the care continuum, duplication of information is inevitable. A novel system designed to support automated consolidation and de-duplication of information across clinical documents as they are exchanged shows promise. Future work is needed to expand the capabilities of the system and further test it using heterogeneous vocabularies across multiple HIE scenarios.
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    Reconciling disparate information in continuity of care documents: Piloting a system to consolidate structured clinical documents
    (Elsevier, 2017-10) Hosseini, Masoud; Jones, Josette; Faiola, Anthony; Vreeman, Daniel J.; Wu, Huanmei; Dixon, Brian E.; Department of BioHealth Informatics, School of Informatics and Computing
    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 150 h. The same data were automatically consolidated in 3.3 min. 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.