Impact of document consolidation on healthcare providers' perceived workload and information reconciliation tasks: a mixed methods study. (19th December 2018)

• Record Type: Journal Article
• Authors: Hosseini, Masoud; Faiola, Anthony; Jones, Josette; Vreeman, Daniel J; Wu, Huanmei; Dixon, Brian E
• Is Part Of: Journal of the American Medical Informatics Association. Volume 26:Number 2(2019)
• Page Start: 134
• Page End: 142
• Publication Date: 2018-12-19
• Subjects: workload -- de-duplication -- consolidation -- Clinical Document Architecture (CDA) -- Continuity of Care Document (CCD) -- Health Information Exchange (HIE) -- Health Level Seven (HL7) -- meaningful use -- NASA-TLX; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocy158
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: Background: Information reconciliation is a common yet complex and often time-consuming task performed by healthcare providers. While electronic health record systems can receive "outside information" about a patient in electronic documents, rarely does the computer automate reconciling information about a patient across all documents. Materials and Methods: Using a mixed methods design, we evaluated an information system designed to reconcile information across multiple electronic documents containing health records for a patient received from a health information exchange (HIE) network. Nine healthcare providers participated in scenario-based sessions in which they manually consolidated information across multiple documents. Accuracy of consolidation was measured along with the time spent completing 3 different reconciliation scenarios with and without support from the information system. Participants also attended an interview about their experience. Perceived workload was evaluated quantitatively using the NASA-TLX tool. Qualitative analysis focused on providers' impression of the system and the challenges faced when reconciling information in practice. Results: While 5 providers made mistakes when trying to manually reconcile information across multiple documents, no participants made a mistake when the system supported their work. Overall perceived workload decreased significantly for scenarios supported by the system (37.2% in referrals, 18.4% in medications, and 31.5% in problems scenarios, P < 0.001). Information reconciliation time was reduced significantly when the system supported provider tasks (58.8% in referrals, 38.1% in medications, and 65.1% in problem scenarios). Conclusion: Automating retrieval and reconciliation of information across multiple electronic documents shows promise for reducing healthcare providers' task complexity and workload.