Indexed on: 20 Dec '18Published on: 20 Dec '18Published in: Journal of the American Medical Informatics Association : JAMIA
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. 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. 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). Automating retrieval and reconciliation of information across multiple electronic documents shows promise for reducing healthcare providers' task complexity and workload.