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Application of Human Factors Methods to Understand Missed Follow-up of Abnormal Test Results. | LitMetric

AI Article Synopsis

Article Abstract

Objective: This study demonstrates application of human factors methods for understanding causes for lack of timely follow-up of abnormal test results ("missed results") in outpatient settings.

Methods: We identified 30 cases of missed test results by querying electronic health record data, developed a critical decision method (CDM)-based interview guide to understand decision-making processes, and interviewed physicians who ordered these tests. We analyzed transcribed responses using a contextual inquiry (CI)-based methodology to identify contextual factors contributing to missed results. We then developed a CI-based flow model and conducted a fault tree analysis (FTA) to identify hierarchical relationships between factors that delayed action.

Results: The flow model highlighted barriers in information flow and decision making, and the hierarchical model identified relationships between contributing factors for delayed action. Key findings including underdeveloped methods to track follow-up, as well as mismatches, in communication channels, timeframes, and expectations between patients and physicians.

Conclusion: This case report illustrates how human factors-based approaches can enable analysis of contributing factors that lead to missed results, thus informing development of preventive strategies to address them.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577780PMC
http://dx.doi.org/10.1055/s-0040-1716537DOI Listing

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