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

Deevakar Rogith, Tyler Satterly, Hardeep Singh, Dean F. Sittig, Elise Russo, Michael W. Smith, Don Roosan, Viraj Bhise, Daniel R. Murphy

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)692-698
Number of pages7
JournalApplied Clinical Informatics
Volume11
Issue number5
DOIs
StatePublished - Oct 1 2020
Externally publishedYes

Keywords

  • abnormal laboratory follow-up
  • contextual inquiry
  • fault tree analysis
  • human factors
  • patient safety

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications
  • Health Information Management

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