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Identifying, Analyzing, and Visualizing Diagnostic Paths for Patients with Nonspecific Abdominal Pain
25 July 2018
25 October 2018
19 December 2018 (online)
Background Diagnosis is complex, uncertain, and error-prone. Symptoms such as nonspecific abdominal pain are especially challenging. A diagnostic path consists of diagnostic steps taken from initial presentation until a diagnosis is obtained or the evaluation ends for other reasons. Analysis of diagnostic paths can reveal patterns associated with more timely and accurate diagnosis. Visual analytics can be used to enhance both analysis and comprehension of diagnostic paths.
Objective This article applies process-mining methods to extract and visualize diagnostic paths from electronic health records (EHRs).
Methods Patient features, actions taken (i.e., tests, referrals, etc.), and diagnoses obtained for 501 adult patients (half female, half ≥50 years of age) presenting with abdominal pain were extracted from an EHR database to construct diagnostic paths from a hospital system in suburban Chicago, Illinois, United States. A stable diagnosis was defined as the same diagnosis recorded twice in a 12-month period; a working diagnosis was recorded only once. Three different types of path visualizations were obtained.
Results A stable diagnosis was obtained in 63 (13%) patients after 12 months. In 271 (54%) patients, a working diagnosis was obtained. Mean path duration was 145.3 days (standard deviation, 195.1 days). These 63 patients received 75 stable diagnoses.
Conclusion Structured EHR data can be used to construct diagnostic paths to gain insight into diagnostic practices for complaints such as abdominal pain.
Protection of Human and Animal Subjects
This study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects, and was reviewed and approved by the Institutional Review Board of the NorthShore University HealthSystem.
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