Performance of Predefined Search Patterns for Identifying Documented Goals-of-Care Discussions in Inpatient Electronic Health Records.

Abstract

Objective: To characterize the sensitivity and predictive value of predefined search terms for identifying documented goals-of-care discussions in health records of hospitalized patients with serious illness. Methods: We evaluated the performance of 30 previously published and investigator-defined search terms codified into regular expressions (a type of pattern-based text search) in detecting goals-of-care documentation in a 2974-note corpus of electronic health record notes belonging to 159 inpatients enrolled in a U.S. clinical trial over 2020-2021. Results: Compared to conventional chart abstraction, search terms for "goals of care" and synonyms such as "GOC" had poor sensitivity (range: 29.5-38.3%) and modest positive predictive value (PPV; range: 48.3-61.7%) for identifying notes with goals-of-care documentation. Combinations of search terms demonstrated modest performance (sensitivity 62.0%, PPV 59.4%, F₁ 0.61) but fell short of more complex natural language processing models. Conclusion: In certain contexts, predefined regular-expression-based search terms may have suboptimal sensitivity and predictive value for identifying documented goals-of-care discussions.