Article ; Online: Forms or Free-Text? Measuring Advance Care Planning Activity Using Electronic Health Records.
Journal of pain and symptom management
2023 Volume 66, Issue 5, Page(s) e615–e624
Abstract: Advance care planning (ACP) discussions seek to guide future serious illness care. These discussions may be recorded in the electronic health record by documentation in clinical notes, structured forms and directives, and physician orders. Yet, most ... ...
Abstract | Advance care planning (ACP) discussions seek to guide future serious illness care. These discussions may be recorded in the electronic health record by documentation in clinical notes, structured forms and directives, and physician orders. Yet, most studies of ACP prevalence have only examined structured electronic health record elements and ignored data existing in notes. We sought to investigate the relative comprehensiveness and accuracy of ACP documentation from structured and unstructured electronic health record data sources. We evaluated structured and unstructured ACP documentation present in the electronic health records of 435 patients with cancer drawn from three separate healthcare systems. We extracted structured ACP documentation by manually annotating written documents and forms scanned into the electronic health record. We coded unstructured ACP documentation using a rule-based natural language processing software that identified ACP keywords within clinical notes and was subsequently reviewed for accuracy. The unstructured approach identified more instances of ACP documentation (238, 54.7% of patients) than the structured ACP approach (187, 42.9% of patients). Additionally, 16.6% of all patients with structured ACP documentation only had documents that were judged as misclassified, incomplete, blank, unavailable, or a duplicate of a previously entered erroneous document. ACP documents scanned into electronic health records represent a limited view of ACP activity. Research and measures of clinical practice with ACP should incorporate information from unstructured data. |
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Language | English |
Publishing date | 2023-08-01 |
Publishing country | United States |
Document type | Journal Article ; Review |
ZDB-ID | 639142-4 |
ISSN | 1873-6513 ; 0885-3924 |
ISSN (online) | 1873-6513 |
ISSN | 0885-3924 |
DOI | 10.1016/j.jpainsymman.2023.07.016 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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