ReCAP: Detection of Potentially Avoidable Harm in Oncology From Patient Medical Records
Author(s) -
Allison LipitzSnyderman,
Saul N. Weingart,
Christopher B. Anderson,
Andrew S. Epstein,
Aileen R. Killen,
David C. Classen,
Camelia S. Sima,
Elizabeth Fortier,
Coral L. Atoria,
David G. Pfister
Publication year - 2016
Publication title -
journal of oncology practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.555
H-Index - 60
eISSN - 1935-469X
pISSN - 1554-7477
DOI - 10.1200/jop.2015.006874
Subject(s) - medicine , delphi method , medical record , medline , precision oncology , population , cancer , oncology , medical emergency , medical physics , computer science , environmental health , artificial intelligence , political science , law
QUESTION ASKED: Although medical record–based measurement of adverse events (AEs) associated with cancer care is desirable, condition-specific triggers in oncology care are needed. We sought to develop a screening tool to facilitate efficient detection of AEs across settings of cancer care via medical record review. We hope to use this tool to understand the frequency, spectrum, and preventability of AEs with the goal of helping improve the quality and safety of cancer care.SUMMARY ANSWER: We developed a cancer-specific screening tool to help identify candidate preventable AEs that occur during cancer care from patients’ medical records. Our oncology screening tool consists of 76 triggers—readily identifiable findings to screen for possible AEs that occur during cancer care ( Table 1 ).METHODS: We sought to develop a screening tool to facilitate the detection of AEs across settings of cancer care via medical record review. We obtained structured and unstructured input from clinical experts to develop our tool, using a modified Delphi process.BIAS, CONFOUNDING FACTOR(S), DRAWBACKS: Our oncology tool requires further evaluation in order to understand its usefulness for population-based assessments of AEs in oncology and quality improvement.REAL-LIFE IMPLICATIONS: Information obtained from structured record reviews using an oncology trigger tool could help to prioritize quality improvement activities, identify high-risk groups, and generate cancer-focused quality measures. Ultimately, the goals of this work are to prevent AEs and allow timely, automated identification of these events so that clinicians can intervene promptly to improve patient outcomes. [Table: see text]
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