Electronic Medical Record Inaccuracies: Multicenter Analysis of Challenges with Modified Lung Cancer Screening Criteria.
Publication Title
Canadian respiratory journal : journal of the Canadian Thoracic Society
Document Type
Article
Publication Date
1-1-2020
Abstract
The National Comprehensive Cancer Network expanded their lung cancer screening (LCS) criteria to comprise one additional clinical risk factor, including chronic obstructive pulmonary disease (COPD). The electronic medical record (EMR) is a source of clinical information that could identify high-risk populations for LCS, including a diagnosis of COPD; however, an unsubstantiated COPD diagnosis in the EMR may lead to inappropriate LCS referrals. We aimed to detect the prevalence of unsubstantiated COPD diagnosis in the EMR for LCS referrals, to determine the efficacy of utilizing the EMR as an accurate population-based eligibility screening "trigger" using modified clinical criteria. We performed a multicenter review of all individuals referred to three LCS programs from 2012 to 2015. Each individual's EMR was searched for COPD diagnostic terms and the presence of a diagnostic pulmonary functionality test (PFT). An unsubstantiated COPD diagnosis was defined by an individual's EMR containing a COPD term with no PFTs present, or the presence of PFTs without evidence of obstruction. A total of 2834 referred individuals were identified, of which 30% (840/2834) had a COPD term present in their EMR. Of these, 68% (571/840) were considered unsubstantiated diagnoses: 86% (489/571) due to absent PFTs and 14% (82/571) due to PFTs demonstrating no evidence of postbronchodilation obstruction. A large proportion of individuals referred for LCS may have an unsubstantiated COPD diagnosis within their EMR. Thus, utilizing the EMR as a population-based eligibility screening tool, employing expanded criteria, may lead to individuals being referred, potentially, inappropriately for LCS.
Clinical Institute
Cancer
Specialty
Swedish Thoracic Surgery
Specialty
Oncology
Specialty
Health Information Technology
DOI
10.1155/2020/7142568