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- Title
Combining billing codes, clinical notes, and medications from electronic health records provides superior phenotyping performance.
- Authors
Wei-Qi Wei; Teixeira, Pedro L.; Huan Mo; Cronin, Robert M.; Warner, Jeremy L.; Denny, Joshua C.; Wei, Wei-Qi; Mo, Huan
- Abstract
<bold>Objective: </bold>To evaluate the phenotyping performance of three major electronic health record (EHR) components: International Classification of Disease (ICD) diagnosis codes, primary notes, and specific medications.<bold>Materials and Methods: </bold>We conducted the evaluation using de-identified Vanderbilt EHR data. We preselected ten diseases: atrial fibrillation, Alzheimer's disease, breast cancer, gout, human immunodeficiency virus infection, multiple sclerosis, Parkinson's disease, rheumatoid arthritis, and types 1 and 2 diabetes mellitus. For each disease, patients were classified into seven categories based on the presence of evidence in diagnosis codes, primary notes, and specific medications. Twenty-five patients per disease category (a total number of 175 patients for each disease, 1750 patients for all ten diseases) were randomly selected for manual chart review. Review results were used to estimate the positive predictive value (PPV), sensitivity, andF-score for each EHR component alone and in combination.<bold>Results: </bold>The PPVs of single components were inconsistent and inadequate for accurately phenotyping (0.06-0.71). Using two or more ICD codes improved the average PPV to 0.84. We observed a more stable and higher accuracy when using at least two components (mean ± standard deviation: 0.91 ± 0.08). Primary notes offered the best sensitivity (0.77). The sensitivity of ICD codes was 0.67. Again, two or more components provided a reasonably high and stable sensitivity (0.59 ± 0.16). Overall, the best performance (Fscore: 0.70 ± 0.12) was achieved by using two or more components. Although the overall performance of using ICD codes (0.67 ± 0.14) was only slightly lower than using two or more components, its PPV (0.71 ± 0.13) is substantially worse (0.91 ± 0.08).<bold>Conclusion: </bold>Multiple EHR components provide a more consistent and higher performance than a single one for the selected phenotypes. We suggest considering multiple EHR components for future phenotyping design in order to obtain an ideal result.
- Subjects
MEDICAL coding; ELECTRONIC health records; INTERNATIONAL Statistical Classification of Diseases &; Related Health Problems; ALZHEIMER'S disease diagnosis; PARKINSON'S disease diagnosis; ALGORITHMS; COMPARATIVE studies; DIAGNOSIS; RESEARCH methodology; MEDICAL cooperation; MEDICAL records; NOSOLOGY; RESEARCH; RESEARCH funding; PHENOTYPES; EVALUATION research; PREDICTIVE tests
- Publication
Journal of the American Medical Informatics Association, 2016, Vol 23, Issue e1, pe20
- ISSN
1067-5027
- Publication type
journal article
- DOI
10.1093/jamia/ocv130