Development of an Algorithm to Identify Cases of Nonalcoholic Steatohepatitis Cirrhosis in the Electronic Health Record
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ORIGINAL ARTICLE
Development of an Algorithm to Identify Cases of Nonalcoholic Steatohepatitis Cirrhosis in the Electronic Health Record Christopher J. Danford1 · Jennifer Y. Lee2 · Ian A. Strohbehn3 · Kathleen E. Corey3 · Michelle Lai1 Received: 11 October 2019 / Accepted: 3 June 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Background and Aims Current genetic research of nonalcoholic steatohepatitis (NASH) cirrhosis is limited by our ability to accurately identify cases on a large scale. Our objective was to develop and validate an electronic health record (EHR) algorithm to accurately identify cases of NASH cirrhosis in the EHR. Methods We used Clinical Query 2, a search tool at Beth Israel Deaconess Medical Center, to create a pool of potential NASH cirrhosis cases (n = 5415). We created a training set of 300 randomly selected patients for chart review to confirm cases of NASH cirrhosis. Test characteristics of different algorithms, consisting of diagnosis codes, laboratory values, anthropomorphic measurements, and medication records, were calculated. The algorithms with the highest positive predictive value (PPV) and the highest F score with a PPV ≥ 80% were selected for internal validation using a separate random set of 100 patients from the potential NASH cirrhosis pool. These were then externally validated in another random set of 100 individuals using the research patient data registry tool at Massachusetts General Hospital. Results The algorithm with the highest PPV of 100% on internal validation and 92% on external validation consisted of ≥ 3 counts of “cirrhosis, no mention of alcohol” (571.5, K74.6) and ≥ 3 counts of “nonalcoholic fatty liver” (571.8–571.9, K75.81, K76.0) codes in the absence of any diagnosis codes for other common causes of chronic liver disease. Conclusions We developed and validated an EHR algorithm using diagnosis codes that accurately identifies patients with NASH cirrhosis. Keywords Electronic medical record · NASH · NAFLD · Genetics
Introduction Since the completion of the Human Genome Project in 2003, the field of genetics has rapidly expanded with the identification of over 10,000 single nucleotide Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10620-020-06388-y) contains supplementary material, which is available to authorized users. * Christopher J. Danford [email protected] Jennifer Y. Lee [email protected] Ian A. Strohbehn [email protected] Kathleen E. Corey [email protected]
polymorphisms (SNPs) associated with over 250 different phenotypes [1]. While initial discovery was limited by genotyping technology, current discovery is more limited by lack of accurate phenotypic descriptors to link with genetic data [2]. Traditionally, genetic studies have occurred within purpose-built, well-phenotyped cohorts such as the Framingham Heart Study [3]. However, this approach is limited by small sample size, high cost, and 1
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