Developing electronic health record algorithms that accurately identify patients with juvenile idiopathic arthritis.
• To the best of our knowledge, this is the first study to create an EHR-based JIA cohort using ICD codes, keywords, and exclusion criteria. • Three studied algorithms achieved PPVs of 97%, each with different algorithm criteria, allowing for users to select an algorithm to best fit their research n...
| Published in: | Seminars in Arthritis & Rheumatism Vol. 59 |
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| Main Authors: | , , , |
| Format: | research Journal Article |
| Published: |
W B Saunders
Apr2023
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=162178548&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 162178548 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00490172 4GQ jtl: Seminars in Arthritis & Rheumatism issn: 00490172 maglogo: N pubinfo: dt: Apr2023 vid: 59 pid: 1351 pub: W B Saunders place: Philadelphia, Pennsylvania artinfo: ui: 162178548 162178548 162178548 10.1016/j.semarthrit.2023.152167 162178548 ppct: 1 formats: tig: atl: Developing electronic health record algorithms that accurately identify patients with juvenile idiopathic arthritis. aug: au: Peterson, Hannah M. Vela, Kelsi L. Barnado, April Patrick, Anna E. affil: Lipscomb University College of Pharmacy and Health Sciences, Nashville, TN, United States sug: subj: Arthritis, Juvenile Rheumatoid Diagnosis Algorithms Evaluation Electronic Health Records Diagnosis, Computer Assisted Decision Support Techniques Predictive Value of Tests Human Random Sample Sensitivity and Specificity International Classification of Diseases Prospective Studies Descriptive Statistics Validation Studies ab: • To the best of our knowledge, this is the first study to create an EHR-based JIA cohort using ICD codes, keywords, and exclusion criteria. • Three studied algorithms achieved PPVs of 97%, each with different algorithm criteria, allowing for users to select an algorithm to best fit their research needs. • This methodology allows for an efficient, cost-effective way to assemble a cohort of JIA patients at a single institution or at multiple institutions. The objective of this study was to develop an algorithm that accurately identifies juvenile idiopathic arthritis (JIA) patients in the electronic health record (EHR). Algorithms were developed in a de-identified EHR by searching for a priori JIA ICD-9 (International Classification of Diseases, Ninth Revision) and ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) codes and JIA-related keywords. Exclusion criteria were selected to remove other autoimmune diseases. A training set of 200 patients was randomly selected from patients containing ≥1 occurrence of a JIA ICD-9 or ICD-10-CM code. Case status was determined by a rheumatology clinic note documenting a JIA diagnosis before age 20. For each algorithm, positive predictive value (PPV), sensitivity, and F-measure were determined using the training set. We developed 103 algorithms using combinations of ICD codes, keywords, and exclusion criteria. The algorithm requiring 4 or more counts of JIA ICD-9 or ICD-10-CM codes, keywords "enthesitis" and "uveitis", and exclusion of ICD-9 or ICD-10-CM codes for systemic lupus erythematosus, dermatomyositis, polymyositis, and dermatopolymyositis had the highest PPV of 97% in the training set with an F-measure of 87%. There were 1,131 JIA cases returned by this algorithm. We validated the highest performing algorithm in a separate cohort from the training set with a PPV of 92% and an F-measure of 75%. We developed and validated JIA EHR algorithms with ICD-9 and ICD-10-CM codes to accurately identify a JIA cohort. Three algorithms achieved PPVs of 97%, each with different algorithm criteria, allowing for users to select an algorithm to best fit their research needs. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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