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Development and validation of an electronic phenotyping algorithm for chronic kidney disease.
Nadkarni GN, Gottesman O, Linneman JG, Chase H, Berg RL, Farouk S, Nadukuru R, Lotay V, Ellis S, Hripcsak G, Peissig P, Weng C, Bottinger EP. Nadkarni GN, et al. AMIA Annu Symp Proc. 2014 Nov 14;2014:907-16. eCollection 2014. AMIA Annu Symp Proc. 2014. PMID: 25954398 Free PMC article.
Twenty-six million Americans are estimated to have chronic kidney disease (CKD) with increased risk for cardiovascular disease and end stage renal disease. ...As members of eMERGE (electronic medical records and genomics) Network, …
Twenty-six million Americans are estimated to have chronic kidney disease (CKD) with increased risk for cardiovascular …
A Novel Chronic Kidney Disease Phenotyping Algorithm Using Combined Electronic Health Record and Claims Data.
Mansour O, Paik JM, Wyss R, Mastrorilli JM, Bessette LG, Lu Z, Tsacogianis T, Lin KJ. Mansour O, et al. Clin Epidemiol. 2023 Mar 8;15:299-307. doi: 10.2147/CLEP.S397020. eCollection 2023. Clin Epidemiol. 2023. PMID: 36919110 Free PMC article.
PURPOSE: Because chronic kidney disease (CKD) is often under-coded as a diagnosis in claims data, we aimed to develop claims-based prediction models for CKD phenotypes determined by laboratory results in electronic health records (EHRs). …
PURPOSE: Because chronic kidney disease (CKD) is often under-coded as a diagnosis in claims data, we aimed to develo
PheValuator: Development and evaluation of a phenotype algorithm evaluator.
Swerdel JN, Hripcsak G, Ryan PB. Swerdel JN, et al. J Biomed Inform. 2019 Sep;97:103258. doi: 10.1016/j.jbi.2019.103258. Epub 2019 Jul 29. J Biomed Inform. 2019. PMID: 31369862 Free PMC article.
BACKGROUND: The primary approach for defining disease in observational healthcare databases is to construct phenotype algorithms (PAs), rule-based heuristics predicated on the presence, absence, and temporal logic of clinical observations. ...We used the pred …
BACKGROUND: The primary approach for defining disease in observational healthcare databases is to construct phenotype algor
Development and validation of algorithms to identify patients with chronic kidney disease and related chronic diseases across the Northern Territory, Australia.
Chen W, Abeyaratne A, Gorham G, George P, Karepalli V, Tran D, Brock C, Cass A. Chen W, et al. BMC Nephrol. 2022 Sep 23;23(1):320. doi: 10.1186/s12882-022-02947-9. BMC Nephrol. 2022. PMID: 36151531 Free PMC article.
The Territory Kidney Care project developed algorithms to identify individuals with chronic kidney disease (CKD) and several commonly comorbid chronic diseases. ...CONCLUSIONS: We developed and validated algorithms
The Territory Kidney Care project developed algorithms to identify individuals with chronic kidney dis
Electronic Health Record Phenotypes for Identifying Patients with Late-Stage Disease: a Method for Research and Clinical Application.
Ernecoff NC, Wessell KL, Hanson LC, Lee AM, Shea CM, Dusetzina SB, Weinberger M, Bennett AV. Ernecoff NC, et al. J Gen Intern Med. 2019 Dec;34(12):2818-2823. doi: 10.1007/s11606-019-05219-9. Epub 2019 Aug 8. J Gen Intern Med. 2019. PMID: 31396813 Free PMC article.
OBJECTIVE: To develop EHR phenotypes to identify decedents with stage 4 solid-tumor cancer or stage 4-5 chronic kidney disease (CKD). DESIGN: We developed two EHR phenotypes. Each phenotype included International Classificat …
OBJECTIVE: To develop EHR phenotypes to identify decedents with stage 4 solid-tumor cancer or stage 4-5 chronic kidn