Electronic Health Record Use to Classify Patients with Newly Diagnosed versus Preexisting Type 2 Diabetes: Infrastructure for Comparative Effectiveness Research and Population Health Management.
Use of electronic health record (EHR) content for comparative effectiveness research (CER) and population health management requires significant data configuration. A retrospective cohort study was conducted using patients with diabetes followed longitudinally ( N = 36,353) in the EHR deployed at ou...
| Publicado en: | Population Health Management Vol. 15; no. 1; pp. 3 - 12 |
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| Autores principales: | , , , , , , |
| Formato: | algorithm research tables/charts Journal Article |
| Publicado: |
Mary Ann Liebert, Inc.
Feb2012
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104515341&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104515341 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 19427891 8765 jtl: Population Health Management issn: 19427891 maglogo: N pubinfo: dt: Feb2012 vid: 15 iid: 1 pid: 1365 pub: Mary Ann Liebert, Inc. place: New Rochelle, New York artinfo: ui: 104515341 71528629 71528629 10.1089/pop.2010.0084 104515341 ppf: 3 ppct: 9 formats: tig: atl: Electronic Health Record Use to Classify Patients with Newly Diagnosed versus Preexisting Type 2 Diabetes: Infrastructure for Comparative Effectiveness Research and Population Health Management. aug: au: Kudyakov, Rustam Bowen, James Ewen, Edward West, Suzanne L. Daoud, Yahya Fleming, Neil Masica, Andrew affil: , Dallas, Texas. sug: subj: Electronic Health Records Diabetes Mellitus, Type 2 Diagnosis Diabetes Mellitus, Type 2 Classification Human Comparative Studies Retrospective Design Prospective Studies Record Review Descriptive Statistics Predictive Value of Tests Disease Management Texas Delaware Algorithms Male Female Adult Middle Age Aged Funding Source Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Male Female ab: Use of electronic health record (EHR) content for comparative effectiveness research (CER) and population health management requires significant data configuration. A retrospective cohort study was conducted using patients with diabetes followed longitudinally ( N = 36,353) in the EHR deployed at outpatient practice networks of 2 health care systems. A data extraction and classification algorithm targeting identification of patients with a new diagnosis of type 2 diabetes mellitus (T2DM) was applied, with the main criterion being a minimum 30-day window between the first visit documented in the EHR and the entry of T2DM on the EHR problem list. Chart reviews ( N = 144) validated the performance of refining this EHR classification algorithm with external administrative data. Extraction using EHR data alone designated 3205 patients as newly diagnosed with T2DM with classification accuracy of 70.1%. Use of external administrative data on that preselected population improved classification accuracy of cases identified as new T2DM diagnosis (positive predictive value was 91.9% with that step). Laboratory and medication data did not help case classification. The final cohort using this 2-stage classification process comprised 1972 patients with a new diagnosis of T2DM. Data use from current EHR systems for CER and disease management mandates substantial tailoring. Quality between EHR clinical data generated in daily care and that required for population health research varies. As evidenced by this process for classification of newly diagnosed T2DM cases, validation of EHR data with external sources can be a valuable step. ( Population Health Management 2012;15:3-11) pubtype: Academic Journal doctype: algorithm research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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