EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites.
Objective: The Recruitment Innovation Center (RIC), partnering with the Trial Innovation Network and institutions in the National Institutes of Health-sponsored Clinical and Translational Science Awards (CTSA) Program, aimed to develop a service line to retrieve study population estimates from elect...
| Publicado en: | Journal of the American Medical Informatics Association Vol. 29; no. 4; pp. 652 - 660 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Oxford University Press / USA
Apr2022
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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=155812598&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 155812598 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10675027 FZ9 jtl: Journal of the American Medical Informatics Association issn: 10675027 maglogo: N pubinfo: dt: Apr2022 vid: 29 iid: 4 pid: 622 pub: Oxford University Press / USA artinfo: ui: 155812598 155812598 NLM34850917 155812598 10.1093/jamia/ocab265 NLM34850917 155812598 ppf: 652 ppct: 8 formats: tig: atl: EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites. aug: au: Nelson, Sarah J Drury, Bethany Hood, Daniel Harper, Jeremy Bernard, Tiffany Weng, Chunhua Kennedy, Nan LaSalle, Bernie Gouripeddi, Ramkiran Wilkins, Consuelo H Harris, Paul affil: Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center , Nashville, Tennessee, USA sug: subj: National Institutes of Health (U.S.) Research Personnel Prospective Studies Algorithms Study Design Human United States Comparative Studies Multicenter Studies Evaluation Research Validation Studies Clinical Assessment Tools Scales ab: Objective: The Recruitment Innovation Center (RIC), partnering with the Trial Innovation Network and institutions in the National Institutes of Health-sponsored Clinical and Translational Science Awards (CTSA) Program, aimed to develop a service line to retrieve study population estimates from electronic health record (EHR) systems for use in selecting enrollment sites for multicenter clinical trials. Our goal was to create and field-test a low burden, low tech, and high-yield method.Materials and Methods: In building this service line, the RIC strove to complement, rather than replace, CTSA hubs' existing cohort assessment tools. For each new EHR cohort request, we work with the investigator to develop a computable phenotype algorithm that targets the desired population. CTSA hubs run the phenotype query and return results using a standardized survey. We provide a comprehensive report to the investigator to assist in study site selection.Results: From 2017 to 2020, the RIC developed and socialized 36 phenotype-dependent cohort requests on behalf of investigators. The average response rate to these requests was 73%.Discussion: Achieving enrollment goals in a multicenter clinical trial requires that researchers identify study sites that will provide sufficient enrollment. The fast and flexible method the RIC has developed, with CTSA feedback, allows hubs to query their EHR using a generalizable, vetted phenotype algorithm to produce reliable counts of potentially eligible study participants.Conclusion: The RIC's EHR cohort assessment process for evaluating sites for multicenter trials has been shown to be efficient and helpful. The model may be replicated for use by other programs. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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