EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites

Abstract

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.

Leveraging the Expertise of the CTSA Program to Increase the Impact and Efficiency of Clinical Trials

“…The TIN created a successful distributed process for EHR site-based cohort estimation based on sharing phenotype algorithms that could be run on any data warehousing platform. 36 While the large number of and their nationwide distribution has been a strength for the TIN, only a finite set of sites are interested in or needed for each trial. Because the PI maintains final site selection authority, not all interested sites will be selected to participate in every trial.…”

Selecting EHR-driven recruitment strategies: An evidence-based decision guide

“…At their core, all EHR-driven recruitment strategies require a computable phenotype [9,11]. The phenotype may be general ("all patients ages 2-18 years") or specific ("4-year-old females with an encounter diagnosis ICD-10-CM code F84.0 from clinic X in the past 30 days") and should be well specified.…”

“…A basic feasibility assessment [9] can often confirm whether a recruitment site has an adequate patient population to meet their recruitment goals. The rate at which an eligible patient population presents in the healthcare setting can be a strong differentiator between clinician directed point of care alerts, researcher directed alerts, other EHR based methods, or using non-EHR recruitment methods.…”

“…Notably, the ERCR is part of a larger suite of services supporting trial recruitment, including the EHR-based Cohort Assessment service line for study site selection (see Fig. 1 for organization chart) [9]. The ERCR includes domain experts and project managers to support consultations.…”

What we wish every investigator knew: Top 4 recruitment and retention recommendations from the Recruitment Innovation Center

“…Investigators should evaluate the availability of the target population to be recruited at each site. Electronic health record (EHR) data can be analyzed to determine whether an appropriate volume of patients with the specified health condition exists at a potential site [13]. Other data sources can be leveraged to assist in site identification and selection, including public health datasets and population-level data.…”