OBJECTIVE: This article presents and describes our methods in developing a novel strategy for recruitment of underrepresented, community-based participants, for pragmatic research studies leveraging routinely collected electronic health record (EHR) data. METHODS: We designed a new approach for recruiting eligible patients from the community, while also leveraging affiliated health systems to extract clinical data for community participants. The strategy involves methods for data collection, linkage, and tracking. In this workflow, potential participants are identified in the community and surveyed regarding eligibility. These data are then encrypted and deidentified via a hashing algorithm for linkage of the community participant back to a record at a clinical site. The linkage allows for eligibility verification and automated follow-up. Longitudinal data are collected by querying the EHR data and surveying the community participant directly. We discuss this strategy within the context of two national research projects, a clinical trial and an observational cohort study. CONCLUSION: The community-based recruitment strategy is a novel, low-touch, clinical trial enrollment method to engage a diverse set of participants. Direct outreach to community participants, while utilizing EHR data for clinical information and follow-up, allows for efficient recruitment and follow-up strategies. This new strategy for recruitment links data reported from community participants to clinical data in the EHR and allows for eligibility verification and automated follow-up. The workflow has the potential to improve recruitment efficiency and engage traditionally underrepresented individuals in research. Schattauer GmbH Stuttgart.
OBJECTIVE: This article presents and describes our methods in developing a novel strategy for recruitment of underrepresented, community-based participants, for pragmatic research studies leveraging routinely collected electronic health record (EHR) data. METHODS: We designed a new approach for recruiting eligible patients from the community, while also leveraging affiliated health systems to extract clinical data for community participants. The strategy involves methods for data collection, linkage, and tracking. In this workflow, potential participants are identified in the community and surveyed regarding eligibility. These data are then encrypted and deidentified via a hashing algorithm for linkage of the community participant back to a record at a clinical site. The linkage allows for eligibility verification and automated follow-up. Longitudinal data are collected by querying the EHR data and surveying the community participant directly. We discuss this strategy within the context of two national research projects, a clinical trial and an observational cohort study. CONCLUSION: The community-based recruitment strategy is a novel, low-touch, clinical trial enrollment method to engage a diverse set of participants. Direct outreach to community participants, while utilizing EHR data for clinical information and follow-up, allows for efficient recruitment and follow-up strategies. This new strategy for recruitment links data reported from community participants to clinical data in the EHR and allows for eligibility verification and automated follow-up. The workflow has the potential to improve recruitment efficiency and engage traditionally underrepresented individuals in research. Schattauer GmbH Stuttgart.
Authors: Rachel L Richesson; Beverly B Green; Reesa Laws; Jon Puro; Michael G Kahn; Alan Bauck; Michelle Smerek; Erik G Van Eaton; Meredith Zozus; W Ed Hammond; Kari A Stephens; Greg E Simon Journal: J Am Med Inform Assoc Date: 2017-09-01 Impact factor: 4.497
Authors: Robert J Mentz; Adrian F Hernandez; Lisa G Berdan; Tyrus Rorick; Emily C O'Brien; Jenny C Ibarra; Lesley H Curtis; Eric D Peterson Journal: Circulation Date: 2016-03-01 Impact factor: 29.690
Authors: K Allen Greiner; Daniela B Friedman; Swann Arp Adams; Clement K Gwede; Paula Cupertino; Kimberly K Engelman; Cathy D Meade; James R Hébert Journal: Cancer Epidemiol Biomarkers Prev Date: 2014-03 Impact factor: 4.254
Authors: Rachel E Sherman; Steven A Anderson; Gerald J Dal Pan; Gerry W Gray; Thomas Gross; Nina L Hunter; Lisa LaVange; Danica Marinac-Dabic; Peter W Marks; Melissa A Robb; Jeffrey Shuren; Robert Temple; Janet Woodcock; Lilly Q Yue; Robert M Califf Journal: N Engl J Med Date: 2016-12-08 Impact factor: 91.245
Authors: William R Carpenter; Seth Tyree; Yang Wu; Anne-Marie Meyer; Lisa DiMartino; Leah Zullig; Paul A Godley Journal: Clin Trials Date: 2012-07-03 Impact factor: 2.486
Authors: Rachael L Fleurence; Lesley H Curtis; Robert M Califf; Richard Platt; Joe V Selby; Jeffrey S Brown Journal: J Am Med Inform Assoc Date: 2014-05-12 Impact factor: 4.497
Authors: Danielle Beck; Aliya Asghar; Tawni Kenworthy-Heinige; Marcus R Johnson; Cyenthia Willis; Alexandra S Kantorowicz; Debra L Condon; Grant D Huang Journal: Contemp Clin Trials Commun Date: 2020-07-18
Authors: Emily Pfaff; Adam Lee; Robert Bradford; Jinhee Pae; Clarence Potter; Paul Blue; Patricia Knoepp; Kristie Thompson; Christianne L Roumie; David Crenshaw; Remy Servis; Darren A DeWalt Journal: J Am Med Inform Assoc Date: 2019-01-01 Impact factor: 4.497
Authors: Kelsey Moriarty; Susan M Wolf; Patricia M Veach; Bonnie LeRoy; Ian M MacFarlane; Heather A Zierhut Journal: Per Med Date: 2020-08-17 Impact factor: 2.512
Authors: Yilin Yoshida; Sonal J Patil; Ross C Brownson; Suzanne A Boren; Min Kim; Rosie Dobson; Kayo Waki; Deborah A Greenwood; Astrid Torbjørnsen; Ambady Ramachandran; Christopher Masi; Vivian A Fonseca; Eduardo J Simoes Journal: J Am Med Inform Assoc Date: 2020-06-01 Impact factor: 4.497