TY - JOUR
T1 - Electronic medical record-based cohort selection and direct-to-patient, targeted recruitment
T2 - Early efficacy and lessons learned
AU - Miller, Hailey N.
AU - Gleason, Kelly T.
AU - Juraschek, Stephen P.
AU - Plante, Timothy B.
AU - Lewis-Land, Cassie
AU - Woods, Bonnie
AU - Appel, Lawrence J.
AU - Ford, Daniel E.
AU - Dennison Himmelfarb, Cheryl R.
N1 - Publisher Copyright:
© 2019 The Author(s).
PY - 2019/7/22
Y1 - 2019/7/22
N2 - Objective: The study sought to characterize institution-wide participation in secure messaging (SM) at a large academic health network, describe our experience with electronic medical record (EMR)-based cohort selection, and discuss the potential roles of SM for research recruitment. Materials and Methods: Study teams defined eligibility criteria to create a computable phenotype, structured EMR data, to identify and recruit participants. Patients with SM accounts matching this phenotype received recruitment messages. We compared demographic characteristics across SM users and the overall health system. We also tabulated SM activation and use, characteristics of individual studies, and efficacy of the recruitment methods. Results: Of the 1 308 820 patients in the health network, 40% had active SM accounts. SM users had a greater proportion of white and non-Hispanic patients than nonactive SM users id. Among the studies included (n = 13), 77% recruited participants with a specific disease or condition. All studies used demographic criteria for their phenotype, while 46% (n = 6) used demographic, disease, and healthcare utilization criteria. The average SM response rate was 2.9%, with higher rates among condition-specific (3.4%) vs general health (1.4%) studies. Those studies with a more inclusive comprehensive phenotype had a higher response rate. Discussion: Target population and EMR queries (computable phenotypes) affect recruitment efficacy and should be considered when designing an EMR-based recruitment strategy. Conclusions: SM guided by EMR-based cohort selection is a promising approach to identify and enroll research participants. Efforts to increase the number of active SM users and response rate should be implemented to enhance the effectiveness of this recruitment strategy.
AB - Objective: The study sought to characterize institution-wide participation in secure messaging (SM) at a large academic health network, describe our experience with electronic medical record (EMR)-based cohort selection, and discuss the potential roles of SM for research recruitment. Materials and Methods: Study teams defined eligibility criteria to create a computable phenotype, structured EMR data, to identify and recruit participants. Patients with SM accounts matching this phenotype received recruitment messages. We compared demographic characteristics across SM users and the overall health system. We also tabulated SM activation and use, characteristics of individual studies, and efficacy of the recruitment methods. Results: Of the 1 308 820 patients in the health network, 40% had active SM accounts. SM users had a greater proportion of white and non-Hispanic patients than nonactive SM users id. Among the studies included (n = 13), 77% recruited participants with a specific disease or condition. All studies used demographic criteria for their phenotype, while 46% (n = 6) used demographic, disease, and healthcare utilization criteria. The average SM response rate was 2.9%, with higher rates among condition-specific (3.4%) vs general health (1.4%) studies. Those studies with a more inclusive comprehensive phenotype had a higher response rate. Discussion: Target population and EMR queries (computable phenotypes) affect recruitment efficacy and should be considered when designing an EMR-based recruitment strategy. Conclusions: SM guided by EMR-based cohort selection is a promising approach to identify and enroll research participants. Efforts to increase the number of active SM users and response rate should be implemented to enhance the effectiveness of this recruitment strategy.
KW - cohort selection
KW - direct messaging
KW - electronic medical records
KW - patient portal messaging
KW - research recruitment
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U2 - 10.1093/jamia/ocz168
DO - 10.1093/jamia/ocz168
M3 - Article
C2 - 31553434
AN - SCOPUS:85073183039
SN - 1067-5027
VL - 26
SP - 1209
EP - 1217
JO - Journal of the American Medical Informatics Association
JF - Journal of the American Medical Informatics Association
IS - 11
ER -