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Related Concept Videos

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Related Experiment Video

Updated: Nov 21, 2025

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Electronic Health Record Algorithm Development for Research Subject Recruitment Using Colonoscopy Appointment

Jeanette M Daly1, Kim Parang1, Barcey T Levy1

  • 1From the Department of Family Medicine, Carver College of Medicine, University of Iowa, Iowa City, IA (JMD, KP, BTL); Department of Epidemiology, College of Public Health, University of Iowa, Iowa City, IA (BTL).

Journal of the American Board of Family Medicine : JABFM
|January 16, 2021
PubMed
Summary

An electronic health record (EHR) algorithm effectively identifies patients for fecal immunochemical tests (FITs) research. Iterative refinement and tracking of colonoscopy appointment changes improved recruitment accuracy.

Keywords:
AlgorithmsAppointments and SchedulesColonoscopyColorectal CancerEarly Detection of CancerElectronic Health RecordsInformation TechnologyInternational Classification of DiseasesOccult Blood

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Area of Science:

  • Medical Informatics
  • Clinical Research
  • Health Services Research

Background:

  • Electronic health records (EHRs) are crucial for efficient participant recruitment in medical research.
  • Identifying eligible patients for comparative effectiveness studies can be challenging and time-consuming.

Purpose of the Study:

  • To validate and refine an EHR algorithm for identifying potentially eligible participants for a fecal immunochemical test (FIT) comparative effectiveness study.
  • To optimize participant recruitment for studies utilizing colonoscopy as a standard.

Main Methods:

  • Developed an Epic report-based algorithm to identify patients eligible for screening or surveillance colonoscopies.
  • Employed descriptive statistics and manual verification for algorithm validation.
  • Iteratively refined the algorithm based on criteria including age, appointment details, procedure, and patient type.

Main Results:

  • The algorithm was refined over three iterations.
  • Key criteria included age, appointment dates, procedure type, contact type, date range, encounter departments, ICD-10 codes, and patient type.
  • Tracking cancellations and reschedules improved recruitment potential.

Conclusions:

  • Developing and refining an EHR algorithm significantly reduces time by pre-excluding ineligible individuals.
  • Daily reports incorporating appointment changes maximize recruitment within study timeframes.
  • Iterative algorithm refinement, including tracking of colonoscopy cancellations and reschedules, enhances recruitment accuracy.