Interactivity in a Decision Aid: Findings From a Decision Aid to Technologically Enhance Shared Decision Making RCT

Masahito Jimbo; Ananda Sen; Melissa A Plegue; Sarah Hawley; Karen Kelly-Blake; Mary Rapai; Minling Zhang; Yuhong Zhang; Xiao Xie; Mack T Ruffin 4th

doi:10.1016/j.amepre.2019.03.004

Interactivity in a Decision Aid: Findings From a Decision Aid to Technologically Enhance Shared Decision Making RCT

Am J Prev Med. 2019 Jul;57(1):77-86. doi: 10.1016/j.amepre.2019.03.004. Epub 2019 May 23.

Authors

Affiliations

¹ Department of Family Medicine, University of Michigan, Ann Arbor, Michigan.
² Department of Family Medicine, University of Michigan, Ann Arbor, Michigan; Department of Biostatistics, University of Michigan, Ann Arbor, Michigan. Electronic address: anandas@umich.edu.
³ Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan.
⁴ Center for Ethics and Humanities in the Life Sciences and Department of Medicine, Michigan State University, East Lansing, Michigan.
⁵ Kidney Epidemiology and Cost Center, University of Michigan, Ann Arbor, Michigan.
⁶ Department of Family and Community Medicine, Penn State Health Milton S. Hershey Medical Center, Penn State College of Medicine, Hershey, Pennsylvania.

PMID: 31128959
DOI: 10.1016/j.amepre.2019.03.004

Abstract

Introduction: Colorectal cancer screening (CRCS) remains underutilized. Decision aids (DAs) can increase patient knowledge, intent, and CRCS rates compared with "usual care," but whether interactivity further increases CRCS rate remains unknown.

Study design: A two-armed RCT compared the effect of a web-based DA that interactively assessed patient CRC risk and clarified patient preference for specific CRCS test to a web-based DA with the same content but without the interactive tools.

Setting/participants: The study sites were 12 community- and three university-based primary care practices (56 physicians) in southeastern Michigan. Participants were men and women aged 50-75 years not current on CRCS.

Intervention: Random allocation to interactive DA (interactive arm) or non-interactive DA (non-interactive arm).

Main outcome measures: Primary outcome was medical record documentation of CRCS 6 months after the intervention. Secondary outcome was patient decision quality (i.e., knowledge, preference clarification, and intent) measured immediately before and after DA use, and immediately after the office visit. To determine that either DA had a positive effect on CRCS adherence, usual care CRCS rates were determined from the three university-based practices among patients eligible for but not participating in the study.

Results: Data were collected between 2012 and 2014; analysis began in 2015. At 6 months, CRCS rate was 36.1% (95% CI=30.5%, 42.2%) in the interactive arm (n=284) and 40.5% (95% CI=34.7%, 46.6%) in the non-interactive arm (n=286, p=0.29). Usual care CRCS rate (n=440) was 18.6% (95% CI=15.2%, 22.7%), significantly lower than both arms (p<0.001). Knowledge, attitude, self-efficacy, test preference, and intent increased significantly within each arm versus baseline, but the rate was not significantly different between the two arms.

Conclusions: The interactive DA did not improve the outcome compared to the non-interactive DA. This suggests that the resources needed to create and maintain the interactive components are not justifiable.

Trial registration: This study is registered at www.clinicaltrials.gov NCT01514786.

Publication types

Randomized Controlled Trial
Research Support, N.I.H., Extramural

MeSH terms

Aged
Colorectal Neoplasms / diagnosis*
Decision Making, Shared*
Decision Support Techniques*
Early Detection of Cancer*
Female
Health Knowledge, Attitudes, Practice*
Humans
Male
Michigan
Middle Aged
Patient Preference / psychology
Primary Health Care

Associated data

ClinicalTrials.gov/NCT01514786

Grants and funding

R01 CA152413/CA/NCI NIH HHS/United States