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 Ruffin

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)77-86
Number of pages10
JournalAmerican Journal of Preventive Medicine
Volume57
Issue number1
DOIs
StatePublished - Jul 1 2019

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Decision Support Techniques
Early Detection of Cancer
Colorectal Neoplasms
Decision Making
Office Visits
Patient Preference
Self Efficacy
Random Allocation
Documentation
Medical Records
Primary Health Care
Outcome Assessment (Health Care)
Physicians

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Public Health, Environmental and Occupational Health

Cite this

Jimbo, Masahito ; Sen, Ananda ; Plegue, Melissa A. ; Hawley, Sarah ; Kelly-Blake, Karen ; Rapai, Mary ; Zhang, Minling ; Zhang, Yuhong ; Xie, Xiao ; Ruffin, Mack. / Interactivity in a Decision Aid : Findings From a Decision Aid to Technologically Enhance Shared Decision Making RCT. In: American Journal of Preventive Medicine. 2019 ; Vol. 57, No. 1. pp. 77-86.
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title = "Interactivity in a Decision Aid: Findings From a Decision Aid to Technologically Enhance Shared Decision Making RCT",
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.",
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Interactivity in a Decision Aid : Findings From a Decision Aid to Technologically Enhance Shared Decision Making RCT. / Jimbo, Masahito; Sen, Ananda; Plegue, Melissa A.; Hawley, Sarah; Kelly-Blake, Karen; Rapai, Mary; Zhang, Minling; Zhang, Yuhong; Xie, Xiao; Ruffin, Mack.

In: American Journal of Preventive Medicine, Vol. 57, No. 1, 01.07.2019, p. 77-86.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Interactivity in a Decision Aid

T2 - Findings From a Decision Aid to Technologically Enhance Shared Decision Making RCT

AU - Jimbo, Masahito

AU - Sen, Ananda

AU - Plegue, Melissa A.

AU - Hawley, Sarah

AU - Kelly-Blake, Karen

AU - Rapai, Mary

AU - Zhang, Minling

AU - Zhang, Yuhong

AU - Xie, Xiao

AU - Ruffin, Mack

PY - 2019/7/1

Y1 - 2019/7/1

N2 - 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.

AB - 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.

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