Current Challenges When Using Numbers in Patient Decision Aids: Advanced Concepts

Author:

Trevena Lyndal J.12ORCID,Bonner Carissa12ORCID,Okan Yasmina3ORCID,Peters Ellen4,Gaissmaier Wolfgang5ORCID,Han Paul K. J.67ORCID,Ozanne Elissa8ORCID,Timmermans Danielle9ORCID,Zikmund-Fisher Brian J.10ORCID

Affiliation:

1. Faculty of Medicine and Health, School of Public Health, The University of Sydney, Sydney, NSW, Australia

2. Ask Share Know NHMRC Centre for Research Excellence, The University of Sydney, Australia

3. Centre for Decision Research, University of Leeds, Leeds, UK

4. University of Oregon, Eugene, OR, USA

5. University of Konstanz, Konstanz, Baden-Wurttemberg, Germany

6. Center for Outcomes Research and Evaluation, Maine Medical Center Research Institute, Portland, ME, USA

7. School of Medicine, Tufts University, Medford, MA, USA

8. University of Utah, Salt Lake City, UT, USA

9. Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, North Holland, The Netherlands

10. University of Michigan, Ann Arbor, MI, USA

Abstract

Background Decision aid developers have to convey complex task-specific numeric information in a way that minimizes bias and promotes understanding of the options available within a particular decision. Whereas our companion paper summarizes fundamental issues, this article focuses on more complex, task-specific aspects of presenting numeric information in patient decision aids. Methods As part of the International Patient Decision Aids Standards third evidence update, we gathered an expert panel of 9 international experts who revised and expanded the topics covered in the 2013 review working in groups of 2 to 3 to update the evidence, based on their expertise and targeted searches of the literature. The full panel then reviewed and provided additional revisions, reaching consensus on the final version. Results Five of the 10 topics addressed more complex task-specific issues. We found strong evidence for using independent event rates and/or incremental absolute risk differences for the effect size of test and screening outcomes. Simple visual formats can help to reduce common judgment biases and enhance comprehension but can be misleading if not well designed. Graph literacy can moderate the effectiveness of visual formats and hence should be considered in tool design. There is less evidence supporting the inclusion of personalized and interactive risk estimates. Discussion More complex numeric information. such as the size of the benefits and harms for decision options, can be better understood by using incremental absolute risk differences alongside well-designed visual formats that consider the graph literacy of the intended audience. More research is needed into when and how to use personalized and/or interactive risk estimates because their complexity and accessibility may affect their feasibility in clinical practice.

Publisher

SAGE Publications

Subject

Health Policy

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3