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Identifying Patient Preferences for Communicating Risk Estimates: a Descriptive Pilot Study

Overview
Publisher Biomed Central
Date 2001 Sep 8
PMID 11545684
Citations 50
Authors
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Abstract

Background: Patients increasingly seek more active involvement in health care decisions, but little is known about how to communicate complex risk information to patients. The objective of this study was to elicit patient preferences for the presentation and framing of complex risk information.

Method: To accomplish this, eight focus group discussions and 15 one-on-one interviews were conducted, where women were presented with risk data in a variety of different graphical formats, metrics, and time horizons. Risk data were based on a hypothetical woman's risk for coronary heart disease, hip fracture, and breast cancer, with and without hormone replacement therapy. Participants' preferences were assessed using likert scales, ranking, and abstractions of focus group discussions.

Results: Forty peri- and postmenopausal women were recruited through hospital fliers (n = 25) and a community health fair (n = 15). Mean age was 51 years, 50% were non-Caucasian, and all had completed high school. Bar graphs were preferred by 83% of participants over line graphs, thermometer graphs, 100 representative faces, and survival curves. Lifetime risk estimates were preferred over 10 or 20-year horizons, and absolute risks were preferred over relative risks and number needed to treat.

Conclusion: Although there are many different formats for presenting and framing risk information, simple bar charts depicting absolute lifetime risk were rated and ranked highest overall for patient preferences for format.

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References
1.
Col N, Eckman M, Karas R, Pauker S, Goldberg R, Ross E . Patient-specific decisions about hormone replacement therapy in postmenopausal women. JAMA. 1997; 277(14):1140-7. View

2.
Dupont W, Plummer Jr W . Understanding the relationship between relative and absolute risk. Cancer. 1996; 77(11):2193-9. DOI: 10.1002/(SICI)1097-0142(19960601)77:11<2193::AID-CNCR2>3.0.CO;2-R. View

3.
Bell R, Kravitz R, Wilkes M . Direct-to-consumer prescription drug advertising and the public. J Gen Intern Med. 1999; 14(11):651-7. PMC: 1496757. DOI: 10.1046/j.1525-1497.1999.01049.x. View

4.
Barrett-Connor E . Hormone replacement therapy. BMJ. 1998; 317(7156):457-61. PMC: 1113713. DOI: 10.1136/bmj.317.7156.457. View

5.
McGettigan P, Sly K, OCONNELL D, Hill S, Henry D . The effects of information framing on the practices of physicians. J Gen Intern Med. 1999; 14(10):633-42. PMC: 1496755. DOI: 10.1046/j.1525-1497.1999.09038.x. View