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The Effect of Physicians' Explanations on Patients' Treatment Preferences

Medical Decision MakingPublished 1 August 1994
Dennis J. Mazur, David H. Hickam
Citations53
SJR quartileQ1
SJR score1.48
SNIP1.35

TL;DR

The patients' treatment preferences for long-term vs short-term survival benefits were influenced by the amounts of verbal explanation provided to them about five-year survival graphs summarizing treatment results, which appeared to minimize the importance of medium-range data when those data were not specifically pointed out to them.

Abstract

OBJECTIVE: To evaluate the influence of physicians' explanations on patients' choices. SETTING: A university-based Department of Veterans Affairs Medical Center. PARTICIPANTS: 136 patients seen in a continuity-care general medicine clinic. MEASUREMENTS AND RESULTS: Patients were randomized to two groups [Limited Explanation (LE) and Extensive Explanation (EE)] and asked to choose between two alternative treatments (differing in short-term vs long-term survival benefits) for an unidentified medical condition, based on the information given in the explanations. LE consisted of a brief orientation to graphs summarizing the treatment results, while EE consisted of a detailed verbal description of the graphs. Significantly (p < 0.001) more patients receiving EE changed their preferences across the three pairs of five-year survival curves, compared with patients receiving LE. Of the patients receiving EE, 57% reported either medium-term (year 0-to-intercept or intercept-to-year 5) data or the average life expectancy for the five-year period contained in the curves (ALE-5) as most influencing their decision making; whereas 78% of patients receiving LE reported only endpoint (year 0 or year 5) data as most influencing their preferences. CONCLUSIONS: The patients' treatment preferences for long-term vs short-term survival benefits were influenced by the amounts of verbal explanation provided to them about five-year survival graphs summarizing treatment results. The patients appeared to minimize the importance of medium-range data when those data were not specifically pointed out to them.

Keywords

Decision SciencesMedicineHealth Professions