Determining the Impact of Informed Choice

Author:

McCaffery Kirsten J.12,Turner Robin12,Macaskill Petra12,Walter Stephen D.12,Chan Siew Foong12,Irwig Les12

Affiliation:

1. Screening and Test Evaluation Program, School of Public Health, University of Sydney, Sydney, Australia (KJM, RT, PM, SFC, LI)

2. Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada (SDW)

Abstract

Background. The Rucker 2-stage randomized trial (RCT) design and method allows treatment, preference, and selection effects to be estimated separately in clinical trials. Objective. To understand the effect of patient choice on patient outcomes, the authors applied the Rucker design and analysis method. Design. They used data from a trial of management strategies for women with atypical cells of undetermined significance (ASCUS) detected at routine cervical screening, in which informed choice using a decision aid was compared to no choice. Setting. Women’s health clinics across Australia. Patients. Women aged 18 to 70 years (n = 314) with ASCUS. Intervention. Women were randomized to either an informed choice of human papillomavirus (HPV) triage testing or repeat Pap testing or to no choice with random allocation to management by either option. Measurements. Health-related quality of life (SF36) and satisfaction were measured over the course of management and up to 1 year after triage. Results. Using the Rucker analysis, patients who received their choice had higher quality of life scores than those who did not choose (SF36 MCS, 6% higher, 6.0; 95% confidence interval: −0.6 to 12.9; P = 0.07; effect size 0.61 [moderate]). In contrast, the traditional RCT analysis suggested there was little difference in quality of life between the choice and no-choice trial arms. Limitations. The Rucker method assumes that the declared preferences for treatment in the choice arm are representative of the preferences that would have been observed in the no-choice arms if choice was available. Conclusions. The Rucker method should be used to estimate treatment, preference, and selection effects in randomized trials, as it adds to our understanding of the effect of choice on patient outcomes.

Publisher

SAGE Publications

Subject

Health Policy

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