Using the analytic hierarchy process to elicit patient preferences: prioritizing multiple outcome measures of antidepressant drug treatment.

BACKGROUND AND OBJECTIVE: In health technology assessment, the evidence obtained from clinical trials regarding multiple clinical outcomes is used to support reimbursement claims. At present, the relevance of these outcome measures for patients is, however, not systematically assessed, and judgments on their relevance may differ among patients and healthcare professionals. The analytic hierarchy process (AHP) is a technique for multi-criteria decision analysis that can be used for preference elicitation. In the present study, we explored the value of using the AHP to prioritize the relevance of outcome measures for major depression by patients, psychiatrists and psychotherapists, and to elicit preferences for alternative healthcare interventions regarding this weighted set of outcome measures. METHODS: Supported by the pairwise comparison technique of the AHP, a patient group and an expert group of psychiatrists and psychotherapists discussed and estimated the priorities of the clinical outcome measures of antidepressant treatment. These outcome measures included remission of depression, response to drug treatment, no relapse, (serious) adverse events, social function, no anxiety, no pain, and cognitive function. Clinical evidence on the outcomes of three antidepressants regarding these outcome measures was derived from a previous benefit assessment by the Institute for Quality and Efficiency in Health Care (IQWiG; Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen). RESULTS: The most important outcome measures according to the patients were, in order of decreasing importance: response to drug treatment, cognitive function, social function, no anxiety, remission, and no relapse. The patients and the experts showed some remarkable differences regarding the relative importance of response (weight patients = 0.37; weight experts = 0.05) and remission (weight patients = 0.09; weight experts = 0.40); however, both experts and patients agreed upon the list of the six most important measures, with experts only adding one additional outcome measure. CONCLUSIONS: The AHP can easily be used to elicit patient preferences and the study has demonstrated differences between patients and experts. The AHP is useful for policy makers in combining multiple clinical outcomes of healthcare interventions grounded in randomized controlled trials in an overall health economic evaluation. This may be particularly relevant in cases where different outcome measures lead to conflicting results about the best alternative to reimburse. Alternatively, AHP may also support researchers in selecting (primary) outcome measures with the highest relevance.

Integrating patients' views into health technology assessment: Analytic hierarchy process (AHP) as a method to elicit patient preferences.

BACKGROUND: Patient involvement is widely acknowledged to be a valuable component in health technology assessment (HTA) and healthcare decision making. However, quantitative approaches to ascertain patients' preferences for treatment endpoints are not yet established. The objective of this study is to introduce the analytic hierarchy process (AHP) as a preference elicitation method in HTA. Based on a systematic literature review on the use of AHP in health care in 2009, the German Institute for Quality and Efficiency in Health Care (IQWiG) initiated an AHP study related to its HTA work in 2010. METHODS: The AHP study included two AHP workshops, one with twelve patients and one with seven healthcare professionals. In these workshops, both patients and professionals rated their preferences with respect to the importance of different endpoints of antidepressant treatment by a pairwise comparison of individual endpoints. These comparisons were performed and evaluated by the AHP method and relative weights were generated for each endpoint. RESULTS: The AHP study indicates that AHP is a well-structured technique whose cognitive demands were well handled by patients and professionals. The two groups rated some of the included endpoints of antidepressant treatment differently. For both groups, however, the same six of the eleven endpoints analyzed accounted for more than 80 percent of the total weight. CONCLUSIONS: AHP can be used in HTA to give a quantitative dimension to patients' preferences for treatment endpoints. Preference elicitation could provide important information at various stages of HTA and challenge opinions on the importance of endpoints.