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

M.J.M. Hummel, F. Volz, Jeanette Gabrielle van Manen, M. Danner, C.-M. Dintsios, Maarten Joost IJzerman, A. Gerber

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    Abstract

    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 fu¨r Qualita¨ t 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.
    Original languageEnglish
    Pages (from-to)1-13
    Number of pages13
    JournalPatient : patient centered outcomes research
    Volume5
    Issue number4
    Publication statusPublished - 2012

    Fingerprint

    Patient Preference
    Antidepressive Agents
    Outcome Assessment (Health Care)
    Therapeutics
    Delivery of Health Care
    Weights and Measures
    Psychotherapy
    Psychiatry
    Anxiety
    Depression
    Recurrence
    Biomedical Technology Assessment
    Administrative Personnel
    Pharmaceutical Preparations
    Cognition
    Cost-Benefit Analysis
    Randomized Controlled Trials
    Research Personnel
    Clinical Trials
    Pain

    Keywords

    • IR-82232
    • METIS-288990

    Cite this

    @article{0c2312c840eb471faba75fa46b2c8618,
    title = "Using the analytic hierarchy process to elicit patient preferences: prioritizing multiple outcome measures of antidepressant drug treatment",
    abstract = "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 fu¨r Qualita¨ t 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.",
    keywords = "IR-82232, METIS-288990",
    author = "M.J.M. Hummel and F. Volz and {van Manen}, {Jeanette Gabrielle} and M. Danner and C.-M. Dintsios and IJzerman, {Maarten Joost} and A. Gerber",
    year = "2012",
    language = "English",
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    Using the analytic hierarchy process to elicit patient preferences: prioritizing multiple outcome measures of antidepressant drug treatment. / Hummel, M.J.M.; Volz, F.; van Manen, Jeanette Gabrielle; Danner, M.; Dintsios, C.-M.; IJzerman, Maarten Joost; Gerber, A.

    In: Patient : patient centered outcomes research, Vol. 5, No. 4, 2012, p. 1-13.

    Research output: Contribution to journalArticleAcademicpeer-review

    TY - JOUR

    T1 - Using the analytic hierarchy process to elicit patient preferences: prioritizing multiple outcome measures of antidepressant drug treatment

    AU - Hummel, M.J.M.

    AU - Volz, F.

    AU - van Manen, Jeanette Gabrielle

    AU - Danner, M.

    AU - Dintsios, C.-M.

    AU - IJzerman, Maarten Joost

    AU - Gerber, A.

    PY - 2012

    Y1 - 2012

    N2 - 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 fu¨r Qualita¨ t 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.

    AB - 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 fu¨r Qualita¨ t 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.

    KW - IR-82232

    KW - METIS-288990

    M3 - Article

    VL - 5

    SP - 1

    EP - 13

    JO - Patient : patient centered outcomes research

    JF - Patient : patient centered outcomes research

    SN - 1178-1653

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