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Using the Analytic Hierarchy Process to Elicit Patient Preferences

Background and ObjectiveIn 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.MethodsSupported 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).ResultsThe 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.ConclusionsThe 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.

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.

Communicating the parameter uncertainty in the IQWiG efficiency frontier to decision-makers.

The Institute for Quality and Efficiency in Health Care (IQWiG) developed—in a consultation process with an international expert panel—the efficiency frontier (EF) approach to satisfy a range of legal requirements for economic evaluation in Germanys statutory health insurance system. The EF approach is distinctly different from other health economic approaches. Here, we evaluate established tools for assessing and communicating parameter uncertainty in terms of their applicability to the EF approach. Among these are tools that perform the following: (i) graphically display overall uncertainty within the IQWiG EF (scatter plots, confidence bands, and contour plots) and (ii) communicate the uncertainty around the reimbursable price. We found that, within the EF approach, most established plots were not always easy to interpret. Hence, we propose the use of price reimbursement acceptability curves—a modification of the well-known cost-effectiveness acceptability curves. Furthermore, it emerges that the net monetary benefit allows an intuitive interpretation of parameter uncertainty within the EF approach. This research closes a gap for handling uncertainty in the economic evaluation approach of the IQWiG methods when using the EF. However, the precise consequences of uncertainty when determining prices are yet to be defined.

Using qualitative research to facilitate the interpretation of quantitative results from a discrete choice experiment: insights from a survey in elderly ophthalmologic patients

Background Age-related macular degeneration (AMD) is the leading cause of visual impairment and blindness in industrialized countries. Currently, mainly three treatment options are available, which are all intravitreal injections, but differ with regard to the frequency of injections needed, their approval status, and cost. This study aims to estimate patients’ preferences for characteristics of treatment options for neovascular AMD. Methods An interviewer-assisted discrete choice experiment was conducted among patients suffering from AMD treated with intravitreal injections. A Bayesian efficient design was used for the development of 12 choice tasks. In each task patients indicated their preference for one out of two treatment scenarios described by the attributes: side effects, approval status, effect on visual function, injection and monitoring frequency. While answering the choice tasks, patients were asked to think aloud and explain the reasons for choosing or rejecting specific characteristics. Quantitative data were analyzed with a mixed multinomial logit model. Results Eighty-six patients completed the questionnaire. Patients significantly preferred treatments that improve visual function, are approved, are administered in a pro re nata regimen (as needed), and are accompanied by bimonthly monitoring. Patients significantly disliked less frequent monitoring visits (every 4 months) and explained this was due to fear of deterioration being left unnoticed, and in turn experiencing disease deterioration. Significant preference heterogeneity was found for all levels except for bimonthly monitoring visits and severe, rare eye-related side effects. Patients gave clear explanations of their individual preferences during the interviews. Conclusion Significant preference trends were discernible for the overall sample, despite the preference heterogeneity for most treatment characteristics. Patients like to be monitored and treated regularly, but not too frequently or infrequently. The results of our qualitative research facilitated the interpretation of the quantitative data collected in this study.

Focus Groups in Elderly Ophthalmologic Patients: Setting the Stage for Quantitative Preference Elicitation

ObjectivesPatients suffering from age-related macular degeneration (AMD) are rarely actively involved in decision-making, despite facing preference-sensitive treatment decisions. This paper presents a qualitative study to prepare quantitative preference elicitation in AMD patients. The aims of this study were (1) to gain familiarity with and learn about the special requirements of the AMD patient population for quantitative data collection; and (2) to select/refine patient-relevant treatment attributes and levels, and gain insights into preference structures.MethodsSemi-structured focus group interviews were performed. An interview guide including preselected categories in the form of seven potentially patient-relevant treatment attributes was followed. To identify the most patient-relevant treatment attributes, a ranking exercise was performed. Deductive content analyses were done by two independent reviewers for each attribute to derive subcategories (potential levels of attributes) and depict preference trends.ResultsThe focus group interviews included 21 patients. The interviews revealed that quantitative preference surveys in this population will have to be interviewer assisted to make the survey feasible for patients. The five most patient-relevant attributes were the effect on visual function [ranking score (RS): 139], injection frequency (RS: 101), approval status (RS: 83), side effects (RS: 79), and monitoring frequency (RS: 76). Attribute and level refinement was based on patients’ statements. Preference trends and dependencies between attributes informed the quantitative instrument design.ConclusionThis study suggests that qualitative research is a very helpful step to prepare the design and administration of quantitative preference elicitation instruments. It especially facilitated familiarization with the target population and its preferences, and it supported attribute/level refinement.

How Well Can Analytic Hierarchy Process be Used to Elicit Individual Preferences? Insights from a Survey in Patients Suffering from Age-Related Macular Degeneration

BackgroundIn this study, we tested the feasibility of an interviewer-assisted analytic hierarchy process (AHP) in a special patient population with age-related macular degeneration (AMD).ObjectivesOne aim was to generate preference weights regarding AMD treatment characteristics. A secondary aim was to explore the consistency of preference judgments and reasons for inconsistency.MethodsWe generated quantitative importance weights for decision criteria using the matrix multiplication method. A qualitative study component in the form of asking patients to think aloud throughout their judgments was implemented to facilitate understanding of quantitative findings. Consistency ratios were calculated as a measure of logical judgment performance within AHP. If consistency ratios exceeded 0.2, we explored reasons for inconsistency.ResultsWe interviewed 86 patients and generated preference weights for criteria. Patients rated the injection’s effect on visual function the highest (0.44), followed by the frequency of monitoring visits (0.18), approval status (0.13), injection frequency (0.13), and side effects (0.12). Inconsistency in judgments was prevalent at the subcriteria level. Whereas much of the observed inconsistency was due to an excessive use of high/extreme value judgments, these judgments seemed to result from patients reasonably trying to highlight their strong preferences.ConclusionOur study combines quantitative with qualitative data to explore patients’ preference weights and decision processes using the AHP. It suggests that the type of inconsistency observed in judgments of AMD patients mostly results from rational decision making, not from error or lack of understanding. Further research should address which type and extent of inconsistency might be acceptable in different AHP settings.

Patients’ Preferences for Outcome, Process and Cost Attributes in Cancer Treatment: A Systematic Review of Discrete Choice Experiments

IntroductionAs several studies have been conducted to elicit patients’ preferences for cancer treatment, it is important to provide an overview and synthesis of these studies. This study aimed to systematically review discrete choice experiments (DCEs) about patients’ preferences for cancer treatment and assessed the relative importance of outcome, process and cost attributes.MethodsA systematic literature review was conducted using PubMed and EMBASE to identify all DCEs investigating patients’ preferences for cancer treatment between January 2010 and April 2016. Data were extracted using a predefined extraction sheet, and a reporting quality assessment was applied to all studies. Attributes were classified into outcome, process and cost attributes, and their relative importance was assessed.ResultsA total of 28 DCEs were identified. More than half of the studies (56%) received an aggregate score lower than 4 on the PREFS (Purpose, Respondents, Explanation, Findings, Significance) 5-point scale. Most attributes were related to outcome (70%), followed by process (25%) and cost (5%). Outcome attributes were most often significant (81%), followed by process (73%) and cost (67%). The relative importance of outcome attributes was ranked highest in 82% of the cases where it was included, followed by cost (43%) and process (12%).ConclusionThis systematic review suggests that attributes related to cancer treatment outcomes are the most important for patients. Process and cost attributes were less often included in studies but were still (but less) important to patients in most studies. Clinicians and decision makers should be aware that attribute importance might be influenced by level selection for that attribute.

Cost-effectiveness of different strategies to prevent breast and ovarian cancer in German women with a BRCA 1 or 2 mutation

BackgroundWomen with a BRCA1 or BRCA2 mutation are at increased risk of developing breast and/or ovarian cancer. This economic modeling study evaluated different preventive interventions for 30-year-old women with a confirmed BRCA (1 or 2) mutation.MethodsA Markov model was developed to estimate the costs and benefits [i.e., quality-adjusted life years (QALYs), and life years gained (LYG)] associated with prophylactic bilateral mastectomy (BM), prophylactic bilateral salpingo-oophorectomy (BSO), BM plus BSO, BM plus BSO at age 40, and intensified surveillance. Relevant input data was obtained from a large German database including 5902 women with BRCA 1 or 2, and from the literature. The analysis was performed from the German Statutory Health Insurance (SHI) perspective. In order to assess the robustness of the results, deterministic and probabilistic sensitivity analyses were performed.ResultsWith costs of €29,434 and a gain in QALYs of 17.7 (LYG 19.9), BM plus BSO at age 30 was less expensive and more effective than the other strategies, followed by BM plus BSO at age 40. Women who were offered the surveillance strategy had the highest costs at the lowest gain in QALYs/LYS. In the probabilistic sensitivity analysis, the probability of cost-saving was 57% for BM plus BSO. At a WTP of 10,000 € per QALY, the probability of the intervention being cost-effective was 80%.ConclusionsFrom the SHI perspective, undergoing BM plus immediate BSO should be recommended to BRCA 1 or 2 mutation carriers due to its favorable comparative cost-effectiveness.

Price elasticities in the German Statutory Health Insurance market before and after the health care reform of 2009

This paper investigates the change in price elasticity of health insurance choice in Germany after a reform of health insurance contributions. Using a comprehensive data set of all sickness funds between 2004 and 2013, price elasticities are calculated both before and after the reform for the entire market. The general price elasticity is found to be increased more than 4-fold from -0.81 prior to the reform to -3.53 after the reform. By introducing a new kind of health insurance contribution the reform seemingly increased the price elasticity of insured individuals to a more appropriate level under the given market parameters. However, further unintended consequences of the new contribution scheme were massive losses of market share for the more expensive sickness funds and therefore an undivided focus on pricing as the primary competitive element to the detriment of quality.

Comparing Analytic Hierarchy Process and Discrete-Choice Experiment to Elicit Patient Preferences for Treatment Characteristics in Age-Related Macular Degeneration

BACKGROUND In this study, we conducted an analytic hierarchy process (AHP) and a discrete choice experiment (DCE) to elicit the preferences of patients with age-related macular degeneration using identical attributes and levels. OBJECTIVES To compare preference-based weights for age-related macular degeneration treatment attributes and levels generated by two elicitation methods. The properties of both methods were assessed, including ease of instrument use. METHODS A DCE and an AHP experiment were designed on the basis of five attributes. Preference-based weights were generated using the matrix multiplication method for attributes and levels in AHP and a mixed multinomial logit model for levels in the DCE. Attribute importance was further compared using coefficient (DCE) and weight (AHP) level ranges. The questionnaire difficulty was rated on a qualitative scale. Patients were asked to think aloud while providing their judgments. RESULTS AHP and DCE generated similar results regarding levels, stressing a preference for visual improvement, frequent monitoring, on-demand and less frequent injection schemes, approved drugs, and mild side effects. Attribute weights derived on the basis of level ranges led to a ranking that was opposite to the AHP directly calculated attribute weights. For example, visual function ranked first in the AHP and last on the basis of level ranges. CONCLUSIONS The results across the methods were similar, with one exception: the directly measured AHP attribute weights were different from the level-based interpretation of attribute importance in both DCE and AHP. The dependence/independence of attribute importance on level ranges in DCE and AHP, respectively, should be taken into account when choosing a method to support decision making.