PCV96 - Acceptability of technological treatment and the effect of respondent characteristics on treatment preference

OBJECTIVES:\ud Surgical and/or technological treatment such as nerve stimulation is becoming increasingly popular in the treatment of acquired ankle-foot deformity in rehabilitation medicine. It is known that the older and impaired population can be technology adverse. The purpose of this study was to determine the acceptability of invasive technological treatment to patients and healthy controls and to study the influence of respondent characteristics on the preference for treatment.\ud \ud METHODS:\ud A total of 204 Respondents participated in a conjoint analysis discrete choice experiment. Ankle-foot impairment was related to either central neurological (n = 58), or peripheral neurological disease (n = 54). Healthy respondents were also included (n = 92). The amount of information on the decision problem\ud which was provided to the healthy controls varied. A multinomial logit regression model was used to estimate part worth utilities for the attribute levels of 8 criteria (treatment duration, treatment impact, duration and ease of use of aids, complication severity and rate, comfort & cosmetics, result type and success rate on choice of treatment) with 2–4 levels and attribute importance and to study the influence of age, gender, educational level, cognitive impairment, physical impairment and extent of information provision prior to the experiment on the fit of the regression model.\ud \ud RESULTS:\ud All treatment attributes have a significant influence on treatment choice. Most important are impact of treatment (20%) and duration & ease of use of aids (19%). No operation (0.46) and minimal use of aids (0.39) is preferred. Age has a significant influence (W = 4.92; p = 0.026). No effect of cognitive impairment or ankle-foot impairment was found.\ud \ud CONCLUSIONS:\ud It could be concluded that 1) surgical treatment and the use of technology are considered negative aspects of treatment, and 2) age-matched healthy respondents’ preferences can be used as predictors for cognitively and physically impaired patients

Validating a Multi-criteria decision analysis (MCDA) framework for health care decision making (abstract)

OBJECTIVES: When evaluating healthcare interventions, decision-makers are increasingly asked to consider multiple criteria to support their decision. The MCDA-based EVIDEM framework was developed to support this process. It includes a simple weight elicitation technique, designed to be easily applicable by a broad range of users. The objective of this study was to compare the EVIDEM technique with more traditional techniques. METHODS: An online questionnaire was developed comparing the EVIDEM technique with four alternative techniques including AHP, best/worst scaling, ranking and point-allocation. A convenience sample of 60 Dutch and Canadian students were asked to fill out the questionnaires as if they were sitting in an advisory committee for reimbursement/prioritization of healthcare interventions. They were asked to provide weights for 14 criteria using two techniques, and to provide feedback on ease of use and clarity of concepts of the different techniques. RESULTS: Results based on the first 30 responses show that EVIDEM is easy to understand and takes little time to complete, three minutes on average. Criteria weights derived using the EVIDEM technique and best/worst scaling are divergent. Comparing the rank order of criteria respondents gave using these two techniques; there is more resemblance in rank order of criteria weighted with the EVIDEM technique. Compared to AHP/ranking/point-allocation, EVIDEM takes less time to complete but is only preferred by 33% of decision-makers. AHP/ranking and point allocation were often described as clearer and more reflective of the respondents’ opinion. CONCLUSIONS: The simple technique is proposed as a starting point for users wishing to adapt the EVIDEM framework to their own context. Other techniques may be preferred and their impact on the MCDA value estimate generated by applying the framework is being explored. This project is part of a large collaborative work that includes developing and validating this framework to facilitate sound and efficient MCDA-applications

From efficacy to equity: Literature review of decision criteria for resource allocation and healthcare decisionmaking

Objectives Resource allocation is a challenging issue faced by health policy decisionmakers requiring careful consideration of many factors. Objectives of this study were to identify decision criteria and their frequency reported in the literature on healthcare decisionmaking. Method An extensive literature search was performed in Medline and EMBASE to identify articles reporting healthcare decision criteria. Studies conducted with decisionmakers (e.g., focus groups, surveys, interviews), conceptual and review articles and articles describing multicriteria tools were included. Criteria were extracted, organized using a classification system derived from the EVIDEM framework and applying multicriteria decision analysis (MCDA) principles, and the frequency of their occurrence was measured. Results Out of 3146 records identified, 2790 were excluded. Out of 356 articles assessed for eligibility, 40 studies included. Criteria were identified from studies performed in several regions of the world involving decisionmakers at micro, meso and macro levels of decision and from studies reporting on multicriteria tools. Large variations in terminology used to define criteria were observed and 360 different terms were identified. These were assigned to 58 criteria which were classified in 9 different categories including: health outcomes; types of benefit; disease impact; therapeutic context; economic impact; quality of evidence; implementation complexity; priority, fairness and ethics; and overall context. The most frequently mentioned criteria were: equity/fairness (32 times), efficacy/effectiveness (29), stakeholder interests and pressures (28), cost-effectiveness (23), strength of evidence (20), safety (19), mission and mandate of health system (19), organizational requirements and capacity (17), patient-reported outcomes (17) and need (16). Conclusion This study highlights the importance of considering both normative and feasibility criteria for fair allocation of resources and optimized decisionmaking for coverage and use of healthcare interventions. This analysis provides a foundation to develop a questionnaire for an international survey of decisionmakers on criteria and their relative importance. The ultimate objective is to develop sound multicriteria approaches to enlighten healthcare decisionmaking and priority-settin

The use of multi-criteria decision methods in health care:Which method is most suitable for healthy and cognitively impaired population?

OBJECTIVES: To select the best multi-criteria decision making method for use with cognitively impaired patients. Population. A convenience sample of 28 subjects, 12 healthy and 16 cognitively impaired. METHODS: Based on a literature review, 5 multicriteria methods were chosen for comparison including: Kepner-tregoe analysis (KTA), simple multi attribute rating technique (SMART), SMART using swing weights (SWING), Analytic Hierarchy Process (AHP) and Conjoint Analysis (CA). Four attributes of treatment were identified (impact, duration, and end-result of treatment and associated risks). Subjects were asked to both rank and rate the importance of these attributes. After using the methods to establish preferences for treatment, subjects were asked to judge the overall difficulty of the techniques on 1–10 score, and answer questions regarding clarity of explanation of method, difficulty in answering questions, understanding method in relation to goal, and use of the method in health care situations. Subjects were interviewed either once (n = 14) or twice (n = 14) (Only the results of the first measurement are presented) RESULTS: In the overall rating of methods CA scored best (mean score 3.65), followed by SMART (3.70), AHP (4.00), SWING (4.40) and KTA (4.67). CA also scored best on verbal/written explanation, understanding of method in relation to goal second and usefulness in health care situations, and scored second place on difficulty in answering questions. In the impaired population, AHP was rated best on the overall difficulty score. CONCLUSIONS: In this pilot study, conjoint analysis was the most preferred method of preference elicitation. Our main concern regarding CA is the time it takes to fill out a CA questionnaire and the fact that data analysis is most complicated of all methods included. Another concern regarding the use of multicriteria methods needing further study is the rate of rank-reversal between methods in the cognitively impaired population

PHP235 – Combining Headroom and Return on Investment Analysis To Rank Potential Commercial Value of Six Medical Devices in Development

Objectives: The development process of medical devices strongly depends on the financial resources available and the expected return on investment to manufacturers. The aim of this paper is to analyse the potential commercial viability of two disruptive and four incremental medical devices in different stages of development. Methods: The headroom method combined with the return on investment analysis was performed for one therapeutic and five diagnostic devices for different clinical target areas. Information regarding maximum additional benefit that could be obtained with new device, the estimated production price and expected sales volume was gathered from literature and expert opinions. A willingness-to-pay threshold for one additional QALY of € 30,000 was assumed for headroom analysis. Results: The devices were ranked according to their potential commercial viability. The analysis showed that two disruptive and two incremental devices had reasonably good balance between headroom and unit cost, and two incremental devices had no good balance. The device with the highest potential commercial viability was a disruptive therapeutic device for the cartilage repair treatment in the first clinical trial stage, with estimated headroom for the cost of the new treatment: € 74,600 and an expected production cost of the therapy: € 8,000 per unit. The market volume size was calculated based on the incidence of cartilage defects: 65% in routine knee arthroscopies. The disruptive diagnostic device for home brain monitoring of epilepsy patients in the prototype stage of development had the lowest potential commercial viability, with an estimated headroom of € 81,000 and an expected production costs per unit: € 120,000 that resulted in the unfavorable return on investment. Conclusions: The headroom method combined with a return on investment analysis, offers insight in the potential commercial viability of medical devices under development. The research on the impact of that analysis on actual R&D decision making will still be determined

PIH66 – A Systematic Review To Identify the Use of Preference Elicitation Methods in Health Care Decision Making

Objectives: Preference elicitation methods (PEMs) offer the potential to increase patient-centered medical decision-making (MDM), by offering a measure of benefit along with a measure of value. Preferences can be applied in decisions on: reimbursement, including health technology assessment (HTA); market access, including benefit-risk assessment (BRA), and clinical care. The three decision contexts have different requirements for use and elicitation of preferences. The aim of this systematic review was to identify studies that used PEMs to represent the patient view and identify the types of health care decisions addressed by PEMs. Additionally, PEMs were described by methodological and practical characteristics within the three contexts’ requirements. Methods: Search terms included those related to MDM and patient preferences. Only articles with original data from quantitative PEMs were included. Results: Articles (n=322) selected included 379 PEMs, comprising matching methods (MM) (n=71,18.7%), discrete choice experiments (DCE) (n=96,25.3%), multi-criteria decision analysis (n=12,3. 2%), and other methods (i. e. rating scales), which provide estimates inconsistent with utility theory (n=200,52.8%). Most publications of PEMs had an intended use for clinical decisions (n=134,40%), HTA (n=68,20%), or BRA (n=12,4%). However, many did not specify an intended use (n=156,41.1%). In clinical decisions, rating, ranking, visual analogue scales and direct choice are used most often. In HTA, DCEs and MM are both used frequently, and the elicitation of preferences in BRA was limited to DCEs. Conclusions: Relatively simple preference methods are often adequate in clinical decisions, because they are easy to administer, give fast results, place low cognitive burden on the patient, and low analytical burden on the provider. MM and DCE fulfill the requirements of HTA and BRA but are more complex for the respondents. There were no PEMs that had low cognitive burden, and strong methodological underpinnings which could deliver adequate information to inform HTA and BRA decisions

A Review and Classification of Approaches for Dealing with Uncertainty in Multi-Criteria Decision Analysis for Healthcare Decisions

Multi-criteria decision analysis (MCDA) is increasingly used to support decisions in healthcare involving multiple and conflicting criteria. Although uncertainty is usually carefully addressed in health economic evaluations, whether and how the different sources of uncertainty are dealt with and with what methods in MCDA is less known. The objective of this study is to review how uncertainty can be explicitly taken into account in MCDA and to discuss which approach may be appropriate for healthcare decision makers. A literature review was conducted in the Scopus and PubMed databases. Two reviewers independently categorized studies according to research areas, the type of MCDA used, and the approach used to quantify uncertainty. Selected full text articles were read for methodological details. The search strategy identified 569 studies. The five approaches most identified were fuzzy set theory (45 % of studies), probabilistic sensitivity analysis (15 %), deterministic sensitivity analysis (31 %), Bayesian framework (6 %), and grey theory (3 %). A large number of papers considered the analytic hierarchy process in combination with fuzzy set theory (31 %). Only 3 % of studies were published in healthcare-related journals. In conclusion, our review identified five different approaches to take uncertainty into account in MCDA. The deterministic approach is most likely sufficient for most healthcare policy decisions because of its low complexity and straightforward implementation. However, more complex approaches may be needed when multiple sources of uncertainty must be considered simultaneousl