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

PND60 - Comparison of the valuation of treatment alternatives in Parkinson's disease with best-wordt scaling, time trade-off and visual analogue scales

Objectives: Traditional valuation methods are insensitive to small improvements in process and outcome of care. Best-Worst scaling (BWS) was proposed as a sensitive and efficient method to determine the relative value of different treatments for the same disease, which would be desirable to estimate cost-effectiveness. The study objective was to compare the ability of BWS to differentiate between different treatment alternatives to that of Time Trade Off (TTO) and Visual Analogue Scales (VAS). Methods: An online survey was conducted to estimate individual values for six different treatments reflecting the real-life options in the treatment of Parkinson’s Disease with BWS2, BWS3, TTO and VAS (n=592). Pearson correlation coefficient was used to examine the strength of linear dependence between estimated utility scores. Results: Twenty-seven percent of respondents was not willing to trade life years in TTO. Only two percent of the respondent does not differentiate between the value of health states with VAS. When non-traders were excluded from the analysis, the best case scenario was valued significantly higher than the worst case scenario with all methods. Rank reversals among intermediate alternatives were common. The correlation between utility scores was very strong (VAS-BWS2 1,0; VAS-BWS3 0.98; TTO-BWS2 0.99; TTO-BWS3 0.98, BWS2-BWS3 0.96; P<0.000, n=434). Conclusions: The results demonstrate that BWS, TTO and VAS can be used to elicit incremental utility gain of small improvements in care. However, all methods have limitations. VAS does not result in utilities and some respondents do not trade with TTO. While the use of BWS is attractive because of its ability to estimate utilities for many different treatment alternatives, its applicability in CEA is limited because BWS utilities are not anchored on a 0-1 utility scale. We propose to use TTO to estimate utility for extreme health states, and to use BWS to value intermediate health states which differ on process characteristics