Empirical comparison of discrete choice experiment and best-worst scaling to estimate stakeholders' risk tolerance for hip replacement surgery

Objectives Empirical comparison of two preference elicitation methods, discrete choice experiment (DCE) and profile case best-worst scaling (BWS), regarding the estimation of the risk tolerance for hip replacement surgery (total hip arthroplasty and total hip resurfacing arthroplasty). Methods An online survey was constructed, following international guidelines, and consisted of socio-demographic questions and two randomised sections with 12 DCE and 8 BWS questions. The survey was sent to a general population who can be faced with choosing between THA and TRA (males between 45-65 years old) in the US. After an intensive literature search, the following attributes were selected: probability of a first and a second revision in seven years, pain relief, ability to perform moderate daily activities, and hospital stay. In addition, survey respondents rated the difficulty of each method and the time to complete each section was monitored. BWS and DCE data was analysed using conditional logit analysis. The maximum acceptable risk (MAR) for a revision was estimated for four different hypothetical hip replacement scenarios. Results The final data set consisted of 429 respondents. The MARs estimated for four hypothetical hip replacement scenarios differed between both methods, ranging from 0% to 19% difference for a first revision. BWS questions took significantly more time (401 s.) than DCE (228 s.) questions. And respondents found BWS more difficult to complete. Conclusions Both methods to elicit stakeholder preferences produce different results. Yet, both seem to be consistent in predicting risk tolerance if the benefits are changed. However, DCE seems to be more sensitive for a change in benefits and risks while the MAR estimates obtained through BWS have considerably lower uncertainty than DC

Design of a freeform two-reflector system to collimate and shape a point source distribution

In this paper we propose a method to compute a freeform reflector system for collimating and shaping a beam from a point source. We construct these reflectors such that the radiant intensity of the source is converted into a desired target. An important generalization in our approach compared to previous research is that the output beam can be in an arbitrary direction. The design problem is approached by using a generalized Monge-Amp\`ere equation. This equation is solved using a least-squares algorithm for non-quadratic cost functions. This algorithm calculates the optical map, from which we can then compute the surfaces. We test our algorithm on two cases. First we consider a uniform source and target distribution. Next, we use the model of a laser diode light source and a ring-shaped target distribution

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

The Author(s) 2015. This article is published with open access at Springerlink.com Abstract 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 eco-nomic 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 appro-priate 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 wer

Public stated preferences and predicted uptake for genome-based colorectal cancer screening

Background Emerging developments in nanomedicine allow the development of genome-based technologies for non-invasive and individualised screening for diseases such as colorectal cancer. The main objective of this study was to measure user preferences for colorectal cancer screening using a nanopill. Methods A discrete choice experiment was used to estimate the preferences for five competing diagnostic techniques including the nanopill and iFOBT. Alternative screening scenarios were described using five attributes namely: preparation involved, sensitivity, specificity, complication rate and testing frequency. Fourteen random and two fixed choice tasks, each consisting of three alternatives, were offered to 2225 individuals. Data were analysed using the McFadden conditional logit model. Results Thirteen hundred and fifty-six respondents completed the questionnaire. The most important attributes (and preferred levels) were the screening technique (nanopill), sensitivity (100%) and preparation (no preparation). Stated screening uptake for the nanopill was 79%, compared to 76% for iFOBT. In the case of screening with the nanopill, the percentage of people preferring not to be screened would be reduced from 19.2% (iFOBT) to 16.7%. Conclusions Although the expected benefits of nanotechnology based colorectal cancer screening are improved screening uptake, assuming more accurate test results and less preparation involved, the relative preference of the nanopill is only slightly higher than the iFOBT. Estimating user preferences during the development of diagnostic technologies could be used to identify relative performance, including perceived benefits and harms compared to competitors allowing for significant changes to be made throughout the process of developmen