Objectives: Telemedicine applications could potentially solve many of the challenges faced by the healthcare sectors in Europe. However, a framework for assessment of these technologies is need by decision makers to assist them in choosing the most efficient and cost-effective technologies. Therefore in 2009 the European Commission initiated the development of a framework for assessing telemedicine applications, based on the users' need for information for decision making. This article presents the Model for ASsessment of Telemedicine applications (MAST) developed in this study. Methods: MAST was developed through workshops with users and stakeholders of telemedicine. Results: Based on the workshops and using the EUnetHTA Core HTA Model as a starting point a three-element model was developed, including: (i) preceding considerations, (ii) multidisciplinary assessment, and (iii) transferability assessment. In the multidisciplinary assessment, the outcomes of telemedicine applications comprise seven domains, based on the domains in the EUnetHTA model. Conclusions: MAST provides a structure for future assessment of telemedicine applications. MAST will be tested during 2010-13 in twenty studies of telemedicine applications in nine European countries in the EC project Renewing Health.
This paper discusses the inherent problems associated with applying dummy coding when including a fixed comparator in a discrete choice experiment, and seeks to illustrate the misinterpretations that may arise if the analyst is not aware of the problem. This note provides two examples of possible misinterpretations with dummy coding and how it is solved with the use of effects coding.
Optimising the design of discrete choice experiments (DCE) involves maximising not only the statistical efficiency, but also how the nature and complexity of the experiment itself affects model parameters and variance. The present paper contributes by investigating the impact of the number of DCE choice sets presented to each respondent on response rate, self-reported choice certainty, perceived choice difficulty, willingness-to-pay (WTP) estimates, and response variance. A sample of 1053 respondents was exposed to 5, 9 or 17 choice sets in a DCE eliciting preferences for dental services. Our results showed no differences in response rates and no systematic differences in the respondents' self-reported perception of the uncertainty of their DCE answers. There were some differences in WTP estimates suggesting that estimated preferences are to some extent context-dependent, but no differences in standard deviations for WTP estimates or goodness-of-fit statistics. Respondents exposed to 17 choice sets had somewhat higher response variance compared to those exposed to 5 choice sets, indicating that cognitive burden may increase with the number of choice sets beyond a certain threshold. Overall, our results suggest that respondents are capable of managing multiple choice sets - in this case 17 choice sets - without problems.
Hospital readmissions receive increasing interest from policy makers because reducing unnecessary readmissions has the potential to simultaneously improve quality and save costs. This paper reviews readmission policies in Denmark, England, Germany and the United States (Medicare system). The suggested roadmap enables researchers and policy makers to systematically compare and analyse readmission policies. We find considerable differences across countries. In Germany, the readmission policy aims to avoid unintended consequences of the introduction of DRG-based payment; it focuses on readmissions of individual patients and hospitals receive only one DRG-based payment for both the initial and the re-admission. In Denmark, England and the US readmission policies aim at quality improvement and focus on readmission rates. In Denmark, readmission rates are publicly reported but payments are not adjusted in relation to readmissions. In England and the US, financial incentives penalise hospitals with readmission rates above a certain benchmark. In England, this benchmark is defined through local clinical review, while it is based on the risk-adjusted national average in the US. At present, not enough evidence exists to give recommendations on the optimal design of readmission policies. The roadmap can be a tool for systematically assessing how elements of other countries' readmission policies can potentially be adopted to improve national policies.
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