Narrow Results

The impact of the Parkinson's disease and its treatment on the patients' health-related quality of life can be estimated either by means of generic measures such as the european quality of Life-5 Dimensions (EQ-5D) or specific measures such as the 8-item Parkinson's disease questionnaire (PDQ-8). In clinical studies, PDQ-8 could be used in detriment of EQ-5D due to the lack of resources, time or clinical interest in generic measures. Nevertheless, PDQ-8 cannot be applied in cost-effectiveness analyses which require generic measures and quantitative utility scores, such as EQ-5D. To deal with this problem, a commonly used solution is the prediction of EQ-5D from PDQ-8. In this paper, we propose a new probabilistic method to predict EQ-5D from PDQ-8 using multi-dimensional Bayesian network classifiers. Our approach is evaluated using five-fold cross-validation experiments carried out on a Parkinson's data set containing 488 patients, and is compared with two additional Bayesian network-based approaches, two commonly used mapping methods namely, ordinary least squares and censored least absolute deviations, and a deterministic model. Experimental results are promising in terms of predictive performance as well as the identification of dependence relationships among EQ-5D and PDQ-8 items that the mapping approaches are unable to detect.

Despite widespread efforts to expand health insurance in developing countries, there is scant evidence as to whether doing so actually improves people’s health. This paper aims to fill this gap by evaluating the impact of Rural Mutual Health Care (RMHC), a community-based health insurance scheme, on enrollees’ health outcomes. RMHC is a social experiment that was conducted in one of China’s western provinces from 2003 to 2006. The RMHC experiment adopted a pre–post treatment-control study design. This study used panel data collected in 2002, 1 year prior to the intervention, and followed up in 2005, 2 years after the intervention, both in the intervention and control sites. We measured health status using both a 5-point Categorical Rating Scale and the EQ-5D instruments. The estimation method used here is difference-in-difference combined propensity score matching. The results show that RMHC has a positive effect on the health status of participants. Among the five dimensions of EQ-5D, RMHC significantly reduces pain/discomfort and anxiety/depression for the general population, and has a positive impact on mobility and usual activity for those over 55-years old. Our study provides useful policy information on the development of health insurance in developing countries, and also identifies areas where further research is needed.

Generally, the health status can be measured by means of specific or generic questionnaires that let identify if an illness, a complication or a treatment affect the quality of life. In the existing literature the health status concept is a subjective impression, and patient is only person capable to define it. There are a lot of indexes to measure the health status degree, one of them is the EQ-5D where health information is expressed by means of numerical values, although the evaluated indicators are qualitative and subjective. This contribution proposes a linguistic EQ-5D where health information is modelled by means of linguistic information provided by patients in order to manage the uncertainty and subjectivity of such assessments.