Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
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To establish a normative profile of health-related quality of life (HRQoL) for Hong Kong (HK) Chinese residents aged 18 years and above and to examine the relationship between socioeconomic characteristics and health conditions and the preference-based health index. ⋯ The norm values fully represent the societal preferences of the HK population, and knowledge of societal preferences can enable policy makers to allocate resources and prioritize service planning. The study was conducted with the EuroQol International EQ-5D-5L Valuation Protocol and therefore enabled us to compare the EQ-5D-5L values with other countries to facilitate understanding of societal preferences in different jurisdictions.
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To derive a US-based value set for the EQ-5D-5L questionnaire using an international, standardized protocol developed by the EuroQol Group. ⋯ A societal value set for the EQ-5D-5L was developed that can be used for economic evaluations and decision making in US health systems. The internationally established, standardized protocol used to develop this US-based value set was recommended by the EuroQol Group and can facilitate cross-country comparisons.
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To evaluate expenditures and sources of payment for prescription drugs in the United States from 1997 to 2015. ⋯ Prescription drugs expenditures have increased over the past 2 decades, but public sources now pay for a growing proportion of prescription drugs cost regardless of health insurance coverage or income level. Out-of-pocket expenditures have significantly decreased for persons with lower incomes since the implementation of Medicare Part D and the Affordable Care Act.
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Common health state valuation methodology, such as time tradeoff (TTO) and standard gamble (SG), is typically applied under several descriptively invalid assumptions, for example, related to linear quality-adjusted life years (QALYs) or expected utility (EU) theory. Hence, the current use of results from health state valuation exercises may lead to biased QALY weights, which may in turn affect decisions based on economic evaluations using such weights. Methods have been proposed to correct responses for the biases associated with different health state valuation techniques. In this article we outline the relevance of prospect theory (PT), which has become the dominant descriptive alternative to EU, for health state valuations and economic evaluations. ⋯ Suggestions for research addressing these issues are provided. Nonetheless, if validly corrected health state valuations become available, we argue in favor of using these in economic evaluations.
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This paper examines the implications of the improvements in observational methods and research design, as well as the growing availability of real world data for the quality of RWE. These developments have been very positive. On the other hand, unstructured data, such as medical notes, and the sparcity of data created by merging multiple data assets are not easily handled by traditional health services research statistical methods. In response, machine learning methods are gaining increased traction as potential tools for analyzing massive, complex datasets. ⋯ Machine learning methods have traditionally been used for classification and prediction, rather than causal inference. The prediction capabilities of machine learning are valuable by themselves. However, using machine learning for causal inference is still evolving. Machine learning can be used for hypothesis generation, followed by the application of traditional causal methods. But relatively recent developments, such as targeted maximum likelihood methods, are directly integrating machine learning with causal inference.