In 2017, Ukraine's Parliament passed legislation establishing a single health benefit package for the entire population called the Programme of Medical Guarantees, financed through general taxes and administered by a single national purchasing agency. This legislation was in line with key principles for financing universal health coverage. However, health professionals and some policymakers have been critical of elements of the reform, including its reliance on general taxes as the source of funding. Using qualitative methods and drawing on deliberative democratic theory and criteria for procedural fairness, this study argues that the acceptance and sustainability of these reforms could have been strengthened by making the decision-making process fairer. It suggests that three factors limited the extent of stakeholders' participation in this process: first, a perception among reformers that fast-paced decision-making was required because there was only a short political window for much needed reforms; second, a lack of trust among reformers in the motives, representativeness, and knowledge of some stakeholders; and third, an under-appreciation of the importance of dialogic engagement with the public. These findings highlight a profound challenge for policymakers. In retrospect, some of those involved in the reform's design and implementation believe that a more meaningful engagement with the public and stakeholders who opposed the reform might have strengthened its legitimacy and durability. At the same time, the study shows how difficult it is to have an inclusive process in settings where some actors may be driven by unconstrained self-interest or lack the capacity to be representative or knowledgeable interlocutors. It suggests that investments in deliberative capital (the attitudes and behaviours that facilitate good deliberation) and in civil society capacity may help overcome this difficulty.
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http://dx.doi.org/10.1093/heapol/czad062 | DOI Listing |
PLoS One
January 2025
Department of Health and Wellness, Cape Winelands District, Ceres, South Africa.
Despite much literature on operations research applied to various healthcare problems, impactful implementation in public healthcare is limited, which often results in allocative inefficiency. This article uses a mobile clinic routing and scheduling problem in the Witzenberg region of South Africa as a case study to demonstrate the improvement of implementation success through cross-disciplinary collaboration, and also to propose a new three-stage approach for modelling a mobile clinic problem that incorporates continuity of care, fairness, and minimisation of distance travelled. Mobile clinics are used in many countries to improve access to healthcare for rural communities.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Faculté des sciences infirmières, Université Laval, Québec, QC, Canada.
Background: Artificial intelligence (AI) predictive models in primary health care have the potential to enhance population health by rapidly and accurately identifying individuals who should receive care and health services. However, these models also carry the risk of perpetuating or amplifying existing biases toward diverse groups. We identified a gap in the current understanding of strategies used to assess and mitigate bias in primary health care algorithms related to individuals' personal or protected attributes.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Cardiology and Institute of Vascular Medicine, Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University Third Hospital, Beijing, China.
Large language models (LLMs) are rapidly advancing medical artificial intelligence, offering revolutionary changes in health care. These models excel in natural language processing (NLP), enhancing clinical support, diagnosis, treatment, and medical research. Breakthroughs, like GPT-4 and BERT (Bidirectional Encoder Representations from Transformer), demonstrate LLMs' evolution through improved computing power and data.
View Article and Find Full Text PDFBMC Public Health
January 2025
School of Mental Health, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Background: In China, migrant workers (MWs) constitute a significant vulnerable group that may be highly susceptible to depression. However, there is a lack of empirical research exploring the correlation between subjective social status (SSS) and depressive symptoms among MWs. The objective of this study is to examine the mediating roles of job fairness and job burnout, as well as to investigate potential generational differences in this association.
View Article and Find Full Text PDFBehav Sci (Basel)
November 2024
Departamento de Matemática y Estadística, Universidad de La Frontera, Temuco 4811230, Chile.
The Multidimensional Fairness Scale (MFS) assesses an individual's experience of fairness across the many contexts of daily life. It has been applied in the USA; however, the psychometric qualities of reliability and validity have not been examined in a Spanish-speaking population or among Chilean university students. A cross-sectional study was conducted on 377 university students to explore these properties.
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