Browsing by Author "Hollingworth, S.A."
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Item Economic evaluations of non-communicable diseases conducted in Sub-Saharan Africa: a critical review of data sources(Cost Effectiveness and Resource Allocation, 2023) Hollingworth, S.A.; Leaupepe, G-A.; Nonvignon, J.; et al.Background Policymakers in sub-Saharan Africa (SSA) face challenging decisions regarding the allocation of health resources. Economic evaluations can help decision makers to determine which health interventions should be funded and or included in their benefits package. A major problem is whether the evaluations incorporated data from sources that are reliable and relevant to the country of interest. We aimed to review the quality of the data sources used in all published economic evaluations for cardiovascular disease and diabetes in SSA. Methods We systematically searched selected databases for all published economic evaluations for CVD and diabetes in SSA. We modified a hierarchy of data sources and used a reference case to measure the adherence to reporting and methodological characteristics, and descriptively analysed author statements. Results From 7,297 articles retrieved from the search, we selected 35 for study inclusion. Most were modelled evaluations and almost all focused on pharmacological interventions. The studies adhered to the reporting standards but were less adherent to the methodological standards. The quality of data sources varied. The quality level of evidence in the data domains of resource use and costs were generally considered of high quality, with studies often sourcing information from reliable databases within the same jurisdiction. The authors of most studies referred to data sources in the discussion section of the publications highlighting the challenges of obtaining good quality and locally relevant data. Conclusions The data sources in some domains are considered high quality but there remains a need to make substantial improvements in the methodological adherence and overall quality of data sources to provide evidence that is sufficiently robust to support decision making in SSA within the context of UHC and health benefits plans. Many SSA governments will need to strengthen and build their capacity to conduct economic evaluations of interventions and health technology assessment for improved priority setting. This capacity building includes enhancing local infrastructures for routine data production and management. If many of the policy makers are using economic evaluations to guide resource allocation, it is imperative that the evidence used is of the feasibly highest quality.Item Economic evaluations of non-communicable diseases conducted in Sub-Saharan Africa: a critical review of data sources(Cost Effectiveness and Resource Allocation, 2023) Hollingworth, S.A.; Nonvignon, J.; Fenny, A.P.; et alBackground Policymakers in sub-Saharan Africa (SSA) face challenging decisions regarding the allocation of health resources. Economic evaluations can help decision makers to determine which health interventions should be funded and or included in their benefits package. A major problem is whether the evaluations incorporated data from sources that are reliable and relevant to the country of interest. We aimed to review the quality of the data sources used in all published economic evaluations for cardiovascular disease and diabetes in SSA. Methods We systematically searched selected databases for all published economic evaluations for CVD and diabetes in SSA. We modified a hierarchy of data sources and used a reference case to measure the adherence to reporting and methodological characteristics, and descriptively analysed author statements. Results From 7,297 articles retrieved from the search, we selected 35 for study inclusion. Most were modelled evaluations and almost all focused on pharmacological interventions. The studies adhered to the reporting standards but were less adherent to the methodological standards. The quality of data sources varied. The quality level of evidence in the data domains of resource use and costs were generally considered of high quality, with studies often sourcing information from reliable databases within the same jurisdiction. The authors of most studies referred to data sources in the discussion section of the publications highlighting the challenges of obtaining good quality and locally relevant data. Conclusions The data sources in some domains are considered high quality but there remains a need to make substantial improvements in the methodological adherence and overall quality of data sources to provide evidence that is sufficiently robust to support decision making in SSA within the context of UHC and health benefits plans. Many SSA governments will need to strengthen and build their capacity to conduct economic evaluations of interventions and health technology assessment for improved priority setting. This capacity building includes enhancing local infrastructures for routine data production and management. If many of the policy makers are using economic evaluations to guide resource allocation, it is imperative that the evidence used is of the feasibly highest quality.Item What do we need to know? Data sources to support evidence-based decisions using health technology assessment in Ghana(Health Research Policy and Systems, 2020-04-28) Nonvignon, J.; Hollingworth, S.A.; Downey, L.; Ruiz, F.J.; Odame, E.; Dsane-Selby, L.; Gyansa-Lutterodt, M.; Chalkidou, K.Background: Evidence-based decision-making for prioritising health is assisted by health technology assessment (HTA) to integrate data on effectiveness, costs and equity to support transparent decisions. Ghana is moving towards universal health coverage, facilitated mainly by the National Health Insurance Scheme (NHIS) established in 2003. The Government of Ghana is committed to institutionalising HTA for priority-setting. We aimed to identify and describe the sources of accessible data to support HTA in Ghana. Methods: We identified and described data sources encompassing six main domains using an existing framework. The domains were epidemiology, clinical efficacy, costs, health service use and consumption, quality of life, and equity. We used existing knowledge, views of stakeholders, and searches of the literature and internet. Results: The data sources for each of the six domains vary in extent and quality. Ghana has several large data sources to support HTA (e.g. Demographic Health Surveys) that have rigorous quality assurance processes. Few accessible data sources were available for costs and resource utilisation. The NHIS is a potentially rich source of data on resource use and costs but there are some limits on access. There are some data on equity but data on quality of life are limited. Conclusions: A small number of quality data sources are available in Ghana but there are some gaps with respect to HTA based on greater use of local and contextualised information. Although more data are becoming available for monitoring, challenges remain in terms of their usefulness for HTA, and some information may not be available in disaggregated form to enable specific analyses. We support recent initiatives for the routine collection of comprehensive and reliable data that is easily accessible for HTA users. A commitment to HTA will require concerted efforts to leverage existing data sources, for example, from the NHIS, and develop and maintain new data (e.g. local health utility estimates). It will be critical that an overarching strategic and mandatory approach to the collection and use of health information is developed for Ghana in parallel to, and informed by, the development of HTA approaches to support resource allocation decisions. The key to HTA is to use the best available data while being open about its limitations and the impact on uncertainty.