Regional Network for Equity in Health in east and southern Africa (EQUINET): Disussion Paper 111
The health services delivery system in Zambia is pyramid in structure, with primary healthcare (PHC) services at community level, at the base, followed by first and second level hospitals at distric...t and provincial levels, respectively, and third level (tertiary) services at national level. Notably, primary health services are free in Zambia and health service providers are either governmentowned or not-for-profit facilities.
Over the years, resource constraints have affected the quality and extent of healthcare services at all levels, requiring the mobilisation of additional resources for the sector. In doing so, prioritisation was high on the agenda of health sector reform. The EHB, therefore, prioritises interventions with the highest impact on the population, enabling policy makers to revisit priority diseases and conditions and to cost the services provided at each level of facility. Other key issues in developing the EHB in Zambia have included the need to have cost-effective services and cost per capita of services for more systematic budgeting, to rank interventions and to validate and cost the health benefit package as a whole.
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Disease Control Priorities –3rdEdition, Volume 2.
This book focuses on maternal conditions, childhood illness, and malnutrition. Specifically, the chapters address acute illness and undernutrition in children, principally under age 5. It also covers maternal mortality, morbidity, stillbirth, and ...influences to pregnancy and pre-pregnancy. It also includes the transition to older childhood, in particular, the overlap and commonality with the child development volume
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2006-2008 programme report
BMC Public Health (2018) 18:668 https://doi.org/10.1186/s12889-018-5594-3
Regional Network for Equity in Health in east and southern Africa (EQUINET): Disussion Paper 109
This report describes the evolution of mainland Tanzania’s EHB; the motivations for developing the EHBs, the methods used to develop, define and cost them; how it is being disseminated, communicat...ed, and used; and the facilitators (and barriers) to its development, uptake or use. Findings presented in this report are from three stages of analysis: literature review, key informant perspectives and a national consultative meeting.
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Saving Lives: Universal access to Trauma Services in Kenya
In 2015 around 15 million people living with HIV were receiving antiretroviral treatment (ART) in sub–Saharan Africa. Sustained provision of ART, though both prudent and necessary, creates substantial long–term fiscal obligations for countries affected by HIV/ AIDS. As donor assistance for healt...h remains constrained, novel financing mechanisms are needed to augment funding domestic sources. We explore how Innovative Financing has been used to co–finance domestic HIV/AIDS responses. Based on analysis of non–health sectors, we identify innovative financing instruments that could be used in the HIV response.
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dos Santos et al. BMC Public Health 2014, 14:80 http://www.biomedcentral.com/1471-2458/14/80
High Transmission Areas: Key Populations
PERC produces regional and member state situation analyses, updated regularly.
The Policy Framework for Artificial Intelligence in Tanzania's Health Sector was developed through collaboration between multiple stakeholders, including government bodies, academic institutions, non-governmental organisations (NGOs) and international partners. The framework demonstrates Tanzania’...s dedication to utilising digital technologies and AI to enhance healthcare delivery, facilitate data-driven decision-making, and bolster the resilience of the healthcare system. Although AI integration in Tanzania’s health sector is still in its infancy, a growing number of initiatives are highlighting its potential in clinical care, research, and system management. The Ministry of Health, in collaboration with partners including the President’s Office (PORALG), Fondation Botnar, MUHAS, UDOM and PATH, has spearheaded this initiative with the aim of using AI to minimise errors, improve clinical outcomes and boost the efficiency of the health system.
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