At the turn of the century, several major efforts were initiated to combat HIV/AIDS and other major epidemics affecting low- and middle-income countries (LMICs). They were accompanied by initiatives to enable recipient countries to collect and use data to guide their public health programmes. These health information systems (HIS) typify systems in that they have multiple interacting components, and they are embedded within larger systems. Components of a larger system act as the context for all lower-level systems. Their effects can be pervasive, and thus be taken for granted or regarded as unchangeable.
We identify four contextual factors that affect efforts to strengthen HIS: hierarchical roles, aid funding, corruption, and competing priorities. We provide examples of each as experienced by those working to strengthen HIS in LMICs. Each of these contextual factors can seriously diminish the effectiveness of HIS strengthening efforts and their long-term sustainability. We propose research questions about each that would enable those engaged in HIS strengthening to work effectively and sustainably.
Are you planning on collecting the PEPFAR Orphans and Vulnerable Children (OVC) Monitoring, Evaluation, and Reporting (MER) Essential Survey Indicators? Would you like to learn more about the purpose of these indicators? Do you have questions about how to best sample for the survey? Would you like to find out about additional resources to help with designing and implementing the survey?
If yes, join MEASURE Evaluation for a webinar on January 31st, 2017 from 8:00am-9:30am EST.
We will provide updated guidance for collecting the OVC MER Essential Survey Indicators, summarized from the Frequently Asked Questions document, and respond to any questions on collecting the indicators.
The sustainable development goal (SDG) for health is linked to 67 indicators, eight times more than its predecessor, the Millenium Development Goals. In many low- and middle-income countries (LMICs), the information infrastructure is not yet able to collect and use the data needed for the indicators. As they seek to be responsive to the SDG agenda, LMICs must not lose sight of their local data needs; they should be cautious about embracing untested electronic technologies for data collection, analysis, and use; carefully balance the care provision and data collection responsibilities of care providers; and use evidence of what works in strengthening their health information systems (HIS). While attending to these concerns, countries can look for instances in which SDG indicators are in sync with their own HIS goals.
To address the HIV epidemic and meet the needs of people living with HIV and AIDS (PLHIV), Tanzania’s Ministry of Health and Social Welfare—which, since October 2015, has been called the Ministry of Health, Community Development, Gender, Elderly and Children (MOHCDGEC)—adopted home-based care (HBC) as a component of the continuum of care promoted by the World Health Organization (WHO) and the United States President’s Emergency Plan for AIDS Relief (PEPFAR).
This study seeks to obtain a better understanding of how best to deliver HBC services in the context of changing client needs, as effective and accessible treatment is transforming HIV from a terminal to a chronic condition. MEASURE Evaluation, funded by the United States Agency for International Development (USAID) and PEPFAR, conducted a survey of PLHIV to assess the condition of HBC clients living with HIV and determine needs for and satisfaction with HBC services among those clients. This study took place in five regions of Tanzania between May and August 2015. Study findings can be used to help ensure effective service delivery to better meet the changing HBC client population and to show decision makers how to improve HBC policy and operational guidelines. In particular, findings from this study could be integrated in MOHCDGEC training on HBC guidelines and implementing partner HBC operating guidelines.
Ours is an age of explosive growth in data. Traditional data sources are ever deeper and richer with each passing day. Even more rapidly, new sources of powerful data are emerging. The result is a stunning, exponentially growing torrent of data from every corner of the globe and about nearly every dimension of human life and activity.
This offers challenges and opportunities for society in general and for global health professionals in particular. The increasing amount of data can lead to more insight, better policy and programs, and improvements in people’s lives. However, data can also create noise and confusion if it isn’t used effectively.
In short, data science is a production process, and its central challenge is to integrate the functions just described. Much as the practice of data science often involves merging disparate data sources into a whole far more powerful than the sum of its parts, the process of data science intrinsically involves coordinating the identification of information needs, data exploration, analysis, and the communication of data products so that these activities are far more productive and effective than they could be on their own.
This whitepaper introduces global health professionals to data science. Data science is a production process for generating actionable information. It helps us find, understand, and communicate knowledge hidden in the growing data deluge. In global health, successful data science efforts can extract value from data that might otherwise go unused, and use it to inform policy and support programmatic decision making.
Malaria continues to be an important cause of morbidity and mortality in Madagascar. It has been estimated that the malaria burden costs Madagascar over $52 million annually in terms of treatment costs, lost productivity and prevention expenses. One of the key malaria prevention strategies of the Government of Madagascar consists of large-scale mass distribution campaigns of long-lasting insecticide-treated bed nets (LLIN). Although there is ample evidence that child mortality has decreased in Madagascar, it is unclear whether increases in LLIN ownership have contributed to this decline. This study analyses multiple recent cross-sectional survey data sets to examine the association between household bed net ownership and all-cause child mortality.
Data on household-level bed net ownership confirm that the percentage of households that own one or more bed nets increased substantially following the 2009 and 2010 mass LLIN distribution campaigns. Additionally, all-cause child mortality in Madagascar has declined during the period 2008–2013. Bed net ownership was associated with a 22% reduction in the all-cause child mortality hazard in Madagascar.
Mass bed net distributions contributed strongly to the overall decline in child mortality in Madagascar during the period 2008–2013. However, the decline was not solely attributable to increases in bed net coverage, and nets alone were not able to eliminate most of the child mortality hazard across the island.
In several African countries fertility levels have stagnated or increased slightly. However, many women still report an unmet need for family planning. Therefore achieving further fertility declines requires programs that increase demand for family planning, but that also address the existing unmet need. One way to improve contraceptive access in a cost-effective manner might be to integrate family planning services into other existing health services.
This paper analyzes secondary data from the 2012–2013 Millennium Development Goals (MDG) survey in Madagascar to estimate the number of women with an unmet need for family planning that might benefit from integrating family planning services into other health services. In Madagascar, one third of the demand for family planning is not met; an estimated 820,000 women have an unmet need for family planning. A substantial portion of these women can be reached by integrating family planning services into existing maternal and child health services. Health providers are uniquely positioned to help address method-related reasons for non-use of family planning, such as concerns about health problems and side-effects. Given the large unmet need for family planning, programs should not exclusively focus on increasing the demand for family planning, but also seek new ways to address the existing unmet need.
Our study illustrates that simple analyses of existing health survey data can be an important tool for informing the design of programs to tackle this unmet need.