Beyond Scaling Up: Building the evidence base


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This presentation was given at the 'Beyond Scaling Up: Pathways to Universal Access' workshop which was held at the Institute of Development Studies, Brighton on the 24-25 May, 2010. This event was co-sponsored by the Future Health Systems Research Programme Consortium and the STEPS Centre. Matlin presented on the challenge of building the evidence base in this area.

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  • One way to better understand the wealth-health link is by dissecting the data in space and time. Among the first to define (and begin to explain) the relation between wealth and health was Samuel Preston, in his classic paper ‘The Changing Relation between Mortality and Level of Economic Development’ (1975). The Preston curve (as it's come to be known) makes 2 points: (1) there is a strong, positive relationship between national income levels and life expectancy in poorer countries, but not in richer countries; life expectancy in richer countries is less sensitive to variations in average income; (2) the relationship is changing, with life expectancy increasing over time at all income levels. Is the curve being pushed up by knowledge, technology, cultural factors, or what?
  • Beyond Scaling Up: Building the evidence base

    1. 1. Beyond Scaling Up: Pathways to Universal Access Institute of Development Studies, Brighton, 24-25 May 2010 Building evidence   Stephen Matlin
    2. 2. <ul><li>How important is evidence of what works and what does not for the rapid implementation of sustainable change? </li></ul><ul><li>Systems approach </li></ul><ul><li>Key Question: </li></ul><ul><li>What’s wrong with the system? </li></ul><ul><li>Do we ask the right questions? </li></ul><ul><li>Do we have the right models/assumptions? </li></ul>
    3. 3. New Yorker, 2006 and thanks to R Terry, WHO
    4. 4. Preston curve <ul><li>20th century mortality decline had its origin in technical progress </li></ul><ul><li>Easterlin, European Review of Economic History 3: 257–94, 1999 </li></ul><ul><li>Much of the variation in country outcomes results from very substantial cross-country variation in the rate of technical progress </li></ul><ul><li>e.g. technical progress explains 66 percent of inter-country variation in the decline in infant mortality from 1962–1987, whereas change in income explains 9 percent </li></ul><ul><li>J amison, Disease Control Priorities in Developing Countries (DCP2), World Bank, 2006 </li></ul>Too little research being undertaken to address the health needs of developing countries Commission on Health Research for Development 1990 Ignorance is fatal
    5. 5. Technological and social innovation
    6. 6. <ul><li>“ The health system does not just act on, but also interacts with ecological, social and microbial processes.” </li></ul><ul><li>You can’t obtain information about any system without interacting with it. </li></ul><ul><li>Every interaction causes change (reversible or irreversible). </li></ul><ul><li>Scaling up health system is itself an experiment </li></ul><ul><li>Research on scaling up: what kinds of ‘evidence’? </li></ul><ul><li>Capacity building </li></ul><ul><li>- Research </li></ul><ul><li>- Innovation </li></ul><ul><li>Individual, Institutional, Systems </li></ul>
    7. 7. Research system Innovation system Health research system Health sector Other sectors National Global Research and innovation systems
    8. 8. Mapping of country scientific capability to adopt 16 technology applications RAND, 2006: The Global Technology Revolution 2020
    9. 9. Mapping of country scientific capability to adopt 16 technology applications RAND, 2006: The Global Technology Revolution 2020 <ul><li>Major drivers and barriers </li></ul><ul><li>Cost and financing </li></ul><ul><li>Laws and policies </li></ul><ul><li>Social values, public opinion, and politics </li></ul><ul><li>Infrastructure </li></ul><ul><li>Privacy concerns </li></ul><ul><li>Use of resources and environmental health </li></ul><ul><li>R&D investment </li></ul><ul><li>Education and literacy </li></ul><ul><li>Population and demographics </li></ul>
    10. 10. Matlin & Samuels, The Lancet 2009, 374: 1662-3 Global Health Research and Innovation System <ul><li>Funders </li></ul><ul><ul><li>Public Sector </li></ul></ul><ul><li>Private Sector </li></ul><ul><li>Not-for-Profit Sector </li></ul><ul><li>Intermediaries </li></ul><ul><li>Public-private partnerships </li></ul><ul><li>Advocacy organizations </li></ul><ul><li>Global health initiatives </li></ul>Performers of R&D and innovation <ul><li>Global Public Goods </li></ul><ul><ul><li>Products </li></ul></ul><ul><li>Processes </li></ul><ul><li>Knowledge </li></ul><ul><li>Commercial Products </li></ul><ul><ul><li>Products </li></ul></ul><ul><li>Processes </li></ul><ul><li>Knowledge </li></ul>Health Benefits Better health & health equity Environment for research and innovation for health Influences: push and pull mechanisms Flows of resources, ideas, information, products, mechanisms
    11. 11. <ul><li>Some of the most important innovations are now coming from developing countries </li></ul><ul><li>Shifting power between different countries </li></ul>
    12. 12. “ Developing countries” Developing world GDP (measured in PPP) to overtake advanced economies in 2013 Euromonitor: Countries and Consumers – October 2008 Advanced economies Developing and emerging economies
    13. 13. Researchers per million inhabitants, 2007 or latest available year UNESCO Institute for Statistics, September 2009 Based on FTEs where possible, or on headcounts
    14. 14. <ul><li>Territory size shows the proportion of all scientific papers published in 2001 written by authors living there. </li></ul><ul><li>Scientific papers cover physics, biology, chemistry, mathematics, clinical medicine, biomedical research, engineering, technology, and earth and space sciences. </li></ul><ul><li> </li></ul>Science output
    15. 16. Dealing with multiple, contested goals and framings. Are we talking the same language?
    16. 17. You’re 30 metres above the ground in a balloon You must be a researcher Yes. How did you know? Because what you told me is absolutely correct but completely useless You must be a policy maker Yes, how did you know? Because you don’t know where you are, you don’t know where you’re going, and now you’re blaming me Martin McKee Where am I?
    17. 18. Nobody asked me, anyway