Presentation on theme: "RECOGNIZING RESEARCH PARADIGMS, METHODS, AND IMPACT FOR PEOPLE-CENTRED HEALTH SYSTEMS James Macinko, PhD Associate Professor of Public Health & Health."— Presentation transcript:
RECOGNIZING RESEARCH PARADIGMS, METHODS, AND IMPACT FOR PEOPLE-CENTRED HEALTH SYSTEMS James Macinko, PhD Associate Professor of Public Health & Health Policy New York University
Main themes/guiding questions What are some contributions and challenges of quantitative research traditions to Health Policy and Systems Research in/for people-centered health systems? What are some new approaches to the use of quantitative data that may facilitate more people-centered health systems? How can we strengthen existing and emerging quantitative research traditions and tools to promote better programs and policies to achieve and improve people-centered healthcare?
What have we learned from (mostly) quantitative approaches ? How to quantify differences in healthcare costs and quality How to weigh healthcare payments to reflect the underlying socio-economic and health needs of different populations Approaches (albeit still imperfect) to understanding the burden of disease. Some policy lessons learned: User fees should be abolished. Health workers need to be paid. ITNs reduce mortality and should be free of charge. Early child development programs work. Many others! (over 2500 impact evaluations and 200 systematic reviews at 3ie alone-but are we taking full advantage of this?)
The field of quantitative analysis (especially impact evaluation) is in turmoil The quality of many empirical analysis is weak because assessment of impact requires the construction of a counterfactual. This is extremely hard to accomplish and has led to a scramble for opportunities to use experimental methods and exploitation of natural experiments. 4
Meet the perfect natural experiment Monster randomly attacks Tokyo, but leaves other comparable cities unscathed.* *Note: this usually happens just after you’ve completed your study and published the results. The monster attack will dominate the news and, consequently, there will be no press coverage of your important research finding.
The rise of the “Randomistas” Randomized controlled trials seem to offer solutions to many weaknesses of impact evaluation designs They can establish causality They provide solutions to statistical problems of bias, selection, omitted variables (confounding), etc. But their promise may have been blown out of proportion “The World Bank is finally embracing science” Lancet, 2004 “Britain has given the world Shakespeare, Newtonian physics, the theory of evolution, parliamentary democracy—and the randomized trial” BMJ editorial, There are major limitations to these methods Well-designed RCTs can tell us what happened, but not why Limited generalizability (and problem of heterogeneous effects) RCTs may fail just as often as any other research method And this may have led to irrelevant research and other unintended consequences Sometimes absurd generalizations based on small special RCTs Could lead to poor/irrelevant policy choices, stigmatization of vulnerable groups, wasted resources, and missed opportunities. Source: adapted from Deaton, A. 2009; Picciotto 2014
HE USES STATISTICS AS A DRUNKEN MAN USES LAMP POSTS: FOR SUPPORT RATHER THAN FOR ILLUMINATION. - Andrew Lan
Counting and accounting: strengthening people-centered approaches to health policy and health systems With the systematic use of linked datasets and improved data architecture for more reliable and systematic data collection, integration, and analysis, there are powerful opportunities to improve outcomes, reduce harms, and promote greater equity in health. Several promising technologies offer some tantalizing opportunities to bring people into health policy and system research in new and potentially meaningful ways. These and other approaches offer some complimentary ways (NOT SUBSTITUTES) to bring data use and interpretation into participatory forums and to strengthen health systems’ analytic capacity.
1. Making data work for the people Data must communicate more clearly their intent and purpose. This requires more productive interaction with data producers and users at all levels.
2. Linking health and social protections: the potential of clinical records for people- centered health systems Facilitating electronic medical record–based shut-off protection letters (link with legal protections) Using electronic medical records to improve team-based care for homeless veterans (screening for risk and linking with housing services) Brazil: CCT conditions certified through medical records, CHW provides link to programs at the household level. EMR triggers social screening Adapted from: Gottlieb LM, Tirozzi KJ, Manchanda R, Burns AR, Sandel MT. Moving Electronic Medical Records Upstream: Incorporating Social Determinants of Health. Am J Prev Med Sep 9. EMR Triage referral EMR automates social referral EMR Tracks referrals and outcomes EMR facilitates data sharing for advocacy Screening TriageReferral Tracking Sharing
3. Crowdsourcing: bringing outsiders into the research team Though 200+ years old, crowdsourcing has only begun to be used in public health. Examples include: Supplement traditional survey research (promote inclusion of under- represented groups in research) Formative research (solicit feedback about health promotion/education materials) Evaluating the scientific literature (solicit additional literature and updates on systematic reviews) Program evaluation (annotating public webcam images to determine how addition of a bike lane changed transportation patterns) Data processing (classifying polyps on computed tomography (CT) colonography images; identification of malaria infection in RBCs) Surveillance/monitoring (tracking influenza via cellphones and social media, monitoring teacher attendance and physician availability) Identifying resources (mapping automated external defibrillators, ). Ranard BL, et al. Crowdsourcing--harnessing the masses to advance health and medicine, a systematic review. J Gen Intern Med Jan;29(1):
4. Enhancing learning and experimentation through simulations and games Bobby Milstein, Jack Homer, and Gary Hirsch. Analyzing National Health Reform Strategies With a Dynamic Simulation Model. American Journal of Public Health: May 2010, Vol. 100, No. 5, pp “expanding insurance coverage and improving health care quality is cost-effective, but …if implemented without other interventions would likely yield… increasing costs and worsening health inequities. Expanding primary care capacity for the disadvantaged could dramatically improve access and equity and would help to lower costs…” Results from “HealthBound” policy simulation game:
Barriers to making quantitative approaches more people-centered Most countries don’t have the capacity to take advantage of many of these approaches in a systematic way Current investments in health systems do not tend to favor development of local health information infrastructure and capacity Fragmented and low-resourced health systems have fragmented and incomplete data systems There are large global inequities in basic STEM training. Other sectors (besides health) exhibit strong pull forces. People could be entirely cut out of participation except to create and provide increasingly vast amounts of data about themselves. Use of new technologies can create dependencies on the (mostly commercial) suppliers of this technology None of these approaches can be should be performed in a laboratory setting
What do we need to do to make quantitative approaches more relevant to people-entered health systems? Integrate implementation science into impact evaluations- expand from efficacy to effectiveness to empowerment Embrace multiple types of evidence and the complexity of different methodological approaches Embed new forms of transparency and accountability into impact and other evaluations Institutionalize multi-sectorial approaches to quantitative monitoring and evaluation alongside other approaches Democratizing data will require links with education to increase numerical literacy through better learning tools Seek global commitments to support more people-centered evaluations Expand and enhance global communities of practice to demonstrate how these approaches might work
NOT EVERYTHING THAT CAN BE COUNTED COUNTS, AND NOT EVERYTHING THAT COUNTS CAN BE COUNTED. - Albert Einstein
Acknowledgments References: Angus Deaton (2009) “Instruments of development: Randomization in the tropics and the search for the elusive keys to economic development” J. Larry Aber (2014) “Child development and social policy: building science for action” Guiji and Roche (2014). Does impact evaluation in development matter?; Camfield and Duvendack (2014). Impact evaluation—are we off the gold standard? European Journal of Development Research; 26 (1): 1-11; Thanks to Diana Silver, Dina Balabanova, Lucy Gilson, Rene Loewenson, and Barbara McPake for comments and conversations that helped to shape this presentation.