Martens, Patricia

English

Scholarship@Western

Have we been successful?  A policy-maker’s guide to the galaxy of measuring inequities over timePatricia Martens PhDDirector, MCHP;Professor, Community Health Sciences, Faculty of Medicine, University of Manitoba;CIHR/PHAC Applied Public Health ChairStrategic Knowledge Cluster on Population Change and Lifecourse:  SSHRC – Ottawa, ON March 27, 2013MANITOBA CENTRE FOR HEALTH POLICY  A bit of history and background of MCHP– Department of Community Health Sciences, Faculty of Medicine– Worldwide recognition– Funding:  • research grants from provincial and national agencies (like the Canadian Institutes of Health Research, CIHR) • an ongoing grant relationship with Manitoba Health since 1990/91 … a long history since 1970’swww.umanitoba.ca/faculties/medicine/units/mchp/A World-Class RepositoryPopulation‐Based Health RegistryHospitalHome CarePharmaceuticalsCostVital StatisticsProviderNursing HomeMedicalFamily ServicesEducationImmunizationCensus Data at DA level Special data e.g. ICU, Metis cohortSocial HousingERHealthy Child MB dataJustice, U of M, lab and diagnosticsMCHP:  What we do with the information - KT• At the government level– Deliverables (i.e., research reports); briefing of ADMs, DM, Minister of Health, other Ministers, Healthy Child Committee of Cabinet• At the public/clinician level– Four-pagers; clinician one-pagers; media interviews, op eds,, responses to news, website• At the researcher level– Research reports, publications, conferences etc.– Concept Dictionary and Glossary, website• At the RHA level– Annual Workshop Days (WRHA, MH, non-Winnipeg RHAs, Education/Family Services), dissemination of reports, website data– The Need To Know TeamThe Need To Know Team:  MCHP,  with RHA & Manitoba Health top level planners (integrated KT)– Creation of new knowledge, capacity building, disseminate/apply research at the regional level, all undergirded with relationship building• CIHR-funded, 2001-2006 through the Community Alliances for Health Research (CAHR) program, 2008-2013 CIHR/PHAC Applied Public Health Chair for Martens• CIHR 2005 KT Award for Regional Impact• Highlighted as 1 of 5 “knowledge to action” stories in the 2009/2010 annual report of CIHRInvolvement and influencing health policy• MCHP’s Annual Workshop Days– Rural & Northern RHAs, Winnipeg RHA, Manitoba Health Days, Gov’t Days– Look for the STORIES!– NTK facilitates round tables: Evidence-based stories lead to evidence-informed decision-makingBus trip up Pembina Highway to downtown:Life Expectancy at birth (in years):South Pembina Highway:Males:  81 yearsFemales:  87 yearsDowntown:Males: 67 yearsFemales: 71 yearsFransoo et al. 2009Figure 7.6: Trends in Winnipeg Breastfeeding Initiation RatesMaternal age-adjusted percent of newborns breastfeeding at hospital discharge0%10%20%30%40%50%60%70%80%90%100%1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2000/01 2001/02 2002/03 2003/04Time PeriodWpg Most HealthyWpg Average HealthWpg Least HealthyWinnipegManitobasource: Manitoba Centre for Health Policy, 2007Canada Prenatal Nutrition Programs, Healthy Baby and Family First RATE DIFFERENCE 16.0%RD 11.7%Significant “jump” at program onset, p<.003What Works ReportMartens et al. 2008Concentration curves are intuitive• If you don’t dwell on the mathematics, Concentration curves can tell stories to decision makers• How bad is the inequity?• In the words of Michael Marmot and proportionate universalism, what end of the spectrum do we focus upon – targeted or universal?• Is the inequity getting better or worse over time?Concentration curves are intuitiveMartens et al. 201035% of infant deaths in lowest SES, representing 23% of population31% of infant deaths in lowest SES, representing 26% of populationChange in Gini Coefficient over time: p=.08, NSSo what works? … researchers, decision-makers• USER INVOLVEMENT FROM START TO FINISH– integrated KT• INTERACTIVE FORUMS • RELEVANT RESEARCH FOR REGIONS• EVIDENCE-BASED STORY TELLING potentially leads to EVIDENCE-INFORMED DECISION MAKINGSo what does it take?To develop collaborative relationships around data stewardship and use, it takes:• TIME and $ commitment• SHARED LANGUAGE • TRUST• RELATIONSHIP BUILDING• “LETTING GO” of traditional roles• PATIENCE• UNDERSTANDINGBowen S, Erickson T, Martens P.  More than “using research”: the real challenges in promoting evidence-informed decision- making.  Healthcare Policy 2009;4(3):69-84.Bowen S, Martens PJ.  A model for collaborative evaluation of university-community partnerships.  J. Epidemiol. Community Health 2006; 60: 902-907.Bowen S, Martens PJ, The Need To Know Team.  Demystifying “Knowledge Translation”: Learning from  the community. Journal of Health Services Research & Policy 2005;10(4):203-211.Martens PJ, Roos NP.  When health services researchers and policy-makers interact:  Tales from the tectonic plates.  Healthcare Policy 2005;1(1):72-84.But what about health inequities, and translating this research into policy?Key Article under discussion:Martens PJ. The right kind of evidence –integrating, measuring, and making it count in health equity research.  Journal of Urban Health 2012;89(6):925-936.  DOI: 10.1007s11524-012/-9738-y• Online First TM Open Access (July 7, 2012) at: http://www.springerlink.com/content/nglt87w44731q737/  THE RIGHT KIND OF EVIDENCE—WHAT COUNTSAROUND THE DECISION-MAKING TABLE?“Are we producing the right kind of evidence to advance health and health equity? And what kind of research impact do we want and can we expect from health and health equity research? The right kind of evidence is probably a moot point if we work in an integrated KT mode—“right” by research standards means the best possible approaches to answer the questions in the most valid and reliable way, and right by decision-maker standards means a research project which answers something relevant and of high importance.”(Martens 2012:page 929)• Pretend that you are the CEO of an RHA, or the Deputy Minister or Minister of Health.  Someone gives you these graphs.  Jot down the immediate message that the graph is giving you• Remember, we’re trying to answer the question as to whether the gap between rich and poor for this fictitious disease is getting better, worse, or not changing over timeMeasuring SES gap over time:an exercise in what makes intuitive sense for planning and policyWhat‘s a Relative Risk (RR)?• Relative Risk (RR) or Rate Ratio• Take the rate for one group divided by the rate for the other group• If one group rate is 30 per 1000, and the other is 15 per 1000, then the RR = 30/15 = 2• i.e., the first group has double the rate of the second group• For example, in these case studies:– Rate of disease per 1000 for lowest SES group divided by  rate of disease per 1000 for highest SES groupWhat‘s a Risk Difference (RD)?• Risk Difference (RD) or Rate Difference• Take the rate for one group and subtract the rate for the other group• If one group rate is 30 per 1000, and the other is 15 per 1000, then the RD = 30-15 = 15 per thousand• i.e., the first group has 15 people MORE per thousand with the disease compared to the second group• For example, in these case studies:– Rate of disease per 1000 for lowest SES group minus the  rate of disease per 1000 for highest SES groupCase studies 1, 5, 9Case studies 2, 6, 10Case studies 3, 7, 11Case studies 4, 8, 12So what does that tell us?• Be VERY careful of relative measures• The meaning may only be intuitive when the reference group in a time trend analysis has a rate that changes very little.  • If you are going to present relative measures, combine that with the real rates, and with other measures (like rate differences)• Age adjustment?Martens et al. 2010Lessons from deer signs(very short version)Collected over a decade by Pat Martens and friends!Message #1• Are the deer really different, or do we just perceive them as being different?  We need comparative data to tell us that.• Even regions can have very different populations within them –we need contextual dataMessage #2• Look for indicators and measures wherever you can find them to assist in your research projects!• And if you can’t find GOOD data, figure out how to collect it (with input from researchers, planners, decision-makers, health care providers, AND privacy people!)Message #3• We must analyze and interpret data with the highest standards of research skill– Ask the users of the data, and the people closest to the situation to help you interpret the data and work toward change, so you “get it right” (and don’t sound foolish to the insiders!)Message #4• Never lose sight of the fact that indicators and numbers are telling you a story about REAL PEOPLE, so don’t get frustrated trying to get evidence into actionManitobaCentre forHealth Policywww.umanitoba.ca/faculties/medicine/units/mchp/Youtube video about our workplace …http://www.youtube.com/watch?v=r--a96JEuXo&feature=youtube_gdatafacebook.com/mchp.umanitobatwitter.com/mchp_umanitoba(@mchp_umanitoba)

Have we been successful? A policy-maker’s guide to the galaxy of measuring inequities over time

https://ir.lib.uwo.ca/cgi/viewcontent.cgi?article=1071&amp;context=pclc_conf

Have we been successful? A policy-maker’s guide to the galaxy of measuring inequities over time

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