Health Care Stories are Good for You
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The document discusses EvidenceNetwork.ca, a platform that connects journalists with health policy experts to provide credible information on health issues. It outlines the importance of evidence in health stories and provides a framework for evaluating the quality of research and data in health policymaking. Additionally, it raises critical questions about research credibility, funding sources, and the context of health findings.
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Health Care Stories are Good for You
- 1. Sharon Manson Singer, EvidenceNetwork.ca Steve Buist, Hamilton Spectator Jennifer Verma, CHSRF
- 2. Introduce EvidenceNetwork.ca Talk about the Hierarchy of Evidence What makes a good health story? A bad one? Top ten questions to ask of health experts about their research Where to go for data How to assess the quality of data Last word to you the audience
- 3. EvidenceNetwork.ca links journalists with health policy experts to provide access to credible, evidence-based information.
- 4. EvidenceNetwork.ca is a non-partisan, web- based project funded by the Canadian Institutes of Health Research and the Manitoba Health Research Council to make the latest evidence on controversial health policy issues available to the media.
- 5. The Canadian Health Accord is scheduled for renegotiation in 2014. Canadians will have to make decisions about many complex health policy issues, including; • Aging population impact • Rising drug costs • Health care accessibility • Private sector financing/delivery • User fees • Sustainability of the healthcare system EvidenceNetwork.ca is committed to working with the media to build a healthy dialogue around Canadian healthcare.
- 8. Systematic Review and Strongest evidence – meta-analysis only as good as the Use upper tier studies underlying studies in a synthesis of research findings Type of Study Expected Results
- 9. Randomized Well designed with experiments sufficient sample size High quality source of Natural experiments exogenous variation generating comparison group Well designed pre and post measures Analytical techniques are appropriate Type of Study How good is it?
- 10. Some control in the Limited source of assignment of exogenous variables or some control of selection treatment or process Well designed pre and post measures Appropriate data with large sample Reasonable approach to estimating Correlational studies counterfactuals Type of Study How good is it?
- 11. Studies without a Credible case selection with explicit causal logic comparison group model Quality outcome measures Collect feedback from participants on quality of Participant Satisfaction intervention Respected individuals or organizations with Expert Opinions explicit rationale for opinion Type of Study How good is it?
- 12. Exploratory case Less credible or studies explicit case selection criteria, theory of change or outcome measure(s) Type of Study How good is it?
- 13. www.EvidenceNetwork.ca Sharon Manson Singer, PhD [email protected]
- 14. Steve Buist, Investigations Editor The Hamilton Spectator
- 15. Luigi Di Bella and the “miracle” cure for cancer (Pulling for the underdog . . .)
- 16. Autism and the MMR vaccine (Science is a lot easier if you just make it up . . .)
- 17. Multiple sclerosis and “liberation therapy” (The underdog tale, with a modern-day social media twist . . .)
- 18. Climate change and the human touch (What makes for a balanced story . . .)
- 20. 1. Who is conducting the science?
- 21. 1. Who is conducting the science? 2. Who is paying for the research?
- 22. 1. Who is conducting the science? 2. Who is paying for the research? 3. Who is paying the researcher?
- 23. 1. Who is conducting the science? 2. Who is paying for the research? 3. Who is paying the researcher? 4. Where are the results being published?
- 24. 1. Who is conducting the science? 2. Who is paying for the research? 3. Who is paying the researcher? 4. Where are the results being published? 5. What was the population being tested?
- 25. 6. What was the sample size?
- 26. 6. What was the sample size? 7. How significant are the results?
- 27. 6. What was the sample size? 7. How significant are the results? 8. What do other people think, and do those people have their own conflicts of interest?
- 28. 9. How do these results fit into the context of what’s already known?
- 29. 9. How do these results fit into the context of what’s already known? 10. Are there opposing viewpoints and how much weight should those viewpoints be given?
- 30. Jenn Verma, Director, Collaboration for Innovation and Improvement
- 31. mythbusters USING EVIDENCE TO DEBUNK COMMON MISCONCEPTIONS IN CANADIAN HEALTHCARE 31
- 32. 32
- 33. THE LATEST RESEARCH SHOWS THAT WE REALLY SHOULD DO SOMETHING WITH ALL THIS RESEARCH 33
- 34. In a review of World Health Organization (WHO) and World Bank recommendations on five topics (contracting, healthcare financing, HHR, tuberculosis control and tobacco control): ◦ 2/8 publications cited systematic reviews; ◦ 5/14 WHO and 2/7 World Bank recommendations were consistent with both the direction and nature of effect claims from systematic reviews. Hoffman SJ, Lavis JN, Bennett S. 2009. The use of research evidence in two international organizations’ recommendations about health systems. Healthcare Policy 9(1): 66-86. 34
- 35. Effective Focused on Population Accessible Health Adapted with permission from Health Quality Ontario Appropriat ely High-quality Safe resourced and performance health systems Integrated Equitable (2011) Patient- Efficient centred 35
- 36. Select Provincial Subject Non- F/P/T International Health Quality Matter jurisdictional Jurisdictions Reporting Councils Experts Organizations Initiatives NL Centre for Health Canadian Institute Canadian Institute National Quality P/T Ministries of Information for Health for Health Forum (US) Health Information Information NB Health Council Health Council of Agency for Health Institute for Clinical Canada Research and Quality Evaluative Sciences Canadian Patient (US) Commissaire à la P/T Health Regions (ON) Safety Institute santé et au bien- NHS Indicators for être du Québec Canadian Stroke Canadian Quality Improvement Network Partnership Against (UK) Health Quality Canadian Cancer Australian Ontario Cardiovascular Commission on Statistics Canada Accreditation Outcomes Research Quality and Safety in Canada MB Institute of Health Care Team Patient Safety Fraser Institute Quality and POWER Study (ON) Ontario Hospital Efficiency in Swedish Public Health Health Quality Health Care Association Agency of Canada Council SK Cardiac Care Network (ON) Heart and Stroke Health Quality Foundation OECD Collaboration for Council AB Excellence in Canadian Diabetes Healthcare Quality Health Canada Association BC Patient Safety and Alberta Diabetes RAND Quality Council Surveillance System Cancer Care Ontario Adapted with permission from the Health Council of Canada (2011) 36
- 37. 37
- 38. Health Indicators provide a Dashboard for Health and Healthcare They can let you know that things are running smoothly. They can alert you to problems that may need attention. 38
- 39. Interpreting Data… rising BMI (Body Mass Index) doesn’t explain the root cause of weight gain. In 2009, Canadians received 121 CT scans per 1000 people. There were also 8 MRI units per million population (vs. 12 MRI units per million as the OECD average). OECD (2011) reports Canada is “lagging behind,” but there is no agreed-upon benchmark. In 2009, Canada had 2.4 physicians per 1000 population (vs. 3.1 OECD avg), but… ◦ We have more physicians than ever before – Is this about supply or distribution and deployment? ◦ We also have more nurses per 1000 people (9.4 in Canada vs. 8.4 OECD avg) 39
- 40. Comparing apples-to-apples? ◦ Age standardization ◦ Risk adjustment Measuring intangibles ◦ e.g., quality of life ◦ Composite indicators 40
- 41. 41
- 42. Lavis J. et al. 2009. SUPPORT Tools for evidence-informed health Policymaking (STP). Health Research Policy & Systems 7(Suppl 1). http://www.health-policysystems.com/content/7/S1/I1 42
- 43. “Numbers can’t ‘talk’ but they can tell you as much as your human sources can. But just like with human sources, you have to ask” (Niles, 2007). Niles R. 2007. Statistics every writer should know: A simple guide to understanding basic statistics, for journalists and other writers who might not know math. http://nilesonline.com/stats/ 43
- 44. Support Tools for Policy Making http://www.chsrf.ca/PublicationsAndResources/Research Reports/Support_Tools_for_Policy-Making.aspx Mythbusters http://www.chsrf.ca/PublicationsAndResources/ Mythbusters.aspx What If? http://www.chsrf.ca/Programs/HealthcareFinancingInnov ationAndTransformation/WhatIf.aspx CHSRF’s Quality of Healthcare in Canada: A Chartbook (2010) CIHI’s Making Sense of Health Indicators (2011) HCC’s A Citizen’s Guide to Health Indicators (2011) CIHI’s Making Sense of Health Rankings (2008) OECD’s Health Data 2011: How Does Canada Compare? (2011) 44