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Measuring Health Equity: Initial Implementation of Patient Demographic Data Collection.

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Presentation on theme: "Measuring Health Equity: Initial Implementation of Patient Demographic Data Collection."— Presentation transcript:

1 Measuring Health Equity: Initial Implementation of Patient Demographic Data Collection

2 Equity: A Core Component of Quality TC LHIN emphasis on “Health Equity Vision” TC LHIN is committed to including equity dimensions and objectives in quality healthcare planning TC LHIN aims to: “create and sustain a healthcare system in Toronto where all have equitable access to a full range of high-quality healthcare and support, and systemic and avoidable health inequities are steadily reduced” 1

3 TCLHIN Supports Patient Level Demographic Data Collection TC LHIN recognizes that tracking and addressing health (in)equity necessitates adopting robust demographic data systems TCLHIN has mandated patient level demographic data collection in hospitals – Target date for the initial implementation of demographic data collection: March 2013

4 Equity: A Core Component of Quality The American Institute of Medicine identifies the six pillars of quality healthcare as: efficiency, effectiveness, safety, timeliness, patient-centeredness, and equity 2 Equity is necessary condition for a “Culture of Quality” in hospitals 3 Unchecked inequity leads to increased pressure on hospital services, avoidable future costs, and reduced productivity 4 Disparities in health care have an impact on quality, safety, cost, and risk management 5

5 Equity: A Core Component of Quality Implications of inequity for Canadians Equity-relevant variables such as income and race matter more than health behaviour in determining Canadians’ health outcomes 6 Children from low-income families require more hospital stays and show increased vulnerability to various illnesses, accidental injuries and mental health problems 7 Living conditions, age, income, immigrant status, and race are a few of the social factors shown to significantly affect diabetes, cardiovascular disease, mental health, and self-reported health (see figure on next slide) 8

6 Figure: Age-standardized prevalence of diabetes among urban-dwelling immigrants*, by sex and world region of birth, and among urban-dwelling long-term residents^ in Ontario (2005) * Granted residency status in Canada between 1985-2000 ^ Canadian-born residents and people granted permanent residence prior to 1985 Source: Bierman, A. S. et al. (2012). Social determinants of health and populations at risk. Ontario Women’s Health Equity Report: Improving Health & Promoting Health Equity in Ontario

7 Why Collect Demographic Data? Strengthen patient-centered care by using data to: – Provide information about the prevalence of specific conditions and outcomes in particular groups – Determine the composition of the community being served – Ensure health care serves individual needs – Ensure services are reaching all of the community effectively Use data to evaluate and track programs and services Demographic data is a necessary condition for monitoring equity and fulfilling health equity plans

8 Perceived Challenges Collection of information is illegal Patients won’t want to provide information Process will take too long, impede registration Adapting IT systems to collect info costly Uncertain how information will be used

9 Vision for project Foster an organization-wide culture that is committed to equity as a key element of quality care Promote demographic data collection as a strategy for achieving equity in healthcare Introduce support structures for sustainable and standardized demographic data collection: – Support the creation of a steering committee composed of inter-professional expertise and responsible for overseeing data collection – Support staff through the development and implementation of initial demographic data collection

10 References and Further Reading 1Gardner, B. (2008). Health Equity Discussion Paper. Toronto Central LHIN 2 Institute of Medicine, Committee on Quality of Health Care in America, IOM (2002). Crossing the Quality Chasm. Washington, DC: National Academy Press 3ibid 4Marmot, M., Shipley, M., Brunner, E., & Hemingway, H. (2001). Relative contribution of early life and adult socioeconomic factors to adult morbidity in the Whitehall II study. Journal of Epidemiology and Community Health, 55, 301-307 5Betancourt, J. R., Green, A. R., King, R. R., Tan-McGory, A., Cervantes, M., and Renfrew, M. (2009, February). Improving Quality and Achieving Equity: A Guide for Hospital Leaders. The Disparities Solutions Centre, Massachusetts General Hospital 6Benzeval, M., Dilnot, A., Judge, K., & Taylor, J. (2001). Income and health over the lifecourse: Evidence and policy implications. In H. Graham (Ed.), Understanding Health Inequalities (pp. 96- 112). Buckingham, UK: Open University Press. 7Canadian Institute on Children's Health. (2000). The Health of Canada's Children: A CICH Profile 3rd Edition. Ottawa, Canada: Canadian Institute on Children's Health 8Bierman, A. S. et al. (2012). Social determinants of health and populations at risk. Ontario Women’s Health Equity Report: Improving Health & Promoting Health Equity in Ontario.


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