Measuring Health Equity in the TC LHIN
Hospitals and community health centres (CHCs) in the Toronto Central LHIN (TC LHIN) are now collecting client and patient-level demographic information. The TC LHIN has asked Mount Sinai Hospital to lead and support hospitals and CHCs as they begin asking all clients and patients eight standardized demographic questions.
The questions were developed and tested through the The Tri-Hospital and Toronto Public Health Health Equity Data Collection Research Project. This study, undertaken by Mount Sinai Hospital, Centre for Addiction and Mental Health, St Michael’s Hospital and Toronto Public Health resulted in eight core and three optional questions around language, race/ethnicity, length of stay in Canada, disability, gender identity, sexual orientation, income, religion and housing.
The reason for collecting this information is to understand who our clients and patients are, so we can provide and plan for programs and services to meet their individual needs. Collecting demographic data is fundamental for eliminating health inequities and finding opportunities for improvement in the quality of care that we provide.
The data that is collected is analyzed to detect any differences in health outcomes experienced by clients/patients based on demographic variables like race, language, and income. Solutions are put in place and the data is then used to see if the solutions reduce health inequities.
With all hospitals and community health centres collecting the same demographic information in the exact same way, there is a strengthened capacity for a system-wide approach to ensuring the best health outcomes for all across the Toronto Central LHIN.
For more information about the Measuring Health Equity project at Mount Sinai Hospital, including frequently asked questions,please download the patient brochure from the Quick Links, or contact the Patient Relations Office at email@example.com or 416-586-4800 ext. 5066.
We Ask Because We Care: The Tri-Hospital + TPH Health Equity Data Collection Research Project
In 2010 three of Toronto’s most diverse hospitals, the Centre for Addiction and Mental Health (CAMH), Mount Sinai Hospital and St. Michael’s Hospital, identified an acute need for quality patient socio-demographic data and launched a pilot project to develop an evidence-based approach for collecting this patient information. Toronto Public Health later joined this effort creating potential for broader impact within the sector. The organizations aimed to answer three key questions:
- What are the best methods to collect patient demographic data?
- What questions are most effective for capturing useful data while maximizing comfort of both staff and patients?
- What is the relationship between demographic factors (e.g., language, disability, etc.) and self-reported health?
Prior to launching the pilot project, the partners conducted a literature review and environmental scan, identified the demographic questions and developed training materials for data collectors. Data was collected on patients’ race, age, preferred language to speak and read, length of residency in Canada, housing status, disability status, religion, gender identity, sexual orientation and income. A variety of data collection methods were used to reflect the unique patient populations of each site, while allowing the partners to examine the impact of different collection techniques on data quality. The data collectors gathered patient information through in-person interviews, paper copies and computer tablets in waiting rooms.
The project was an overwhelming success with a patient participation rate exceeding 85%. Given its potential for transforming patient care, the Toronto Central Local Health Integration Network (TC LHIN) issued a directive requiring all its 17 hospitals to begin collecting data from patients using eight core socio-demographic questions. Data collection and analysis is crucial to the health care system’s ability to meet the diverse needs of Toronto’s population and improve the quality of health care overall. Additionally, hospitals are finally able to know the patients they serve and better meet their needs.
Evidence shows that different groups of people experience different health outcomes based on demographic characteristics, like income, ethnicity, ability and gender.
- Women and men from the lowest-income areas are almost twice as likely to be hospitalized for depression than those from the highest-income areas1;
- The life expectancy of First Nation citizens is five to seven years less than other non-Aboriginal Canadians and infant mortality rates are 1.5 times higher among First Nations2;
- Bisexual women are twice as likely to report fair or poor health in comparison to heterosexual men and women who report the same health status3;
- In Hamilton, Ontario, the lung cancer mortality rate in the lowest-income neighborhoods is 15 times higher than in the highest income neigborhoods4.
Marylin Kanee, Director, Human Rights & Health Equity, Mount Sinai Hospital
Caroline Bennett-AbuAyyash, Health Equity Project Coordinator, Measuring Health Equity, Mount Sinai Hospital
Branka Agic, Manager, Health Equity, Centre for Addiction & Mental Health (CAMH)
Ruby Lam, Manager, Access and Equity, Toronto Public Health
Anthony Mohamed, Senior Specialist, Equity & Community Engagement, St Michael's Hospital
- Lin E, Diaz-Granados N, Stewart DE, Rhodes AE, Yeritsyan N, Johns A, Duong-Hua M, Bierman AS. Depression: In: Bierman AS, editor. Project for an Ontario Women’s Health Evidence-Based Report: Volume 1: Toronto. (2009). http://www.powerstudy.ca/webfm_send/83
- Assembly of First Nations. (2011). FACT SHEET - Quality of Life of First Nations. http://www.afn.ca/uploads/files/factsheets/quality_of_life_final_fe.pdf
- Statistics Canada. (2008). http://www.statcan.gc.ca/daily-quotidien/080319/dq080319b-eng.htm
- Steve Buist. (2013). Panel Presentation - Walk the Talk. Removing Barriers to Cancer Care for All. The Cancer Quality Council of Ontario Tenth Annual Signature Event. http://www.cqco.ca/cms/one.aspx?portalId=89613&pageId=291328