Presentation on theme: "Breast Cancer among Women Living in Poverty: Better Care in Canada than in the United States Historical Cohort Support of a Health Insurance Explanation."— Presentation transcript:
Breast Cancer among Women Living in Poverty: Better Care in Canada than in the United States Historical Cohort Support of a Health Insurance Explanation
Presenter Disclosures No relationships to disclose Funding sources: Canadian Institutes of Health Research Grant no. 67161-2 Manuscript status: Social Work Research (in press)
Abstract We studied breast cancer care among women living in poverty in California & Ontario between 1996 & 2011. Women in Canada were diagnosed earlier, enjoyed better access to breast conserving surgery, radiation (RT) and hormone therapies and survived longer. They even experienced shorter waits for surgery and RT. By observing the historical protective effects of Canada’s universally accessible, single-payer health care system we estimated the Affordable Care Act’s (ACA) likely protections as well as its likely risks.
Longstanding Rhetorical Context Anecdotes about Canadian health care failures abound Long waits for care Care denials—“death lists” “Do you want government in your medicine cabinet?” Does systematic, empirical evidence tend to support or refute such rhetoric ?
Clinical Context Why study breast cancer? Relatively common over the life course Effective screens exist Effective treatment regimes exist Timely diagnosis & best treatment matters Excellent prognoses can be expected: Long survival & high quality of life It is a sentinel health care quality indicator.
Historical-Theoretical Context Large Canada-US studies, exemplified by a General Accounting Office study (1994) found nil to null differences on breast cancer survival Country-by-income interaction discovered (1997) Canadian breast cancer survival better in low-income (LI) neighborhoods only (RR = 1.30) 78 Canada-US cohorts synthesized (2009) Canadian women advantaged in LI neighborhoods only (pooled RR = 1.14); < 65 yoa (RR = 1.21) Knowledge gaps: processesextremely poor Breast cancer care processes in extremely poor places have not yet been studied.
Geo-Economic-Policy Context: During Great Recession, 2007-11 United States Prevalence of people living in poverty increased 25% (12% to 15%) to 46.2 million people Uninsured population rose to more than 50 million Inadequately insured population rise to 100 million [uncovered costs by multi- public & private payers] Canada Prevalence of people living in poverty was nearly constant at approximately 10% The entire population was insured for medically necessary care by a single, public payer.
Research Question: Hypotheses Prior to the enactment of the Affordable Care Act, Did Canadian women living in high poverty neighborhoods with breast cancer experience better care than did their American counterparts? Hypotheses: 1.Canadian women experienced better care and survival. 2.The care and survival of Canadian women was even better when compared to that of uninsured or underinsured American women.
Methods Comparison of Historical Cohorts: High Poverty Neighborhoods in Ontario and California, Women with Breast Cancer Diagnosed Between 1996 & 2000 Followed to 2011
Sampling High Poverty Cohorts Enhanced Ontario and California cancer registries Comprehensive, reliable and valid Diverse places well represented Random samples stratified by urbanity: megalopolises, small cities & rural places Respectively, 300 & 1,950 women (multi-”controls”) Comparably poor places defined by Census Bureaus CT household poverty prevalence of 30-40+% (US) Poorest CTs on Stats Can’s low-income criterion Mdn incomes, purchasing power-adjusted in USD: $23,175 (California) & $23,800 (Ontario)
Practical Statistical Analyses Early diagnosis, treatment & survival rates Directly age-adjusted (other confounds) Study sample was the internal standard Rates per 100 participants or percentages Standardized rate ratio (RR) comparisons with (95% CIs) Mathematical models adjusted for multiple predictive and potentially confounding factors Logistic regressions (diagnosis & treatment) Cox hazards regression (survival) Notes Notes. Key study variables had less than 3% missing data which was not confounding. Covariates: disease stage at diagnosis, tumor grade, tumor size and hormone receptor status.
Node Negative Breast Cancer at Diagnosis? Places (People) Adjusted Rates (%) Ontario (All)65.0 California (All)61.5 RR = 1.06 (0.96, 1.17) Ontario (All)65.0 CA (Uninsured or Publicly)57.9 RR = 1.12 (1.01, 1.24)
Received Cancer-Directed Surgery? Places (People) Adjusted Rates (%) Ontario (All)96.6 California (All)94.3 RR = 1.02 (0.99, 1.05) Ontario (All)96.6 CA (Uninsured or Medicaid)93.2 RR = 1.04 (1.00, 1.08)
Received Breast Conserving Surgery? Places (People) † Adjusted Rates (%) Ontario (All)73.5 California (All)49.6 RR = 1.48 (1.31, 1.68) † † Among women with node negative disease.
Received Radiation Therapy? Places (People) † Adjusted Rates (%) Ontario (All)70.6 California (All)66.4 RR = 1.06 (0.98, 1.14) Ontario (All)70.6 CA (Uninsured or Publicly)60.6 RR = 1.17 (1.01, 1.35) † † Among women with node negative disease who had breast conserving surgery.
Experienced Long Waits for Care? Places (People) † Adjusted Rates (%) Waited > 2 Months for Surgery Ontario (All)7.2 CA (Uninsured or Medicaid)12.4 RR = 0.58 (0.36, 0.93) Waited > 6 Months for Radiation Therapy Ontario (All)6.2 CA (Uninsured or Medicaid)14.2 RR = 0.44 (90% CI: 0.20, 0.96) † † Among women with non-metastasized disease.
Received “Optimum” † Care? Places (People) ‡ Adjusted Rates (%) Ontario (All)64.0 California (All)47.4 RR = 1.35 (90% CI: 1.03, 1.77) Ontario (All)64.0 CA (Uninsured or Publicly)43.1 RR = 1.48 (1.13, 1.94) (CA Uninsured)RR = 1.89 (1.31, 2.72) † † Received breast conserving surgery within 2 months of diagnosis and received adjuvant radiation therapy within 4 months of surgery. ‡ ‡ Women with node negative disease & low to intermediate grade tumors.
Received Hormone Therapy? Places (People) † Adjusted Rates (%) Ontario (All)68.2 California (All)41.2 RR = 1.65 (1.44, 1.89) Ontario (All)68.2 CA (Uninsured or Publicly)38.3 RR = 1.78 (1.53, 2.07) † † Women with hormone receptor positive tumors.
Survived? We ran a number of age, stage and grade adjusted regressions on 3- to 10-year survival. Canadian women were advantaged in each: Pooled RR = 1.60 (1.26, 2.02) In each instance, when health insurance entered the model country was no longer significant: Pooled RR = 1.07 (0.94, 1.19)
Summary Women living with breast cancer in high poverty neighborhoods received better care in Ontario than in California. Such access mattered in terms of their better short- and long-term survival chances. In the pre-Obamacare era that included a number of treatment innovations and increasingly effective breast cancer care, extremely poor women in Ontario gained access to them much more readily than did their counterparts in California.
Interpretations Estimated inequities among women with breast cancer living in poverty in America over the past generation Estimated inequities among women with breast cancer living in poverty in America over the past generation: 53,000 late diagnoses 158,000 sub-optimum treatments 172,000 premature deaths Breast cancer accounts < 2% of US’s disease burden US Women Compared to Canadian women US Women Compared to Canadian women: Uninsured most consistently vulnerable Medicaid insured nearly as vulnerable Significant vulnerabilities among Medicare insured Even certain privately insured were vulnerable
Interpretations Language of American health care: Platinum, gold, silver and bronze private coverages “Medigap” coverages are needed for Medicare covered Cost-sharing among the poor, covered by Medicaid? Seems an acceptance, not only of a multi-payer system, but of a multi-quality and multi-outcome system that destines many to relatively low quality care with its attendant greater risks of suffering & early death. ACA/Obamacare Changes ACA/Obamacare Changes: Tens of millions more Americans will be insured Majority new private plans bronze or silver, high deductibles Many states have not yet expanded Medicaid and considering various, out-of-pocket, cost-sharing measures Many previously uninsured may become underinsured
Conclusions The ACA will probably substantially reduce such observed inequities. But single-payer reform would probably further reduce, if not completely eliminate them. To the extent that such is not politically feasible, advocates ought to work to ensure that the ACA is enacted across all 50 states in ways that are consistent with its federal legislative intent, that is, that high quality health care be truly available to all.
Potential Limitations 1. Race/Ethnicity Alternative Explanation Findings replicated among the subsample of non-Hispanic white women in California vs. the entire ethnically diverse Ontario sample 2.Income Differences (US Poor are Poorer on average than Canadian Poor) Findings replicated among California-Ontario subsamples with nearly identically low incomes Even granting this: It is instructive to know that women who live in Canada’s poorest neighborhoods are so much better insured than women who live in America’s poorest neighborhoods.
Co-Investigators InvestigatorAffiliation__________ Kevin GoreySchool of Social Work Nancy RichterUniversity of Windsor Madhan Balagurusamy Isaac LuginaahDepartment of Geography GuangYong ZouDept. of Epidemiol & Biostats Caroline Hamm † Department of Oncology University of Western Ontario Eric HolowatySchool of Public Health University of Toronto † & Medical Oncology Department, Windsor Regional Cancer Center
Acknowledged Administrative, Logistical or Research Support SupporterAffiliation__________ Kurt SnipesCancer Surveillance and Janet BatesResearch Branch, California Gretchen AghaDepartment of Public Health Mark AllenCalifornia Cancer Registry Allyn Fernandez-Ami Arti Parikh-Patel Sundus Haji-JamaSchool of Social Work University of Windsor Charles SagoeCancer Care Ontario
Disclaimer Other Agencies Involved in Data Management: National Cancer Institute (United States), Cancer Prevention and Public Health Institutes of California, Centers for Disease Control and Prevention, University of Southern California, and the Canadian Institute for Health Information The ideas and opinions expressed herein are those of the presenters and endorsement by any affiliated or data-supportive agencies or their contractors and subcontractors are not intended nor should they be inferred.
Principal Investigator Kevin Gorey For more information about our research see my academic website at: www.uwindsor.ca/gorey For any additional information, including reprint requests, feel free to contact me at: firstname.lastname@example.org