This study compared breast cancer care among socioeconomically vulnerable women in pre-Affordable Care Act California and Ontario. It found that Canadian women living in high poverty neighborhoods or areas lacking specialist physicians received better care, likely due to their greater health insurance coverage and access to primary care physicians. The study recommends strengthening primary care and expanding health insurance in the US to maximize benefits for vulnerable groups similar to protections provided in Canada.

1. Breast Cancer amongBreast Cancer among
Socioeconomically VulnerableSocioeconomically Vulnerable
Women in Vulnerable PlacesWomen in Vulnerable Places
Historical Evidence of Better Care
in Canada than in the United States

2. Presenter DisclosuresPresenter Disclosures
No relationships to disclose
Funding source:
Canadian Institutes of Health Research
Grant no. 67161-2
Manuscript status:
In review for publication consideration in
a peer-reviewed scientific journal

3. AbstractAbstract
We studied the effects of poverty, health insurance and primary care
(PC) on optimum breast cancer care†
among women in pre-
Affordable Care Act (ACA) California and Ontario.
Canadian advantages in the most disadvantaged places: high poverty
neighborhoods (RR = 1.65) and communities that lacked
specialist physicians (RR = 1.33) were explained by better health
insurance coverage and greater access to PC physicians (PCP).
These protective Canadian effects suggested ways to maximize ACA
protections. Ensure the newly insured, public and private, are
adequately insured, without having to bare exorbitant out-of-
pocket costs. Expand Medicaid across all 50 states. Bolster the
supply of PCPs and allied professionals.
†
Optimum care: diagnosed early (small, node negative tumor) and received breast
conserving surgery (lumpectomy) followed by radiation therapy

4. BackgroundBackground

5. Human, Clinical & Scientific ContextsHuman, Clinical & Scientific Contexts
Why study breast cancer?
• Relatively common over the life course
• Effective screens exist
• Effective treatment regimes exist
• Timely diagnoses & best treatments
matter
• Excellent prognoses can be expected:
Long survival & high quality of life
It is a sentinel health care quality indicator.

6. Income and Breast Cancer CareIncome and Breast Cancer Care††
††
Systematic review and meta-analysis of 100+ study outcomesSystematic review and meta-analysis of 100+ study outcomes
• US-Canada studies that did not account for income
found nil to null differences on breast cancer care
• “Comparisons of national ‘haystacks’ tend to lose
important ‘needles’ of knowledge”
• Studies of breast cancer care in impoverished places in
the US and Canada found large Canadian advantages in
diagnosis, treatment and survival
• The more impoverished the people and places the
larger have been the Canadian advantages
• Focusing on the experiences of the most vulnerable
magnifies clinical, policy and human significance
Knowledge gap:
• Better health insurance coverage accounted for
most, but not all, of observed Canadian advantages

7. Primary Care and MortalityPrimary Care and Mortality††
††
Review of 35 national/US analyses (cancer, heart disease & all-cause mortality)Review of 35 national/US analyses (cancer, heart disease & all-cause mortality)
• Barbara Starfield, the late, preeminent PC researcher and
advocate commented that “insurance is necessary, but
not sufficient” to explain these advantages—“Canada’s
more PC-orientation probably also plays a significant
protective role.”
• PCPs are much more prevalent among the Canadian
vs. US physician workforces (47% vs. 27%)
• PCP supply-mortality associations were consistently
and strongly protective (28 of 35 study outcomes)
Knowledge gap:
• We are not aware of any US-Canada study of breast
cancer care that observed the effects of poverty, health
insurance and physician supplies, PCPs and specialists.

8. Study HypothesesStudy Hypotheses
1. Poverty better predicts suboptimum breast cancer
care in the United States.
2. Primary care physician supply better predicts
optimum care in Canada.
3. The hypothesized Canadian advantage among
women who lived in poverty would be completely
explained by their better health insurance
coverage and greater access to primary care.

9. MethodsMethods
Comparison of Pre-ACA Historical Cohorts:
High Poverty Neighborhoods Oversampled in
California and Ontario,
Women with Breast Cancer Diagnosed
Between 1996 & 2000 Followed to 2011

10. Sampling High Poverty NeighborhoodsSampling High Poverty Neighborhoods
Enhanced California and Ontario cancer registries
• Comprehensive, reliable and valid
• Diverse places well represented
Random samples stratified by poverty: > 30% & < 30% poor
• Respectively, 6,300 & 950 women (multi-“controls”)
Comparably poor places defined by Census Bureaus
• CT poverty prevalence of 30+% (US, 2000)
• Poorest CTs, Stats Can’s low-income criterion (2001)
• Mdn incomes, purchasing power-adjusted in USD:
$23,175 (California) & $23,800 (Ontario)
Note. CT = census tract, Mdn = median, Stats Can = Statistics Canada, USD = US dollar

11. Measuring Community PCP SupplyMeasuring Community PCP Supply
Participants joined to county-level active physician data
• AMA and CIHI databases (2000/2001)
• The threshold effect, above which participants were
more likely to receive optimum care, was identified
by exploring increments (0.25 physicians /
10,000):
> 7 PCPs per 10,000 community inhabitants
• PCPs reported specialty as general or family practice
• General internists in the US and emergency family
medicine physicians in Canada were also included
Note. AMA = American Medical Association, CIHI = Canadian Institute for Health
Information

12. Practical Statistical AnalysesPractical Statistical Analyses
Optimum care: diagnosed early, had lumpectomy & RT
(NCCN guideline-based). Clinically valid: those not
3-times more likely to have died over 10 years
• Rates were directly and internally adjusted for age
and place: large or small urban or rural
• Rates reported per 100 participants (percentages)
Standardized rate ratio (RR) comparisons with (95% CIs)
Logistic (care) or Cox (survival) regression models
adjusted for multiple predictive and potentially
confounding factors
NotesNotes. CI = confidence interval, NCCN = National Comprehensive Cancer Network,
RT = radiation therapy. Key study variables had < 3% missing data which was not
confounding. Covariates: age, place, tumor grade and hormone receptor status.

13. ResultsResults

14. Effect of Neighborhood Poverty on RateEffect of Neighborhood Poverty on Rate
of Optimum Breast Cancer Careof Optimum Breast Cancer Care
Within-CountryWithin-Country Adjusted Rates (%)Adjusted Rates (%)
California
Lower poverty
33.6
High poverty (30+% poor)23.1
RR = 0.69 (0.63,
0.75)
Ontario
Lower poverty
34.8
High poverty
38.1
RR = 1.09 (0.92,
1.30)
Between-Canada/US within High Poverty Neighborhoods

15. Effect of Community PCP Density onEffect of Community PCP Density on
Rate of Optimum Breast Cancer CareRate of Optimum Breast Cancer Care
Within-CountryWithin-Country Adjusted Rates (%)Adjusted Rates (%)
California
Lower PCP density29.2
High PCP density (7+ PCPs/10,000)31.2
RR = 1.07
(1.00, 1.14)
Ontario
Lower PCP density29.9
High PCP density
42.9
RR = 1.43
(1.20, 1.70)
Between-Can/US within High PCP Density CommunitiesBetween-Can/US within High PCP Density Communities

16. Health Insurance & PC Explained Breast Cancer Care &Health Insurance & PC Explained Breast Cancer Care &
Ultimately Survival Differences Between-CountriesUltimately Survival Differences Between-Countries
When the main and interacting effects of
poverty, PCP supply and country were
accounted for with a logistic regression there
was no main effect of country on optimum care.
When the main and interacting effects of poverty,
health insurance, PCP supply, optimum care
and country were accounted for with a Cox
regression there was no main effect of country
on survival.

17. Specialist Physician (SP) Density &Specialist Physician (SP) Density &
Optimum Breast Cancer Care: AddendumOptimum Breast Cancer Care: Addendum
Within-CountryWithin-Country Adjusted Rates (%)Adjusted Rates (%)
California (CA)
Lower SP density (< 13 SPs/10,000)25.8
High SP density (72.5%)
32.4
RR = 1.26 (1.15,
1.38)
Ontario (ON)
Lower SP density
34.2
High SP density (18.8%)
36.0
RR = 1.05 (0.88,
1.25)
††

18. DiscussionDiscussion

19. SummarySummary
All three study hypotheses were supported.
In addition to more prevalent optimum care in
communities that were well supplied and served by
PCPs, women with breast cancer in Ontario were
particularly advantaged in the most disadvantaged
places: high poverty neighborhoods and underserved
communities that lacked specialist physicians.
Canadian advantages in care and survival among those
who lived in poverty were fully explained by their
better health insurance coverage and greater access
to primary care.

20. Interpretation: Human SignificanceInterpretation: Human Significance
Applying this study’s effects to US
population parameters on breast cancer
among the inadequately insured and
impoverished we estimate that over the
course of a generation more than 200,000
American women who lived in poverty
with breast cancer were cared for less
optimally than had they had access to a
universally accessible, primary care-
oriented health care system.

21. ConclusionsConclusions
This study’s historical observations of Canadian health care
protections suggested ways to maximize ACA protections.
Policy makers ought to ensure that the newly insured, whether
through private insurance exchanges or public insurance
expansions, are indeed, adequately insured. No one should have
to bare exorbitant out-of-pocket costs for medically necessary
cancer care or any other, and the Medicaid program should be
equitably expanded across all 50 states.
In concert with ultimately insuring all Americans, policies that expand
the supply of PCPs hold the promise of eradicating remaining
barriers to the provision of high quality health care for all.

22. Policy RecommendationsPolicy Recommendations
The United States ought to institute
single payer reform and strengthen its
primary care system.
To the extent that single payer reform is
not politically feasible, strengthening
primary care is probably the best way
to maximize the ACA’s benefits.

23. Potential LimitationsPotential Limitations
1.1. Race/Ethnicity Alternative ExplanationRace/Ethnicity Alternative Explanation
• Findings replicated among the subsample of non-Hispanic
white women in California vs. the entire ethnically diverse
Ontario sample
2.2. Income Differences (US poor are poorer on average thanIncome Differences (US poor are poorer on average than
Canadian poor)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 and cared for than women who live in
America’s poorest neighborhoods.

24. Future ResearchFuture Research
To optimize breast cancer care with an adequate PC workforce of
at least 7 PCPs per 10,000 community residents we estimated
that another 1,700 PCPs are needed in California. Though PC
was more effective in Ontario, a PCP supply gap of 325 PCPs
was estimated there as well.
Systematic replications are needed to identify current evidence-
based gaps in PC across other states, provinces and health
outcomes.
Social workers work with PCPs and others, often leading primary
care efforts in diverse health and mental health field’s of
practice. This study allowed for observation of the role of PCPs
(availability of administrative data), but not of social workers.
Future studies ought to incorporate the value of social work
roles and their protective effects.

25. Co-InvestigatorsCo-Investigators
Investigator Affiliation __________
Kevin Gorey School of Social Work, University of
Windsor, Ontario, Canada
Caroline Hamm†
Department of Oncology
Isaac Luginaah Department of Geography
Guangyong Zou‡
Dept. Epidemiology & Biostatistics
Western University, London, ON
Eric Holowaty Dalla Lana School of Public Health
University of Toronto, Ontario
†
& Oncology Department, Windsor Regional Cancer Center, Ontario
‡
& Robarts Research Institute, London, Ontario

26. Acknowledged Administrative,Acknowledged Administrative,
Logistical or Research SupportLogistical or Research Support
Supporter Affiliation _________________
Kurt Snipes Cancer Surveillance and Research
Janet Bates Branch, California Department of
Gretchen Agha Public Health
Dee West Cancer Registry of Greater California
Marti Induni
Glen Halvorson
Donald Fung
Arti Parikh-Patel
Madhan Balagurusamy School of Social Work
Nancy Richter University of Windsor
Charles Sagoe Cancer Care Ontario
John David Stanway Canadian Institute for Health
Information

27. DisclaimerDisclaimer
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
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.

28. Principal InvestigatorPrincipal Investigator
Kevin GoreyKevin 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:
gorey@uwindsor.ca