February 3-5, 2016 | Lansdowne Resort, Leesburg, VA
Is Current and Future Science
Widening the Gap in Health Disparities?
Amelie G. Ramirez, DrPHDirector, Institute for Health Promotion Research
Associate Director for Cancer Prevention and Health
Disparities, Cancer Therapy & Research Center
The UT Health Science Center at San Antonio
1971Nixon’s “War on Cancer”
Trending up?
2015Obama’s “Moonshot to Cure Cancer”
Cancer knowledge =
Targeted therapy =
Clinical trials =
Gene sequencing =
Advances in big data =
Immunotherapy =
National tumor
genome database =
But where does this leave health disparities? = ↔
Why are minorities being left behind?
Minorities face barriers in accessing quality care:
Insurance / immigrant status / work issues
Co-morbidities
System problems
Transportation
Lack of knowledge of healthcare system
Cultural barriers (language, acculturation)
Less likely to be screened
for cancer
More likely to be treated
at lower-quality hospitals
or hospitals with large
minority and Medicare
populations
References: NCI, 2016; Keating et al, 2016; Mojica et al 2015; Braschi et al, 2014;
Bensink et al, 2014; Jadav et al, 2015; Katz et al, 2014; Hacker et al, 2014
Why are minorities being left behind?
Only 5% of clinical trial enrollees are minority (2.2% Latino)
Most research data are extracted from uniform study populations of
comprised largely of white men
Most clinical trials are run by large medical centers, not the small community
hospitals where many people, including minorities, receive treatment
Precision medicine requires participation and inclusion of a diverse patient
population—not just those who can afford and readily access care
References: Carpenter et al, 2012; Nishi et al, 2016; London et al, 2015
Why are minorities being left behind?
Fewer minorities get genetic testing (only 4% of Latinas for BC)
Genetic heterogeneity exists between/among population groups (Dean identified
6 genetic mutations among Latinas, only one had been reported in literature)
Women with higher incomes = significantly more likely to get genetic profiling,
even w/ same insurance coverage as those with lower incomes
Even with genetic testing / profiling, targeted therapy may be too expensive
ACA helps, but even reducing cost-sharing by 25% (closing of “doughnut hole”
by 2020), those on Medicare w/o low-income subsidies may still spend $10K out
of pocket, negatively affecting adherence to oral cancer drugs
Refs: Al-Alem et al, 2014; Dean et al, 2015; Rangel et al, 2014; Moyer, 2014; Chalela
et al, 2012; Ponce et al, 2015; Lee et al, 2015; Dusetzina et al, 2016; Piana et al, 2014
Why are minorities being left behind?
Underinvestment in prevention
Money spent on genetic or genome-focused
research was 50% greater than that spent on
research areas that included the word
“prevention” in 2014
The gap in cancer health disparities will not be
closed when so much more money and attention
is invested in individual treatment rather than
public health and disease prevention
References: Bayer et al, 2015; Goozner, 2016; Lopes, 2015
Why are minorities being left behind?
BIG DATA can exclude minorities
Jonas Lerman’s “data subordination”
“Billions of people worldwide remain on Big Data’s
periphery. Their information is not regularly
collected or analyzed, because they do not routinely
engage in activities that Big Data is designed to
capture. Consequently, their preferences and needs
risk being routinely ignored when governments and
private industry use big data and advanced analytics
to shape public policy and the marketplace”
References: Delaware Online, 2015 (delonline.us/1UGtePi)
What’s working right now?
Important strategies include:
Patient navigation (culturally competent, can reduce
screening/knowledge barriers)
NCI community network programs
Practice-based research networks to make clinical trial
enrollment more accessible; one boosted enrollment
from 5.4% to 10.2%
Multilevel interventions/studies
References: Braun et al, 2015; Ko et al, 2014; Carpenter et al, 2012; Vicini et al, 2011
Emerging solution: Drug parity laws
36 states have enacted drug parity laws (as of 8/2015) to relieve
out-of-pocket expenses for oral chemotherapy agents
However, extent of laws’ benefits is unclear; concern over increased insurance
premiums and prior-authorization that creates additional barriers to access
Cancer Drug Coverage Parity Act →
Introduced into House and Senate in 2015
Would require private insurance plans with IV
chemotherapy benefits to provide parity for oral and
self-injectable anticancer drugs
References: Kircher et al, 2016; ASCO, 2015
Emerging solution: Big Data as “Human-Centered”
“Big Data is created by or derived from human activities,
communications, movements, and behaviors.”
– Dr. Ming-Hsiang Tsou, Center for Human Dynamics in the Mobile Age, SDSU
Big data should refer to big ideas, big impacts, and big changes
for our society rather than only focusing on big volume
Social life data, health data (EMR, cancer registries, outbreak tracking), scientific
research data, business/commercial data, GPS transportation/traffic data
Analysis requires multidisciplinary collaboration
References: Webinar, 2015 (bit.ly/1PSpaxl)
Emerging solution: Big Data as “Disparities-Focused”
“The next big step is using the acquired knowledge to build
even more knowledge and applying what is learned… to find
better treatments, better prevention and better ways of getting
those better treatments and preventive interventions to people
who need them.” – Dr. Otis Brawley, CMO, American Cancer Society
NY acquiring data on LGBT community to provide better tailored public health services
In Cincinnati, collecting “race, ethnicity, and language” (REL) data is helping healthcare
providers identify disparities in care and create accountability
Camden (NJ) group is creating Social Determinants of Health Database (SDD) to
combine health + social data on vulnerable groups and care coordination
References: NY Times, 2016 (nyti.ms/1QEQ5tk); Huff Post, 2014 (huff.to/1u0OyoA);
Healthcare Informatics, 2014 (bit.ly/1qUi5zO); Health Affairs, 2015 (bit.ly/1MTsxAi);
Emerging solution: Big Data as “Mobile Friendly”
Mobile technology is seen as the great equalizer
84% of low-income adults have access to a mobile phone
Smartphones increasingly come equipped with sensors that monitor health-
related data (i.e., heart rate, steps, routes traveled, and user activity levels)
U-Mich gathering and analyzing large, diverse population health datasets by
leveraging emerging Big Data sources (social media sites, GPS-based data
from personal devices, and citizen-created maps)
Fair Food Network’s app advances mobile payment technology by processing
SNAP food assistance benefits more simply, affordably at farmers’ markets
References: Health Affairs Blog, 2015 (bit.ly/1MTsxAi); Michigan website, 2015
(bit.ly/1mazKSi)
Applying what we know: Big Data
Jonas Lerman, State Department Attorney, Visiting Scholar at
George Washington University Law School
In designing new public-safety and job-training programs, forecasting
future housing and transportation needs, and allocating funds for
schools and medical research … public institutions could be
required to consider, and perhaps work to mitigate, the
disparate impact that their use of Big Data may have on persons
who live outside or on the margins of government datasets.
References: Delaware Online, 2015 (delonline.us/1UGtePi)
Applying what we know: Representing diversity
Muin Khoury, Director of the Office of Public Health
Genomics, U.S. CDC
The U.S. needs to develop a national consortium of cohorts that
is truly representative of the diversity of the U.S. population.
NIH plans to build a national consortium of at least one million
Americans within the next five years that confronts this need.
References: Khoury, 2015; Khoury, 2015; Baker et al, 2015; NIH 2016
Applying what we know: Training providers on disparities
Susan Skochelak, Vice President for Medical Education,
American Medical Association (AMA)
Teaching physicians to think about disparities goes “hand in
glove” with implementing technology that can help address
them. (AMA medical students are analyzing big data sets to analyze
health trends better understand vulnerable patient populations and
address health disparities.)
References: Pittsburgh Post-Gazette, 2015 (bit.ly/1j3HGE0)
Applying what we know: Multifaceted approach
John Z. Ayanian, Director of the Institute for Healthcare
Policy and Innovation, University of Michigan
1. Provide insurance coverage and access to high-quality care for all Americans.
2. Promote a diverse health care workforce.
3. Deliver patient-centered care.
4. Maintain accurate, complete race and ethnicity data to monitor disparities in care.
5. Set measurable goals for improving quality of care, and ensure that goals are
achieved equitably for all racial and ethnic groups.
References: Harvard Business Review, 2015 (bit.ly/1YS2q25)
Call to action
Every scientific or technologic advance that you see, hear about, or
that you create: Ask yourself, how will this affect the disparate
populations who are on the fringes?
Incorporate health disparities
into every single thing you do!
References
Cancer health disparities. http://www.cancer.gov/aboutnci/organization/crchd/cancerhealthdisparitiesfactsheet. Accessed January 25, 2016.
Keating NL, Kouri EM, He Y, et al. Location isn't everything: proximity, hospital characteristics, choice of hospital, and disparities for breast cancer surgery patients. Health Serv
Res. 2016.
Mojica CM, Morales-Campos DY, Carmona CM, Ouyang Y, Liang Y. Breast, cervical, and colorectal cancer education and navigation: results of a community health worker
intervention. Health Promot Pract. 2015.
Braschi CD, Sly JR, Singh S, Villagra C, Jandorf L. Increased colonoscopy screening for Latino Americans through a patient navigation model: a randomized clinical trial. J Immigr
Minor Health. 2014;16(5):934-940.
Bensink ME, Ramsey SD, Battaglia T, et al. Costs and outcomes evaluation of patient navigation after abnormal cancer screening: evidence from the patint navigation res
Jadav S, Rajan SS, Abughosh S, Sansgiry SS. The role of socioeconomic status and health care access in breast cancer screening compliance among Hispanics. J Public Health Manag
Pract. 2015;21(5):467-476.
Katz ML, Young GS, Reiter PL, et al. Barriers reported among patients with breast and cervical abnormalities in the patient navigation research program: impact on timely care.
Womens Health Issues. 2014;24(1):e155-e162.
Hacker K, Anies M, Folb BL, Zallman L. Barriers to health care for undocumented immigrants: a literature review. Risk Manag Healthc Policy. 2015;8:175-183.earch program. Cancer.
2014;120:570-578.
Carpenter WR, Tyree S, Wu Y, et al. A surveillance system for monitoring, public reporting, and improving minority access to cancer clinical trials. Clinical Trials. 2012;9(4):426-435.
Nishi A, Milner DA, Giovannucci EL, et al. Integration of molecular pathology, epidemiology and social science for global precision medicine. Expert Rev Mol Diagn. 2016;16(1):11-
23.
London L, Hurtado-de-Mendoza A, Song M, Nagirimadugu A, Luta G, Sheppard VB. Motivators and barriers to Latinas' participation in clinical trials: the role of contextual
factors. Contemp Clin Trials. 2015;40:74-80.
Al-Alem U, Rauscher G, Shah E, et al. Association of genetic ancestry with breast cancer in ethnically diverse women from Chicago. PloS One. 2014;9(11):e112916.
Dean M, Boland J, Yeager M, et al. Addressing health disparities in Hispanic breast cancer: accurate and inexpensive sequencing of BRCA1 and BRCA2. GigaScience. 2015;4:50.
Rangel LBA, Taraba JL, Frei CR, Smith L, Rodriguez G, Kuhn JG. Pharmacogenomic diversity of tamoxifen metabolites and estrogen receptor genes in Hispanics and non-
Hispanic whites with breast cancer. Breast Cancer Res Treat. 2014;148(3):571-580.
Moyer VA. Risk assessment, genetic counseling, and genetic testing for BRCA-related breast cancer in women: U.S. preventive services task force recommendation statement. Ann
Intern Med. 2014;160:271-281.
Chalela P, Pagan JA, Su D, Munoz E, Ramirez A. Breast cancer genetic testing awareness, attitudes and intentions of Latinas living along the U.S.-Mexico border: a qualitative
study. J Community Med Health Educ. 2012;2:1-15.
References
Ponce NA, Ko M, Liang SY, et al. Early diffusion of gene expression profiling in breast cancer patients associated with areas of high income inequality. Health Aff (Millwood).
2015;34(4):609-615.
Lee JA, Roehrig CS, Duggan Butto E. Cancer cost trends in the United States: 1998 to 2012. Cancer. 2015. Accessed January 27, 2016.
Dusetzina SB, Keating NL. Mind the gap: why closing the doughnut hole is insufficient for increasing medicare beneficiary access to oral chemotherapy. J Clin Oncol.
2016;34(4):375-382.
Piana R. Cancer care under the affordable care act. 2014; http://www.ascopost.com/issues/june-25,-2014/cancer-care-under-the-affordable-care-act.aspx.
Bayer R, Galea S. Public health in the precision-medicine era. The New England journal of medicine. 2015;373(6):499-501.
Goozner M. Where should we point the cancer moonshot? 2016; http://www.modernhealthcare.com/article/20160116/MAGAZINE/301169881.
Lopes G. Investing in cancer prevention and control to reduce global economic burden. 2015; https://am.asco.org/investing-cancer-prevention-and-control-reduce-global-
economic-burden.
Braun KL, Stewart S, Bacquet C, et al. The national cancer institute's community networks program initiative to reduce cancer health disparities: outcomes and lessons learned. Prog
Community Health Partnersh. 2015;9(0):21-32.
Ko NY, Darnell JS, Calhoun E, et al. Can patient navigation improve receipt of recommended breast cancer care? Evidence from the national patient navigation research program.
J Clin Oncol. 2014;32:2758-2764.
Carpenter WR, Tyree S, Wu Y, et al. A surveillance system for monitoring, public reporting, and improving minority access to cancer clinical trials. Clinical Trials. 2012;9(4):426-435.
Vicini F, Nancarrow-Tull J, Shah C, et al. Increasing accrual in cancer clinical trials with a focus on minority enrollment. Cancer. 2011;117:4764-4771.
Kircher SM, Meeker CR, Nimeiri H, et al. The parity paradigm: can legislation help reduce the cost burden of oral anticancer medications? Value in Health. 2016;19(88-98).
ASCO policy brief: cancer drug coverage parity act of 2015 (H.R. 2739/S.1566).
Khoury MJ. The success of precision medicine requires a public health perspective. 2015; http://blogs.cdc.gov/genomics/2015/01/29/precision-medicine/. Khoury MJ.
When a country cannot be a cohort: challenges of implementing a large precision medicine cohort study in the United States. 2015;
http://blogs.cdc.gov/genomics/2015/03/23/when-a-country/. Accessed February 1, 2016.
Baker R, Boerwinkle E, Burke G, et al. Building a consortium of cohorts - cohort identification and participant recruitment. 2015;
https://www.nih.gov/sites/default/files/research-training/initiatives/pmi/building-consortium-cohorts.pdf.
Request for information: NIH precision medicine cohort - strategies to address community engagement and health disparities. National Institutes of Health.
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