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!

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