LEADING INNOVATION IN RESEARCH
- IN THE NEWS : IBM Watson on Social Determinants of Health
- ADVANCING KNOWLEDGE: New Scientific Publications from Mid-South TCC
- STUDIES
- RESOURCES: 2016 Boyer Lectures by Professor Sir Michael Marmot
- COMING SOON: American Journal of Preventive Medicine - Social Determinants of Health
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IN THE NEWS
IBM's Watson: Using Big Data to Address the Social Determinants of Health
In the past, healthcare organizations could write off Social Determinants of Health (SDH) as outside their scope of medical practice. Today, however, that's no longer the case. As the healthcare industry moves toward value-based care, and more hospitals and clinicians assume financial risk for their services, they're realizing that addressing certain aspects of SDH can help mitigate challenges that impede the ability of individuals to manage their health, and, by extension, improve population health outcomes.
The resulting imperative for many healthcare organizations: Create a model bolstered by new sources of data to enhance the ability of care teams to understand and alleviate social care barriers their patients face.
How Data Can Help
That's easier said than done, of course-especially when you consider the unique needs of each person. The social services that are applicable to one individual may look nothing like those required by the next.
So what's the solution? It begins with the collection of an individual person's data. If your goal is to assemble the data needed to care for the whole person, you must start with the data you already have at your fingertips, whether it's clinical, social-behavioral, or functional in nature. That information might include:
- structured and unstructured data from the electronic health record (EHR)
- data collected from questionnaires and health risk assessment forms
- household income data from welfare and food stamp programs
- data from health, disability, and unemployment insurance records
- details on a person's place of residence and living situation
- geographical information like the distance from a person's home to the nearest primary care clinic or grocery store
Once you've incorporated the relevant data, you can parse it using specialized analytic tools-employing risk stratification to identify individuals who require additional resources to manage their health, such as transportation, housing, child care and food, or referrals to behavioral health specialists.
The key, is to find and utilize SDH data in the same way you might use clinical information to determine if a person has a certain condition.
Make that job easier by leveraging technology to turn unstructured data (like that found in case reports) into actionable information. Aggregate a person's SDH data-and then use it to empower care teams that meet the population's personal needs-and your organization will be ready to anticipate what individuals may need even before they present for help.
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ADVANCING KNOWLEDGE
NEW Scientific Publications from the Mid-South TCC
The Mid-South Transdisciplinary Collaborative Center (U54MD008176) advances knowledge that will reduce the disparities in chronic diseases experienced by vulnerable populations in the Mid-South by addressing the social determinants that impact a person's health and produce disparate health outcomes. The Center focuses on pathways to obesity and chronic illness and the mechanisms connecting these pathways to health disparities throughout the life-course.
The following NEW scientific publications resulted from the preliminary work of the center:
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Mona Fouad, MD, MPH Gabriela Oates, PhD Lori Bateman, PhD Karan Singh, PhD
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Irena Stepanikova, Gabriela R. Oates
Perceived discrimination is an important risk factor for minority health. Drawing from the scholarship on multidimensionality of race, this study examines the relationships between perceived discrimination in health care and two dimensions of racial identity: self-identified race/ethnicity and perceived attributed race/ ethnicity (respondents' perceptions of how they are racially classified by others).
Conclusion:
Perceived attributed race/ ethnicity captures an aspect of racial/ethnic identity that is correlated, but not interchangeable, with self-identified race/ethnicity and contributes uniquely to perceived discrimination in health care. Applying the concept of multidimensionality of race/ ethnicity to health disparities research may reveal understudied mechanisms linking race/ethnicity to health risks.
Ethn Dis. 2016;26(4):501-512; doi:10.18865/ ed.26.4.501
Irena Stepanikova, Gabriela R. Oates, Lori Bateman
This study investigates the associations of body mass index (BMI) and waist circumference (WC) with markers of systemic inflammation in midlife by race and gender.
Conclusions:
WC shows more consistent associations with inflammation markers than BMI, although the relationships vary by inflammation marker and population group. Our findings suggest that WC is a risk factor for systemic inflammation among White and Black men and women, and BMI is an additional risk factor for Black men.
Tabatabai MA, Kengwoung-Keumo JJ, Oates GR, Guemmegne JT, Akinlawon A, Ekadi G, Fouad MN, Singh KP.
Certain population groups in the United States carry a disproportionate burden of cancer. This work models and analyzes the dynamics of lung and bronchus cancer age-adjusted incidence rates by race (White and Black), gender (male and female), and prevalence of daily smoking in 38 U.S. states, the District of Columbia, and across eight U.S. geographic regions from 1999 to 2012.
Conclusion:
Although age-adjusted incidence rates in lung cancer have decreased throughout the U.S., racial and gender disparities remain. This longitudinal model can help health professionals and policy makers make predictions of age-adjusted incidence rates for lung cancer in the U.S. in the next five to ten years.
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STUDIES
Over the next decade, leading researchers in the fields of child development and neuroscience will use extensive baseline interviews, psychological and behavioral testing, and cutting-edge technology in brain imaging, to determine how childhood experiences interact with a child's changing biology to affect brain development and-ultimately-social, behavioral, academic, and other health outcomes. Experiences such as playing video games, participating in extracurricular activities like organized sports, insufficient sleep or poor sleep habits, cigarette smoking, other use of tobacco products, and drinking alcohol. For example, we know that adequate hours of sleep is essential for normal growth and brain development, yet studies show that children from minority and economically underserved communities are more likely to experience shorter sleep times compared to their White and economically advantaged counterparts. As a result, these children are disproportionately affected by the adverse health and quality of life consequences of poor sleep.
At this workshop, participants explored public health approaches to reducing and preventing community violence. Individual participants discussed the effects of trauma and violence on communities and explored approaches that community members and multisector partners are using to build safe, resilient, and healthy communities. Individual participants discussed a range of initiatives including community- and hospital-based antiviolence programs, changing the physical and social environment, community policing, and different strategies to include community members in these initiatives, particularly the youth and adults at risk or responsible for much of the violence in communities. This Proceedings of a Workshop-in Brief summarizes discussions from the workshop.
Souce: National Academies of Sciences
The relationship between low income and worse health outcomes is evident, yet its association with cognitive outcomes is less explored. Most studies have measured income at one time and none have examined how sustained exposure to low income influences cognition in a relatively young cohort. This study examined the effect of sustained poverty and perceived financial difficulty on cognitive function in midlife.
Conclusions
Cumulative exposure to low income over 2 decades was strongly associated with worse cognitive function of a relatively young cohort. Poverty and perceived hardship may be important contributors to premature aging among disadvantaged populations.
Researchers at the National Institutes of Health have discovered a two-way link between depression and gestational diabetes. Women who reported feeling depressed during the first two trimesters of pregnancy were nearly twice as likely to develop gestational diabetes, according to an analysis of pregnancy records. Conversely, a separate analysis found that women who developed gestational diabetes were more likely to report postpartum depression six weeks after giving birth, compared to a similar group of women who did not develop gestational diabetes.
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RESOURCES
2016 Boyer Lectures by Professor Sir Michael Marmot
Sir Michael is the President of the World Medical Association, Director of the Institute of Health Equity and a leading researcher on health inequality issues for more than three decades playing a central role in research projects studying health equity.
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MID-SOUTH TRANSDISCIPLINARY COLLABORATIVE CENTER FOR HEALTH DISPARITIES RESEARCH
1717 11th Avenue South, Medical Towers 516 I Birmingham, AL 35294-4410, USA
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