Tending To The Social Determinants Of Health – Or Not

Executive Briefing | by | February 25, 2016


Sarah C. Threnhauser, MPA
Sarah C. Threnhauser, MPA

The issue of addressing the social determinants of health – employment and economic stability, housing, nutrition, and neighborhood context – is getting more traction. Last year, at The 2015 OPEN MINDS Performance Management Institute, Arthur C. Evans, Jr., Ph.D., Commissioner of the Philadelphia Department of Behavioral Health & Intellectual disAbility Services, spoke of Philadelphia’s program to address the social determinants of health (see Improving Population Health Management With Public Health Approaches). And at this year’s institute, Magellan Complete Care of Florida Chief Executive Officer, Kerry McDonald, mentioned that Magellan is paying for housing for its members with severe behavioral disorders (see Moving A Capitated System From Implementation To Operation: A Town Hall Discussion). These are just a few of the many initiatives that are addressing this issue (for more, check out Social Determinants Of Health & Medical Homes and Social Determinants Of Health – How Housing & Other Social Support Services Influence Spending).

This focus is not coming a moment too soon. For the first time, mortality rates for the middle-aged white population is going up – purportedly due to addiction and violence (see Increase In Mortality Among Middle-Aged White Americans Due To Suicide & Substance Abuse). Earlier this month, The New York Times reported on how these biopsychosocial factors are having a disproportionate effect on the health status of the poor – and the gap is continuing the widen (see Disparity In Life Spans Of The Rich & The Poor Is Growing). The article notes that about 40 years ago, as the income gap began to widen, the gap between the life spans of high-income and low-income Americans began to widen as well. For men born in 1920, there was a life expectancy gap of six years between the top 10% of earners and the lowest 10% of earners; among women, the gap was 4.7 years. New analysis shows that for men born in 1950, there is a life expectancy gap of 14 years between the top 10% of earners and the lowest 10% of earners; among women, the gap is now 13 years. What is causing these disparities? Researchers attribute most of this gap to lifestyle factors, including factors such as smoking, obesity, and prescription drug abuse.

The discussion of the social determinants are important in a health and human service system where payers want to connect reimbursements with “outcomes.” Currently, most performance measures do not take into account any of these factors when setting penalties or reimbursement rates tied to quality. For example, the Centers for Medicare and Medicaid Services (CMS) Hospital Readmission Reduction Program is risk adjusted for severity of illness and demographic factors, like age and sex – but not any social determinants of health (see Half Of U.S. Hospitals Face Medicare Readmission Penalties).

But a recent analysis, Socioeconomic Status And Readmissions: Evidence From An Urban Teaching Hospital, found that patients living in high-poverty neighborhoods were 24% more likely than others to be readmitted, after demographic characteristics and clinical conditions were adjusted for. And, this week a study published in JAMA Pediatrics, Association of Social Determinants With Children’s Hospitals’ Preventable Readmissions Performance, tackled this important question. The study’s authors wanted to determine if risk adjusting for social determinants of health would affect readmission performance measures. The authors looked at 179,400 discharges from 43 free-standing children’s hospitals that were tracking 15-day and 30-day readmissions. After risk adjusting the data for severity of illness, as well as social determinants of health variables (race, ethnicity, payer, and median household income for the patient’s home zip code), the study found that readmission penalty status changed for three hospitals (7%) for 15-day readmissions and five hospitals (11.6%) for 30-day readmissions. The authors concluded that without risk adjusting for the social determinants of health, hospitals may be receiving penalties for issues that are beyond the quality of care given to consumers.

Also this month, the Missouri Hospital Association released a readmission dataset that applied a socio-demographic risk adjustment to readmission rates across all hospitals (see Risk Adjustment for Sociodemographic Status in 30-Day Hospital Readmissions). The report found that when risk adjusting for socio-demographic factors, the variation in quality among hospitals was minimized – with between 43% and 88% of the variation among hospital quality accounted for by consumer’s Medicaid status and other community factors (see It’s Time To Add Socio-Demographic Factors When Weighing Quality Performance).

So what does this mean for managers of health plans and provider organizations who are increasingly involved in contractual relationships focused on outcomes? First, know your consumers in a quantitative sort of way (the way Amazon knows you). It’s hard to argue that the current performance-based reimbursement model is deficient if you don’t have the data to discuss the characteristics of your consumer population. Second, be able to tie consumer demographics to your decision support algorithms and your outcomes. Third, invest in better formal systems for referring to and collaborating with social service organizations that can improve the health outcomes of the consumers you serve.

For more, check out these resources from the OPEN MINDS Industry Library:

  1. Majority of Physicians Cite Poor Health Outcomes Due To Lack of Social Supports
  2. A Question Of Permanent Supportive Housing
  3. The Social Service Factor In The Health Care Value Equation
  4. Social Determinants Of Health & Medical Homes
  5. Social Determinants Of Health – How Housing & Other Social Support Services Influence Spending

To ignore the link of consumer health and consumer health outcomes to social determinants of health is a fundamental error in the emerging value-based landscape.


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