Bridging the Gap Between Social
Determinants and Electronic Health
Records for Patient and Public Health
Robert A. Hahn, Ph.D., M.P.H.
Community Guide Branch
Division of Epidemiology, Analysis and Library
Sciences
CDC
Center for Surveillance, Epidemiology, and Laboratory Services (proposed)
Division of Epidemiology, Analysis, and Library Services (proposed)
2
Disclaimer
The findings and conclusions in this
presentation are those of the author and do
not necessarily represent the official position
of the Centers for Disease Control and
Prevention
2
Agenda
1.
2.
3.
What are social determinants?
Current limits to social determinant
intervention research.
Bridging the gap in two directions.
a. Social determinants to health records
b. Health records to social determinants
4. The common link: Residence
3
4
Social determinants of health
Upstream elements of a society’s organization
and process, such as education, housing,
transportation, occupation, the system of
justice, that causally affect the societal
distribution of disease and health. Social
determinants may affect health by distributing
risk and protective factors for disease and
injury, pathological agents and environments,
and resources for prevention and treatment.
4
5
Logic Model: Interventions to Address the Health of Disadvantaged
Populations for the Improvement of Health for All
Social Determinants of
Health
Underlying Social Forces
Societal Distribution of
Health Determinants
Political/Economic
Structure and
Process
Forms of Inequitable
Determinant Distribution
Racism
Sexism
Classism
Multiple forms of inequitable
distribution based on age,
disability, immigration status,
etc.
Physical environment and its
regulation
HABITAT: Neighborhood
Living Conditions
Opportunities for Learning &
Developing Capacity
Community Development &
Employment Opportunities
Public finance, taxation
Health-related Equity
Outcome
Health
Equity
System of justice
Public services (e.g.,
transportation, sanitation,
recreation, social services)
Health Promotion, Disease/
Injury Prevention/ Healthcare
Health
for All
Societal Divisions/
Organization/
StructureHierarchy/ Process
5
6
Goals for Social Determinant Data and
Research
1.
Short-term Improvement
of patient/community
health
Improve care of patient with EHR.
2. Improve community/public health with EHRgenerated information.
3. Etiological research, e.g., assessing poverty
or lack of education as causes of reduced
longevity.
Long-term Improvement
of population health
4. Monitoring trends in social determinants, e.g.,
changes in education achievement gaps by race
and income.
5. Evaluating social determinant interventions,
e.g., the effect of high school completion
programs on long term health outcomes.
7
Guide to Community Preventive Services
Reviews of Educational Interventions to
Promote Health Equity
Past 4 years, systematic reviews of educational
programs, e.g.:
Early childhood education
Full-day vs. half-day kindergarten
Out-of-school time academic programs
High school completion
School based health centers
Extended school day and year
Underlying question: Can social determinant
interventions be used to promote health equity?
8
Range of Variables Considered in
Reviews of Educational Interventions to
Promote Health Equity
 Intervention characteristics, e.g., contents, intensity, duration.
 Student participation, e.g., proportion enrollment, program
completion rate.
 Educational outcomes, e.g., standardized achievement tests,
levels of school completion, school grades.
 Quality of school, e.g., high school completion rates, average
test scores, teacher: student ratio or classroom size, hours of
instruction.
 School demographics, e.g., proportion minority, proportion
receiving free or reduced-price lunch, community.
WeightedHS
mean
OR = 1.72 Programs, by
Mean Adjusted Odds Ratio for General
Completion
Control
(95%CI 1.56, 1.90)
Percent
Completion
Gain Program Type
Rate
76.0
5.6
73.4
6.7
81.6
7.7
53.8
15.5
81.0
8.8
92.9
3.6
83.6
8.3
72.3
13.7
80.9
10.4
83.7
9.4
70.3
15.9
91.0
6.3
n = unique comparison pairs
k = number of samples
Wilson SJ, Tanner-Smith EE, Lipsey, MW, Steinka-Fry, K, Morrison, J. Dropout prevention and intervention programs: Effects on school
completion and dropout among school aged children and youth. Campbell Systematic Reviews 2011:8
9
0
Major Challenge in Educational
Intervention Reviews for Health Equity
Outcomes assessed are primarily
educational, e.g., changes in reading or math
achievement scores, or rates of high school
graduation, not health outcomes
To draw conclusions about health outcomes,
we have to:
 make assumptions about the education—health
link. Assumptions are frequently challenged and
difficult to prove.
 use evidence from other studies.
Linkage to heath outcomes would provide an
enormous advance in this research
1
Challenges of Linkage for this Committee:
From EHR to Social Determinants
 Inclusion of extensive set of social determinant
data in EHR is undesirable and unnecessary;
would be a large burden for health care system.
 Use LINKAGE. Linkage should be purpose-driven,
i.e., what are the goals, what question asked, what
to be achieved?
 Requires common, shared identifiers.
 Useful linkages may be either for the individual in
the record, e.g., years of school completed, or for
an aggregate associated with the individual, e.g.,
quality measures of the school, or the poverty level
in the census tract. (E.g., Krieger,
www.hsph.harvard.edu/thegeocodingproject/)
2
The Key Linkage Variable:
Poverty
Transportation
Residence
(Address/census
tract)
Employment
/Industry
Fiscal
resources
Justice
Housing/
Physical
environment
Education
Allows linkage to community resources (and
their absence), depending on data from
other sources.
3
The Residence Connection
Residence
Education
Extended
day/year
school time
Early
childhood
education
High school
completion
programs
Schoolbased
health
centers
Community
Characteristics
Health
characteristics
of students
and families
4
Summary: A Gap Separates EHR and Social
Determinants of Health
 Merits bridge building in both directions.
 EHR cannot include large arrays of
social determinant data.
 EHR can link to wide variety of social
determinant data.
 Linking requires common variables.
 Because residence commonly defines
resources, it provides an optimal link
between EHR and social determinant
data.
Community Guide
Discussion