Linking EHRs Between PH,
Social Service Agencies, and
Other Relevant Organizations
How to Create Information Systems With
Data that Flow Both Ways
Arthur Davidson, MD, MSPH
Denver Public Health
adavidson@dhha.org
Committee on Recommended Social and Behavioral Domains and Measures for
Electronic Health Records
National Academies of Sciences Building
2101 Constitution Avenue NW
Washington, DC 20418
April 8, 2014
1
Agenda
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Conceptual Model
Linkage for Public Health Surveillance
Linkage for Public Health Intervention
Next Steps
Linkage Conceptual Model
Quitline
Social
Service
Clinical
Care
(EHR)
Schools/
Childcare
Public
Health
Linkage for Public Health Surveillance
(Colorado)
• Transparent, distributed data network
– Modeled on the Mini-Sentinel (FDA) project and local
experience with HMO Research Network (AHRQ) project
• Governance
– Voluntary participation; unlike mandated reporting, data use
agreements established/required
• Privacy
– Minimal data necessary to achieve stated goal (de-identified
to start)
• Technical
– Infrastructure: 1) common data model, 2) emphasize data
quality assessment, and 3) federated query tool
Linkage for Public Health Surveillance
(Colorado)
• Colorado Health Observation Regional Data Service
(CHORDS)
– Provide a "laboratory" to develop and evaluate scientific
methods to support public health surveillance
– Afford Denver Metro and Colorado communities an
opportunity to use existing EHR data systems for public health
surveillance
– Learn about barriers and challenges, both internal and
external, to building a viable and accurate system of
surveillance for public health events (e.g., conditions,
behaviors and outcomes)
– Build an event agnostic infrastructure for public health
surveillance, quality assessment, and research
CHORDS Registries
Colorado Health Observation Regional Data Service
e.g., Kaiser Permanente
Standard (Virtual) Data
PMN
Warehouse Client
Secure
federated
query
Authorize
CHORDS
Query Service
(PopMedNet )
PMN
Current registry efforts:
• BMI
• CVD risk
• Tobacco use and SHS
exposure
• Mental health
• Colorectal cancer
• Adult obesity
e.g., Denver Health
Authenticate
Secure
federated
query
Standard (Virtual) Data
PMN
Warehouse
Client
Capacity to Support Multiple Conditions
CHORDS Project
Source
Years
Colorado Clinical Translational Science Institute focused on regional
informatics infrastructure for research; existing Cancer Center
informatics expertise
NIH
20082018
Grant allowed initiation of virtual data warehouse (VDW) at Denver
Health complementing Kaiser Permanente local expertise
AHRQ
20102012
Evaluation resulted in selection of Mini-sentinel PopMedNet model
used FDA post-marketing surveillance
20122013
TCHF
KP-CB
20112013
CDC
20112016
Tobacco use, second hand smoke exposure and cessation
CDPHE
20122015
Mental health and substance use
AHRQ
20132017
BMI monitoring including social and environmental and data
Cardiovascular risk reduction - Community Transformation Grant
Link Clinical, Social and Environmental
Data Across Multiple Delivery Systems
Pre-CHORDS (e.g., weight status surveillance):
• BRFSS self-reported demographic, weight data
• Survey ~12,000 Colorado/year = 700 Denver/year
• Allows county-level estimates only
CHORDS state:
• Combine measured BMI data from multiple institutions
• Include demographic data, residence location (geo-code)
• Link geographically aggregated BMI data (e.g. census tract)
with social and environmental data
• Identify “place-based” interventions (e.g., social marketing,
community resource development, and policy initiatives)
• Pilot features of local data sharing network
Types and Sources of Geo-coded Social and
Environmental Data for Mapping
Data
Source
Data type
Grocery stores
Reference USA
Points, aggregated into census
tracts
Restaurants
Reference USA
Points, aggregated into census
tracts
Food Deserts (USDA
USDA Economic
Research Council
At census tract level
Streetmap USA/ ESRI
web distribution
Points, aggregated into census
tracts
Green space/parks
From wide variety of
sources
Polygons (areas) , with points of
park entrance
Poverty
American Community
Survey
Polygons (areas), aggregated into
census tracts
definition)
Walkability (based on
number of street
intersections per unit area)
Combined Measured BMI Data
 Denver County (valid BMI) :
– all ages:
184,644 (31%)
– adults:
119,075 (26%)
– children:
64,606 (51%)
 Coverage varies widely:
‒ > 50% for some communities
‒ few with aberrant results
CHORDS BMI Registry Description
Children <18
345,756
Adults
364,889
Total Sample
710,645
Median Adult BMI by Year
2009
26.5
2010
26.5
2011
27.1
Median Child BMI Percentile
2009
62.9
2010
64.4
2011
65.4
Proportion of Children
with Obesity, Denver
Percent Overweight
+ Percent of Families in Poverty
Personal Prescription - example
Linkage Conceptual Model
Quitline
Social
Service
Clinical
Care
(EHR)
Schools/
Childcare
Public
Health
e-Referral between EHR and Quitline
Goal: Efficient EHR-mediated e-Referral (including
patient preferences) to Quitline and timely
acknowledgement/status messages returned to
and posted within the EHR.
• North American Quitline Consortium
• Consensus process with ~15 Quitline vendors/service providers
• Message requirements:
– Content: define common data elements
– Structure: HL7 2.x and c-CDA formats
– Transport: sFTP, Direct, web-service (WSDL-SOAP)
What next?
CHORDS
• Build out standard data model (i.e., add tables, required
content/variables [IZ], extend time range)
• Conduct comprehensive data quality assessment
• Compare member-vs. visit-based denominator estimates
• Expand stakeholders (PH and clinical)
• Address duplicates
Quitline
• Set e-Referral standards, assure meets PH needs
• Vet with EHRA and standards development organization
• Consider as model for PH related HIE and e-referral for other
community-based services
Sustainability strategy
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Enhance “event agnostic” distributed surveillance/research
network (e.g., breadth of use cases and stakeholders, depth of
content)
Study utility of system to multiple stakeholders (i.e.,
communities, elected officials, and individuals)
Facilitate incorporation of new social/environmental data (e.g.,
barriers and assets)
Standardize approach to geocoding and de-duplication
Target outreach and community-based interventions (i.e., policy,
systems and environmental changes) to those who need them
Assess impact on health disparities reduction
Develop cadre of applied researchers and methods
Discussion/Questions?