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Using Data & Analytics for
Population Health
Anjum Khurshid, MD PhDDirector, Data IntegrationAssistant Professor, Population HealthDell Medical [email protected]@Akhurshid1
Outline
• Introducing Learning Health System
– Dell Medical School’s Data Infrastructure
• Strategies for Population Health Data
– Clinical Data Integration
– Social Determinants of Health
– Connected Personalized Data
• Going forward
Dell Medical School & Innovation
Vision: a vital, inclusive health ecosystem
Mission: revolutionize how people get and stay healthy by
• Improving health in our community
• Evolving new models that reward value
• Accelerate innovation and research
• Educating leaders who transform health care
• Redesigning academic health to better serve society
Data & Analytics are Key to Dell Med’s Mission!
Research/ Innovation
Education/ Training
Data, Informatics,
Analytics
Clinical/ Service
Data Management
Analytics
Informatics
A Learning Health System
. . . is designed to generate and
apply the best evidence for the
collaborative healthcare choices
of each patient and provider; to
drive the process of discovery as
a natural outgrowth of patient
care; and to ensure innovation,
quality, safety, and value in health
care.
Institute of Medicine of the National Academies, 2012
Infrastructure for Learning Health Systems
3 Key Trends in Healthcare
1.Datafication98% hospitals use electronic
records
2. Value-based Care90% of payments linked to quality
and value3. Personalized
Medicine>80% health outcomes affected
by factors outside healthcare
3 Healthcare Data Problems
1. Fragmented + Silos
2. Complex rules + processes
3. Messy and unclean data
Frandsen et al. Care fragmentation, quality, and costs among chronically ill patient. Am J Manag Care. 2015;21(5)
Cost of Fragmentation
2. Beyond healthcare data
1. Accurate, timely, relevant medical
data
Strategies for Population Health Data
3. Connected patient’s data
2. Beyond healthcare data
1. Accurate, timely, relevant medical
data
Strategies for Population Health Data
3. Connected patient’s data
Community Health Information Exchange
Building Relationships and Trust
Usual story of accessing data
Da
ta C
ore
Op
era
tio
ns
Post-Data Core
2. Beyond healthcare data
1. Accurate, timely, relevant medical
data
Strategies for Population Health Data
3. Connected patient’s data
McGinnis. The Case for More Active Health Policy . . .
Health Affairs 2002
Social Determinants of Health
Build out a Proof of Concept,
on a community-focused data
infrastructure,
using environmental data,
delivered at the point of care
for pediatric asthma patients
Proof of Concept in Pediatric Asthma
Effect of Allergens and Air pollutants on Asthma
People’s Community Clinic, Austin
Community Health Data Platform
Co
mm
un
ity
Pro
ject
Java
+ J
SON
-bas
ed A
PIs
No
SQL
Dat
abas
eC
lou
d-b
ased
Pla
tfo
rm
Java
+ J
SON
-bas
ed D
ata
Extr
acti
on
+ Im
po
rt L
ayer
Co
mm
un
ity
+ H
ealt
h D
ata
Mo
bile
Ap
plic
atio
ns
Co
mm
un
ity
Pro
ject
Co
mm
un
ity
Pro
ject
Co
mm
un
ity
Pro
ject
Ho
spit
alSc
ho
ol
Pu
blic
Geo
spat
ial
Applications & DashboardData
ExtractionData Linkage &
StorageData Ingestion Data Sources
▪ Five key outdoor environmental factors in asthma
symptomology – PM2.5, NO2, SO2, ozone + pollen (tree).
▪ Indoor air quality has even greater effect – allergies,
dampness, cats, cockroaches, rats + mice.
▪ Project Details▪ Map environmental factors that drive exacerbations geo-
locations in relation to home and school.
▪ Deliver data to providers at the point-of-care.
▪ Measure benefit (to providers) + clinical outcomes (patients).
Key Social Determinants in Pediatric Asthma
Breathe Austin Dashboard
2. Beyond healthcare data
1. Accurate, timely, relevant medical
data
Strategies for Population Health Data
3. Connected patient’s data
Personalized Data: Blockchain
• Mayor’s Office, City of Austin,
Dell Medical School, Emergency
Medical Services, and several
community service providers
• Engaged persons experiencing
homelessness
6-month pilot to test blockchain technology for identity management in homeless population
MyPass Initiative Results
• Developed educational materials
• Tested a blockchain platform for
acceptability and implementation
• Held a blockchain hackathon in
collaboration with Austin Blockchain
Collective
• Identified key lessons for future
blockchain applications
Self-Care and TeleMonitoring
Data, health informatics, data analytics are
going to be key tools in revolutionizing health
care and population health.
Clay Johnston, MD PhD
To increase the pace of innovation in health, high-
quality data needs to be ubiquitous and analysis much
richer
To summarize . . .
@Akhurshid1
Special thanks to team members in the
• Data Integration Core
• Department of Population Health
• Dell Medical School
• Austin community partners
Acknowledgements
