using data & analytics for population healthb4a04973-f047-4601-ad69... · using data &...

Using Data & Analytics for

Population Health

Anjum Khurshid, MD PhDDirector, Data IntegrationAssistant Professor, Population HealthDell Medical Schoolanjum.khurshid@austin.utexas.edu@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

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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

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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 . . .

anjum.khurshid@austin.utexas.edu

@Akhurshid1

Special thanks to team members in the

• Data Integration Core

• Department of Population Health

• Dell Medical School

• Austin community partners

Acknowledgements