new ways for predictive analytics and machine learning to advance population health
TRANSCRIPT
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Population Health Sub-text comes here
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Predictive Analytics Machine Learning
To Advance Population Health
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Discussion Host
Dr. George Wu,Vice President Edifecs, Inc.
Ankur Teredesai, PhD, Professor & Director, University of WA Center for Data Science
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1 Introduction
2 Analytics: Past and Present
3 Data Tsunami Challenges
4 Analytics & Machine Learning Applied to Healthcare
5 Q&A
Agenda
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Analytics
Future A
Future B
Population
You
What’s the risk?
Which risks?
How to prevent?(prescriptive)
No hypothesis required
(i.e., no prior medical
knowledge)
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Analytics Amazon
• Puts items in cart prior to order• Greater customer satisfaction (faster
delivery)• Supply chain and logistics optimizationU.S. Department of VA and Dartmouth School of Medicine1
• Durkheim Project• Opt-in database of 100,000 veterans
and millions of social media posts• Identify risk factors in military suicides
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Data Tsunami
Healthcare data is increasing in volume by 48% per
year
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Center for Data Science: Societal Impact
• Bioinformatics• Health and
Wellness• Predictive Analytics
Health Informatics
• Distributed Systems
• Databases• Geo-Spatial• Embedded
SystemsGeo-Spatial Data Management
• Machine Learning• Data Mining• Computation
Intelligence• Computer Vision
Intelligent Systems
• Web• Devices• Mobile Networks• UX / UI
Social Computing
• Cryptology• Secure Machine
Learning
Big Data Security
• Engineering• Dev-Ops
Big Data Infrastructure
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Predictive Analytics: Why and When?
Common Question: Machine Learning instead of Statistical Regression
The goal is to predict accurately vs. simple explaining a phenomenon
Predictor variables• Too many factors
(25+)• Risk of
Readmission (Demographics, Labs, Vitals, Claims, Comorbidity, LOS)
• Highly Correlated
The predictors have non-linear relationships to the target variable• Linear: Childrens
Medication::Weight
• Non-Linear: Effect of medication over time useful then harmful beyond a time
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iTORNADO
iTornado
Routing Service With Real World Severe Weather
Demo Paper in ACM SIGSPATIAL 2014(Best Demo paper award)
Fatalities Stats by Weather Related Hazards http://www.nws.noaa.gov, June 2014.
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Our Focus: Predictive Population Health Applications
Chronic Condition Care Management
Scalable ACO
Population/Individual Cost Analysis
Bioinformatics and Systems Biology
Readmission as a Service
Scalable Cost Prediction
Personalized Medicine
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Accountable Care OrganizationsCost/Charge Prediction
HealthSCOPE: An Interactive Distributed Data Mining Framework for Scalable Prediction of Healthcare Costs
Marquardt James, Newman Stacey, Hattarki Deepa, Srinivasan Rajagopalan, Sushmita Shanu, Ram Prabhu, Prasad Viren, Hazel David, Ramesh Archana, De Cock Martine, Teredesai Ankur, IEEE Data Mining Conference Demo Track, 2014 IEEE International Conference on DOI: 10.1109/ICDMW.2014.45 Publication Year: 2014 , Page(s): 1227 - 1230
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Motivation: ACO Cost Prediction
Demographics
Diagnosis Codes
Procedure Codes
DrugsLab ResultsC
linic
al
Cla
ims
Sources : SID, OSHPD, MEPS Source : MultiCare Collaboration
ChargesVitals
Health Prediction
Care Management
What are healthcare costs for assigned
population in 2015 ?
Why is the cost so high or low ?
How does the cost distribute across demographics ?
Population Predictive Modeling
Feature Prioritizatio
n
Individual Predictive Modeling
Chandola et. al, KDD 2013
QU
ESTI
ON
SD
ATA
SCIE
NCE
DAT
A
APPLICATIONS
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Cost/Charge Prediction Problem
Predict future healthcare charges of individualsBased on past medical history and charges information
Goal:
Supervised Machine Learning
Technique:Previous health information (e.g. diagnosis, comorbidities, etc). General demographics (age, gender, race)Previous healthcare cost{X} = (x1, x2, x3 ......xp)
Input X:Future healthcare cost in $
Output $Y:
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Predictive Cost Analytics: 4 Scenarios
3 Months of Historical data (Medical, Demographic and Cost)• Cost of Following Nine months (1Q)
6 Months of Historical data (Medical, Demographic and Cost)• Cost of Following Six months (2Q)
9 Months of Historical data (Medical, Demographic and Cost)• Cost of Following Three months (3Q)
12 Months of Historical data (Medical, Demographic and Cost)• Cost of Following Twelve months (4Q)
Access the webinar in full Recorded webinar
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Next Steps
Other Resources
ContactShareApplying Data for Population Health Recorded webinar Questions?