hxr 2016: data insights: mining, modeling, and visualizations- sriram vishwanath
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Data Mining & ML for Value-based Care
Accordion Health
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OUR APPROACH• Population Health Personalized Health• Identify High Risk Patients Predict Change of Risk• I can Predict it all Based on Measured Precision
Key InsightProvider is as critical as patient in determining outcomes
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OUR METHODOLOGY
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Claims
Rx
Labs
EHR
transforminto
tensors
featureextraction
apply algorithms(ML and traditional)
blend
ing
model
Input
ActionableInsight
Intervention
feedback
feedback
GLM
kNN
RF
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Forecast FutureForecasting next events is more difficult than predicting a specific event.
- Anything can happen; a lot of noise
- Need to find “causal” paths
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Personalized-Forecasting Demo
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Joe S.• 69 y/o man with COPD & h/o acute
exacerbations• Tend to occur annually with seasonal
triggers• Also has DM, HTN which are
relatively poorly-controlled• He does not always take his COPD
meds• PCP: Dr. Alvarez (and other
members of healthcare ecosystem)• Risk score: Medium
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Joe S.Joe had a COPD exacerbation last spring…
So, it’s not surprising that he will likely have another exacerbation next spring
Difficulty in Prediction : EasyAssociated Costs: High
Intervention: Medication Reminder Intervention: Home-visitEfficacy: Low Efficacy: High
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Linda R.• 76 y/o woman with h/o well-
controlled Hypertension• Family h/o of CVD• Recently seen for palpitations,
but otherwise asymptomatic• Mostly adherent to medication• PCP: Dr. Tiwari• Risk score: Low
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Linda R.Although palpitations are asymptomatic
We predict severe cardiac dysrhythmia, like atrial fibrillation And the likelihood of a
stroke is highDifficulty in Prediction : Hard
Associated Costs: Extremely HighIntervention: PCP-visit, additional medication prescribed
Efficacy: High
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MEASURED PRECISION
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The “Labdata-at-Home” Challenge• Collect Data passively• Restroom
• Urine• Fecal matter
• Shower• Skin samples• Hair samples
• Use timeseries modeling• Predict comorbidities
• With high accuracy