Post on 06-Jan-2017
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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
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
Forecast FutureForecasting next events is more difficult than predicting a specific event.
- Anything can happen; a lot of noise
- Need to find “causal” paths
Personalized-Forecasting Demo
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
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
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
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
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