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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