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“ High Precision Analytics for Healthcare: Promises and Challenges” by Sriram Vishwanath
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Transcript of “ High Precision Analytics for Healthcare: Promises and Challenges” by Sriram Vishwanath
High Precision Analytics for Healthcare: Promises and Challenges
Sriram VishwanathProfessor, UT Austin
Cofounder, Accordion HealthPresident, Brilliant.MD
Problems with Predictive Analytics
Where Are My Actionable Insights?
“… Software X is a black box. I put my data, and it gives me some sort of risk scores. I know that high risk scores are bad. So, what should I do next? …”
“… I purchased Software Y, and it gives me a report that there have been thirty preventable readmissions in the last month. But I want to know what to do to prevent them in the future … “
Wait!All those people said that they do “predictive” analytics
A Good 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
The Importance of Right Methodology
Claims
Rx
Labs
EHR
transforminto
tensorsfeature
extraction
apply algorithms(ML and traditional)
blend
ing
model
Input
ActionableInsight
Intervention
feedback
feedback
GLM
kNN
RF
*courtesy Accordion Health
Forecast the Future
Example – 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
Example – 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
Example – 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. Lin• Risk score: Low
Example – 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
*courtesy Accordion Health
Predicted Superutilizers
Alice S.Bob W.Cindy N.Doug D.Eve A.Frank L.George B.
Hank T.Ivana M.Jack K.
Alice S.
Cindy N.
Keith L.Larry L.Mary W.Nancy S.Olivia Z.
Patrick W.Quincy A.
Robert S.
13
POST-ACUTE RISK PREDICTION
Case Study
BUNDLING: POST-ACUTE RISK PREDICTIONPost Acute Pathways
Discharge Date Day 0
CJR PeriodDay 90
Home Health
SNF
Inpatient
Good Decision: Patient A (blue) placed in a Skilled Nursing Facility (SNF), then goes home.
Bad Decision: Patient B (red) placed in (HHA) after discharge, resulting in readmission due to surgical complications.
Patient A
Patient B
*courtesy Accordion Health
Post Discharge Facilities Determine Overall Costs
*courtesy Accordion Health
Micro Targeting and Forecasting for Care Intervention
*courtesy Accordion Health
Targeted Predictive Prescriptive
Sriram [email protected]