integrated aco selected for the naacos innovation showcase
TRANSCRIPT
© 2015 IntegratedACO
NAACOS Innovation Session
© 2015 IntegratedACO
Save Lives.Save Money.Let’s do Both.
NAACOS Innovation Session
Why We Are Here
I was part of the problem.
Who Are We?
Vipul Mankad
M.D. Founder and Senior Medical Adviser, IACO (2013-present); Senior Medical Adviser-CMS (2005-2006); RWJ Health Policy Fellow-US Senate (2003-2004);
Eric Weaver
MHA, President (CEO), IACO, Focus on Leadership, Physician Practice and Information Management
Joydeep Ghosh
Directs data mining and predictive modeling operations for ACOs, currently the Schlumberger Centennial Chair Professor of Electrical and Computer Engineering at the University of Texas, Austin
Provider Locations
Midland/Odessa 10
San Antonio 14
Austin 13
Weatherford 1
Alpine 1
Bastrop 1
Port Lavaca 8
Integrated ACO LLC
Track 1, Advance Payment Model,
January 1, 2013
Independent Practices (Primary Care)
Underserved region of West Texas with high numbers of Hispanics
Vast geographic area
Physicians:
28 in 2013 > 48 in 2015
Beneficiaries:
7,177 in 2013 (PY1)
13,000 + currently
90% EHR penetration
9 Platforms
Initial Skepticism, Resistance and lack of Awareness
Will ACA be repealed?
Will Supreme Court overrule it?
We don’t need more work.
Haven’t we seen this before with HMO’s?
Why would I want to spend more time with patients and compromise FFS revenue?
Opportunities
No capital outlay for physicians (advance payment model ACO)
Fast deployment with CMS funding
Low risk - high reward
(Shared Savings in PY1)
Physician autonomy
Capture quality incentives
Prepare for new value-based reimbursement
Free care coordination
Better Care for Patients
Our Experience with MD Recruitment
Physician Ownership, Incentives and Governance
No Conflict of interest - reduction of unnecessary hospitalizations for Ambulatory Care Sensitive Admissions (ACSA)
Executive leadership
Medical Leadership in each region
Well-defined Care Coordination protocols
CHF and Diabetes
Clinical and Predictive analytics
ACO Strengths
One of only 6 Advance Payment ACOs to create a
surplus
Per capita expenditure benchmark: $12,203
Actual Per Capita expenditure: $11,668
Reduction from $81.4 MM to $77.8 MM
Approximately 4.5% cost reduction in PY1
Successfully reported on 100% of quality
measures
Returned $1.54 MM and created a surplus of
$208,000
50% performance bonus and 50% reinvestment
Performance Year 1 Results
Integrated Data Warehouse and EHR Penetration
Versatility in EHR interfacing methodologies
Automated Quality monitoring and GPRO reporting tool
Clinical Analytics to measure compliance and deviation from EBM guidelines
Powerful algorithm for prediction of preventable admissions for CHF patients.
Psychographic segmentation of patient population based on personality type to
personalize care coordination intervention
Innovations
Data Aggregation and Software Modules Used
Predictive Analytics in an ACO
Small number of patients generate large proportion of
costs
Top 5% generate 43-47 % of the costs (CBO and
AHRQ)
Not the same 5% each year
Some of the 5% from last year died
Problem solved (at least temporarily, e.g. bypass
for AMI)
Which 5% will generate the cost in the next 5
months?
How to predict and prevent Ambulatory Care
Sensitive Admissions?
Ambulatory Care Sensitive Admissions
Ambulatory Care Sensitive Admissions
What’s in the CHF Model ?
325 Features in the Model
Demographics (sex, race, age)
Population Level Data (high school graduation and median income)
Healthcare Usage (Outpatient, inpatient, SNF, HHA and Hospice)
ICD-9 Codes during past 1 month and 12 months
Chronic conditions
Utilizes a Lasso regularization technique to: Reduce the number of predictors in a generalized linear model. Identify important predictors. Select among redundant predictors. Produce shrinkage estimates with potentially lower predictive
errors than ordinary least squares.
Goal of Model – To predict accurately which patients will be in top 1%/5%/20% of preventable admissions
Prediction of CHF Admissions
Area Under the Curve (AUC or ROC Curve)
False positive versus true positive
Random Prediction 50%
AUC greater than 70% is excellent
Measures error rate (specificity versus
sensitivity)
Lift Value or Gain Chart
How well the model sorts the patient from a
no model selection
Power of Prediction over random (no model)
selection
Prediction of CHF Admissions
(C-statistic: AUC 0.89 with a Lift of 17.6 at 1%)
ROC and Lift Results
Model AUC Lift at 1% Lift at 5% Lift at 10%
Chronic PQI 0.8365 18.5208* 6.6667 5.5556
Acute PQI 0.7956 NA 5.000 4.1667
CHF 0.8937 17.6492** 11.7648 7.0588
Pneumonia 0.8393 8.0010*** 8.0000 4.8000
* Predictive power is 18.5 times the random selection
** Predictive power 17.6 times the random selection
*** Predictive power is 8 times the random selection
Innovation and Differentiation
Unlike other predictive models developed from grouped data, our
system builds the model from individual (i.e. non-grouped)
More than 325 features are used in analysis
Innovative use of publicly available socioeconomic data
C-statistic in 0.9 range with strong lift at 1-5%
AUC of 50% is considered random.
A model with AUC of 70% is considered good.
Cost Effective Use of Care Coordinators
7,000 Medicare Beneficiaries in PY1
35 Care Coordinators needed to achieve
1:200 ratio for all ACO patients ($2.8M/yr at
10% effectiveness)
2 Care Coordinators needed if 5% of
population (most likely to generate future
costs) is selected ($140k/yr at 50%
effectiveness)
Challenge: Identify 5% of patients most prone
to ACSA admissions in the near future (e.g.,
within next 6 months)
1 CHF admission = $10,000-18,000
Our ACO’s New Innovation
(In Development)
granular view of each
segment
customized patient
engagement approach
for care coordination
Adapt messaging to
individual personality
Psychographic ProfilingC
usto
miz
ed P
opula
tion M
anagem
ent S
yste
m
Alerts
Patient Portal
Patient Outreach
Point of Care
Care
Management
Who uses Psychographics?
Industry Recognition of our ACO’s Predictive Algorithm
Our innovation will be receiving a national award,
LEADING EDGE FOR INNOVATION, at HIMSS15
later this month.
