Accordion Health was founded in 2014 by three machine learning PhDs to provide data analytics solutions to healthcare organizations. It uses advanced machine learning and predictive modeling techniques like time-series analysis, tree-based models, and deep learning on healthcare data to help payers and providers measure value, identify opportunities for improvement, and suggest interventions to control costs, increase revenues, and improve quality of care as the US healthcare system shifts to value-based reimbursement.

1. Data Analytics in Healthcare
Yubin Park, PhD
CEO/CTO of Accordion Health, Inc.
Your Technology Partner for Value-based Care 1

2. Accordion Health
• Founded in 2014 by 3 machine learning PhDs
• Yubin Park, PhD – currently CEO/CTO of the company
• Joyce Ho, PhD – Professor at Emory University
• Sriram Vishwanath, PhD – Professor at University of Texas at Austin
• We are a team of data scientists and engineers who deeply understand
• Nature of different machine learning and data analytics techniques
• Complexity of US healthcare and its noisy datasets
• We work with multiple healthcare payer organizations and risk-taking provider
organizations
• With our predictive analytics API and Web-based products, we help them control their costs,
increase their revenues, and most importantly improve the quality of care
Your Technology Partner for Value-based Care 2

3. How do we help US healthcare?
• The payment model in healthcare is
shifting from Fee-For-Service (FFS) to
Value-Based Reimbursement (VBR)
• Physicians and health plans will get
paid for the values they bring to
patients, not for the services they
provide
• How do we measure the value?
• How do we improve the value?
• How do we align the value and incentive?
• Solution) Using advanced data analytics!
Your Technology Partner for Value-based Care 3
Measure
Value
Measures
Identify
Opportunities
Suggest
actions for
improvements
Interventions
(actions)
Collect data

4. What techniques do we use?
• Time-series models are useful
• Longitudinal analysis is critical for deriving and measuring the value
• Tree-based models are useful
• In healthcare, you may see lots of interaction effects
• Tree-based models can capture such interaction effects
• Deep-learning based models can be helpful
• Complex and multi-length datasets
• Lots of natural language and unstructured data
• Convolutional/Recurrent Neural Nets are being actively investigated to handle such datasets
• Of course, we use Python and R
• To do all these stuffs, we use a mix of Python and R
• We develop our custom algorithms using Python
• We use R for exploring data and visualizing results
Your Technology Partner for Value-based Care 4