Leveraging Machine Learning algorithms to address a business question: Can Patient Centric Service Creation make a difference to Estimates Provided?

Vishnu Galigekere, Davis Gregory, Radhika Mandava
Data Scientist & Software Engineer & Manager, Software Development
Plano, TX
Day 2
11:15 AM

Imagine being at a hospital with a sick family member, and having to worry more about the financial burden, rather than comforting your loved one?

Patient experience is the most important factor that determines the success of the Patient Access team at a hospital.

We will be presenting our findings based on the research in an attempt to answer a question, Will Patient Centric Service Creation make a difference? Does it make a difference to the patients we serve, the clients who use our products, or to nThrive the company we work for. Our goal is to make a difference in a positive manner.

In CarePricer, accuracy of estimates is key for patient experience. How can we ensure our product continues to make a difference, when patients make key decisions in their lives based on the estimates we provide? Our service creation process has been a differentiator in the market for years, but our competitors’ are soon bridging this gap. How do we keep up with that edge in the market?

Our solution is to generate Patient Centric Services. Working with historical data already available in-house, we would like to leverage Machine Learning algorithms and patient attributes, to arrive at patient centric services. This enables us to create more accurate estimates and catered to the patient being served. This proof of concept is a modest attempt to answer some of these questions. Combining a business proposal with Data Driven Science, we hope to arrive at a positive conclusion.