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April 12, 2022

15:00 UTC   Start Times Around the World

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Description

Customer Spotlight: Plano Orthopedics and Sensa Analytics apply Machine Learning to Revenue Cycle Management Processing
For this session, we are pleased to welcome our guest speaker Steve Chamberlin of Sensa Analytics, who will discuss how Sensa Analytics used Oracle Machine Learning with Oracle Autonomous Database to address two important use cases in healthcare claims processing.

Healthcare organizations face the challenge of efficiently processing thousands of claims each day. There are two primary reasons submitting claims has become difficult:

1) Human interaction for submitting and reviewing claims will cause errors due to the increased volume of requirements for the procedures, and
2) The requirements for submitting claims change daily when looking at the broad spectrum of healthcare plans and changing insurance company policies.

A more effective method must be put in place to help the Revenue Cycle Management (RCM) team. They need a smarter way to avoid mistakes when coding a claim and track denied claims for a quicker response.

Plano Orthopedics Sports Medicine Center (POSMC) has teamed with Sensa Analytics to use Oracle Machine Learning with Oracle Autonomous Database in this process. Machine Learning is used to search the setup or coding of claims for errors prior to submitting them to insurance companies. This means faster reimbursement of the claims. It can mean the difference of getting paid in 2 weeks instead of 2-3 months. This can be anywhere from a 2-6% improvement which adds up to hundreds of thousands of dollars annually.

Another aspect of machine learning is being used to find denied claims and categorize them. This is a monumental task for the RCM team. An individual in RCM could have over 500 claims to manage every day. This means creating or correcting a claim in less than 1 minute continuously throughout the day, every day. This makes it impossible to manually review multiple reports and systems to find claim issues and update them with a proper response.

In this session, learn about project goals and results. See how Sensa applied machine learning to the data, the technical architecture and process, and lessons learned with examples.

Your Experts

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    Steve Chamberlin

    Steve Chamberlin

    My analytics journey began in 2001 at PeopleSoft, and have been working over 17 years with Oracle systems. The primary applications we utilize are: OAC (Oracle Analytics Cloud), Data Visualization, DBCS, ADWC (Autonomous Data warehouse cloud), APEX and Machine Learning. Through our experiences, we've created Healthcare apps to improve workflow across disparate systems within an organization. We've delivered OAC-ADW implementations across multiple industries. Most recently through our work in healthcare, I was recognized with the Oracle Excellence Award.
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    Sherry LaMonica

    Sherry LaMonica

    Sherry is a member of the Oracle Machine Learning Product Management team. She has 20 years of software experience focused on enabling the commercial use of the open-source data analysis software systems R and Python for data science and machine learning projects. She has worked with customers in fields as diverse as as pharmaceutical research, financial analysis, manufacturing and healthcare IT.
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    Mark Hornick

    Mark Hornick   

    Mark Hornick is the Senior Director of Product Management for the Oracle Machine Learning (OML) family of products. He leads the OML PM team and works closely with Product Development on product strategy, positioning, and evangelization. Mark has over 20 years of experience with integrating and leveraging machine learning with Oracle technologies, and working with internal and external customers in applying Oracle’s machine learning technologies for scalable and deployable data science projects. Mark is Oracle’s representative to the R Consortium and an Oracle adviser and founding member of the Analytics and Data Oracle User Community. He holds a bachelor's degree from Rutgers University and a master's degree from Brown University, both in Computer Science.
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