If you attended HIMSS last year you know predictive analytics was a hot topic. HIMSS15 in Chicago will be no different as the industry continues to address using data and analytics to spot patterns to improve patient care and outcomes.
As a lead up to Chicago, we’ve joined forces with ZirMed for an upcoming webinar to look at how predictive analytics can help with coding accuracy. In commenting on what will be covered in this thought leadership event, Paul Bradley, Chief Data Scientist, ZirMed, says “In this presentation, we’ll chart how predictive analytics and modeling technology can be applied to a healthcare provider’s historic billing and account data to accurately identify missing charges. Predictive analytics and modeling of thousands of already-collected data elements zeroes in on trends around billable items, taking into account physician practices, specifics of the hospital CDM, and the patient mix that the provider services. This approach identifies millions of dollars of reimbursable care that is often ‘left-on-the-table’ and not recouped.”
You can click here to register for this webinar. Details below.
Date: Tuesday, February 10, 2 pm ET/1 pm CT/11 am PT
Presnters:
Paul Bradley, Chief Data Scientist, ZirMed
Dan Ward, VP of Strategy, ZirMed
Moderator:
Carol Flagg, HITECH Answers
Description: Healthcare providers are often challenged to allocate the resources and technologies needed to research and analyze their coding effectiveness and efficiency. Given time and resource limitations, manual audits are often limited to a small subset of accounts with departments that have complex billing requirements or represent known opportunities for improvement.
With predictive modeling, hospitals can automate the analysis of patient accounts to ensure the necessary codes and charges have been submitted. Predictive analytics leverages data already captured in the HIS to identify coding outliers relative to patterns of similar historic accounts. Additionally, models can analyze data at the claim and transaction level and identify root causes at the core of processing errors, which provide management with the information to determine how to prevent further leakage in the charge recovery process.
In this session, the following learning objectives will be covered:
- Concepts underlying successful application of predictive modeling technology
- Overview of charge capture and how leakage happens
- Application of predictive modeling technology to charge capture
- Charge capture automation and working by exception.
Learn more and/or register for this complimentary webinar.
Attending HIMSS15 in Chicago? Visit ZirMed at Booth 7427.