Automating Medical Coding & Billing Process

Organization:-
This customer is a group of over 30 physicians, nurse practitioners, and physician assistants dedicated to the practice of providing wound care services. They offer their services to patients in their homes and residents in long-term, subacute facilities and assisted living facilities. They are servicing approximately a hundred of these facilities throughout New Jersey, New York, and Pennsylvania, managing 1500 patients weekly.

Challenges:-
Prompt and correct payment through Medicare is important operational aspect for all healthcare providers. The process of manually analyzing clinical documentation—charts and notes—and determining which codes are relevant to a specific case was highly tedious and time consuming. The process required dedicated skilled coders to manually deal with over 70,000+ codes that fall under different categories to generate proper invoices daily. Such complexity and related changes can cause inaccuracies in medical coding delaying the overall operations and can also result in improper payments.

This customer wanted to eliminate the potential loss of revenue from inaccurate coding. Moreover, from a revenue cycle management perspective, it was crucial that the coding for billing was done quickly and with one hundred percent accuracy to avoid rejection/non-payment of claims.

Solution:-
Nividous’ AI-powered RPA Bots are deployed to code thousands of charts on a weekly basis with ease and efficiency. The Bots with native machine learning capabilities understand and analyze each patient’s wound documentation to create billing codes that are then used to create proper invoices. The invoicing/payment process can be accomplished via an external billing company, dedicated system or can all be taken care of in house.

This automation has helped in reducing the risk of manual errors, improving overall process efficiency, and allowed medical personnel to spend more time focusing on patient care and more complex coding scenarios.

Benefits:-
1. 95% reduction in manual work.
2. 90% improvement in coding accuracy.
3. 85% improved process turnaround time.