How we supported a revenue cycle management suite for the healthcare industry improve the success rate of appeals for payment completion and thus increase their overall revenue using Natural Language Processing (NLP) Analytics.
IMPROVED ACCEPTANCE RATE
WITH 25%
~65% UPLIFT IN
OVERALL DOLLAR RATIO
IMPROVED OVERALL
REVENUE
THE SITUATION
With the previous appeals made by the hospitals to the insurance company for outstanding payment completion, about 70% resulted in failure.
Our client wanted to understand the reasons leading to these appeals resulting in success or getting retired. They also wanted to identify the combination of words that could improve the chances of appeals to be successful. The success of the appeal was defined by a payment made after it, which can be quantified by calculating the actual payment-to-payment request ratio, considered as the dollar ratio.
THE SOLUTION
The appeal letters were of a wide variety. These letters were studied thoroughly to understand the content and the way details were mentioned in them. Based on the exploratory data analysis, the letters were segregated into different groups. Amplify created a deep learning-based model to classify these appeal letters in each group as successful or likely to be rejected.
To further identify the likelihood words and sequence of words used in these appeal letters likely result in success or rejection, an Explainable AI model was created. Based on the explainability of the words, a new sequence of words was suggested to further improve the verbiage of these letters, which could in turn result in improving the overall acceptance rate of the appeal letters sent by the hospitals and health systems, maintaining the correct semantics and syntax as per English Grammar rules.
Technical solution: NLP Analytics was used for classification and verbiage improvement in appeal letters
BUSINESS IMPACT
The case study showcases how Amplify Analytix provided a solution to the client using Text Classification and NLP Analytics. This helped in revising the content and format for the letters sent by healthcare service providers to appeal for payment to insurance companies. The new and improved appeal letters resulted in a better acceptance rate, and payment completion by insurance companies further helped in improving overall revenue.
