How RPA can help in Medical Billing and Coding with Healthcare CMS

  • by:
  • Source: Emerj
  • 11/12/2020

Employees and contractors at the Centres of Medicare and Medicaid Services spend countless hours every year reviewing thousands of medical records to ensure the accuracy of Medicare Advantage payments. An automated intake tool is working to change that.

Using emerging technologies such as RPA, Machine Learning and Artificial Intelligence, the Process Automation Tool ingests records as they are submitted and identifies potential problems according to set parameters, submission rules and coding guidance. Specifically,

  • RPA orchestrates the steps of the intake process
  • OCR digitizes the scanned document
  • AI and machine learning are applied to understand the document and extract the information necessary to validate the information

Medical billing and coding is an integral component of healthcare. The medical billing outsourcing market alone is projected to reach $16.9 billion by 2021. The coding and billing process translate patient record information into standard codes which are used for billing patients and third-party payers such as a Medicare and insurance companies.

However, coding accuracy is an ongoing challenge. According to the Centre for Medicare & Medicaid Services (CMS), errors resulted in $36.21 billion in improper payments in FY2017. For example, a major category CMS attributes these errors to is “insufficient documentation for home health claims.”

Home healthcare is defined as medical services provided by health care professionals in the home of a patient. To be eligible for Medicare coverage, physician certification is required and improper payment errors occur when documentation is missing or incomplete.

Medical Billing and Coding AI Applications Overview

The majority of AI use-cases and emerging applications for medical billing and coding appear to fall into the category of Computer Assisted Coding. Specifically, companies are using machine learning and Natural Language Processing (NLP) to automatically recognize and extract data from medical documents for proper coding and billing.

In the article below, we present four representative examples as well as the current progress of each example. We have organized the companies using a set of 7 quantifiable factors (e.g. funds raised, target user, etc…) that we thought would be of particular interest to readers.

How IntelliBuddies® is helpful

Buddies (software assistants) operates and executes the processes at a typically greater speed than humans. It helps the healthcare organization to streamline the following CMS processes— billing and coding, workflows, coding accuracy, scanned documents with images, physician notes, and billing documents without any human interaction seamlessly with the AI automations concepts (NLP, OCR, ML, speech and visual recognition) bundled in the tool.

The Process Designer IDE tool provides large set of activity libraries, and an intuitive drag and drop interface to define the workflow so that anyone with minimal coding knowledge can easily start automating the processes by connecting individual activities to build a sequence.

Source: Emerj

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