The Role of AI in Medical Billing and Coding

As a result, healthcare organizations are confronting a host of technical and administrative challenges when it comes to ensuring correct and efficient billing and coding:

• There are in excess of 70,000 billable codes, the complexity of which significantly boosts the need for medical coders. The number of qualified professionals who can convert EHR (electronic health records) data into codes correctly and quickly isn’t keeping pace with the demand.
• Coders are needed to manually match each medical visit and procedure with a corresponding code from the 70,000+ available, which is both labor-intensive and inclined to error.
• The information then must be keyed into assorted systems for various functions, such as accounting and creating patient statements, which is yet another time-gobbling activity, again prone to human error.
• The complex and laborious manual coding procedure isn’t scalable. With the inadequate number of capable coders, as well as the growing sophistication and workload, many organizations are overwhelmed by costly errors.
  

So, just what can AI do to help healthcare organizations facilitate their billing and coding procedures while minimizing costly errors.

• A significant attribute of AI will be its knack to examine text and the spoken word. Systems will be able to ascertain the language for procedures and diagnosis and ascribe correct codes. This ability could have a pronounced effect after code set updates to make sure appropriate codes are applied and documentation is in compliance, easing the transition that happens with coding updates. Imagine how much more stress-free the transition from ICD-9 to ICD-10 codes would have been if AI had been deployed!
• Perhaps the most noteworthy aspect on a medical biller’s day-to-day activities may be caused by a deep learning of a user’s interaction with electronic health records (EHR) and billing software. Using AI to discover a user’s habits, foresee their needs and show the right data at the right time is of utmost importance for practically all of the major health IT vendors. Automatically retrieving and manipulating information has the capacity to significantly cut labor spent on manual billing tasks (leaving them to RPA or robotic process automation). Part of that allows medical facility staffs to make better choices concerning next step, denial resolution.
• One of the highly important features of AI will be its capacity to make conclusions and projections. Today, it can take hours, at times even days, to get a pre-authorization from a payer. Forthcoming systems could be capable of analyzing a patient’s health data and decide the necessity of a medical procedure within a few seconds. The good news for medical billers is that a programmed method will ensure authorization has been acquired and its related data captured, reducing (or getting rid of) pre-authorization denials due to the absence of an authorization number.
• In addition to accurately coding EHR data, AI has the capacity to routinely perform audits, self-adjusting established values to the audit results. As it matures, the system will continue to reduce margins of error, channeling revenue back into the healthcare system by billing the right amount. This will assist patients as well, ensuring they are not ever overcharged and letting them to simply retrieve their medical bills in a more agreeable fashion.
• AI will no doubt boost efficiency and profitability in the future. However, an even bigger prospect to grow revenue may rest in AI’s ability to investigate data and formulate learned decisions. An example would be a condition where denials are mounting owing to an absence of medical necessity, not having documentation or coding mistakes. AI would investigate the denials to uncover the reason and then produce prompts within the EHR/PM to correct the issues, secure all information for accurate coding and assure the provider’s notes are complete. Truth is, it’s not only healthcare providers and medical billing staff that are set to profit from improvements in AI, but payers as well. According to the Centers for Medicare and Medicaid Services, a recent fiscal year realized an overall improper payment rate of 8.12 percent or $31.62 billion. Considerable savings from “smart” AI systems have the capability to save payers money, which will (with any luck) drive down the overall cost of healthcare.
• AI-technology will be employed across all industries, not only healthcare. Improvements in customer service could noticeably impact the way patient communications are conducted; for example, bots that are utilized for patient communications such as appointment scheduling and securing payment. A chief benefit for both providers and billers is that the method can be standardized, drastically cutting the amount of difficult patient interactions regarding billing and even improving the relationships patients have with medical providers and billers.