Artificial intelligence is defined as the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. Commonly referred to as AI, it’s increasingly being employed in healthcare, and, according to Accenture, has the potential to save the United States $150 billion annually by 2026.
The top ten AI applications in healthcare are robot-assisted surgery, virtual nursing assistance, administrative workflow assistance, fraud detection and dosage error reduction. The administrative workflow assistance component plays an important role in medical billing and addresses multiple challenges. However, it’s important to note that AI isn’t designed to replace medical billing professionals, only enable them to work more efficiently and focus on other tasks.
Mitigation of Unnecessary Errors
AI is slowly being applied to various applications in medical billing to address obstacles to accuracy and productivity. The challenges in medical billing aren’t breaking news, but they have a definite impact on healthcare providers’ reimbursement and revenue cycle.
Claim denials, patient eligibility mistakes, inaccurate or incomplete documentation, manual processes and the compilation of more than 70,000 billable codes and other issues make it difficult for medical billers to conduct error-free processes, even when they have years of experience. Duplicate charges, upcoding, unbundling and illegibility errors during data entry also can result in a claim being denied.
Though not usually done maliciously, administrative errors in medical billing can be costly for the healthcare system as a whole. They account for up to half of all medical errors in primary care. The Centers for Medicare & Medicaid Services (CMS) notes that coding errors resulted in $28.91 billion in improper payments in 2019. Four-in-five medical bills in the U.S. contain at least minor mistakes, resulting in $68 billion annually in unnecessary healthcare spending by doctors and patients. And, the American Medical Association estimates that inaccurate claim payments cost the healthcare industry $1.5 billion in unnecessary administrative expenses.
Perhaps one of the most common uses of AI technology in medical billing is automation. In addition to time savings, it boosts productivity and efficiency for various professionals employed by hospitals, health systems and physician practices by automating repetitive analyses and procedures. Completing revenue cycle management (RCM) tasks often is expensive, but automating them can markedly advance financial processes while enabling providers to focus on patient care.
In an AMA survey, 86 percent of physicians described that prior authorization load as a “high” or “extremely high” burden, with 91 percent saying the process delays care and negatively affects clinical outcomes. By utilizing AI to automate the pre-authorization process, providers and patients are informed sooner about whether or not a procedure or treatment is covered under a specific health plan.
Computer-assisted Coding (CAC)
Another common application of AI in medical billing is CAC, which has been shown to lower coding time by 22 percent without reducing accuracy and increase coder productivity by more than 20 percent. Some newer CAC solutions are designed to enhance the system’s ability to analyze the clinical documentation and determine which codes are relevant to a particular case.
The National Health Care Anti-Fraud Association (NHCAA) estimates that financial losses due to healthcare fraud are in the tens of billions of dollars each year. AI can be used to quickly monitor and identify medical billing and coding trends that point to false claims.
Other current and potential uses of AI in medical billing include extracting EHR data to populate claims forms, matching EHR data with relevant medical codes, auto-correcting codes, generating relevant codes from medical reports and automatically conducting audits. These activities combined could result in even more accurate, efficient and cost-effective medical billing processes.
Additional Benefits for the Medical Billing Industry
In addition to decreased processing times and a reduction in standard work hours of administrative staff, AI offers bountiful benefits for the medical billing industry, including:
- Increased provider satisfaction through less EHR data entry
- Improved patient satisfaction through timely distribution of accurate billing statements
- Enhanced ability to contextualize unstructured data
- Quicker identification of errors
- Reduced claim denials
- Improved workflows
- Decreased operating costs due to manual billing processes
- Increased ability to perform audits in real-time
- Improved accuracy in text processing
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