How Artificial Intelligence Is Rewriting Medical Coding Automation
It’s hard to overstate the importance of artificial intelligence. When implemented efficiently, AI has the ability to multiply your billing business tenfold. In many cases, AI is what is expanding the business rather than the physical workforce. The question in many business minds is how does AI change the way business is done?
To help answer this question, we looked at many billing and coding companies. Below is a condensed version of our research findings:
Coding and billing is a method by which standard codes are established that categorize patient information records and therefore dictate billing to insurance companies.
The goal is to create a standard billing cost that is determined by the patient’s record code. Unfortunately, this process faces significant accuracy challenges.
This could be attributed to insufficient documentation, ineffective execution of procedures.
As indicated by the emergence of technology, according to the Centers for Medicare & Medicaid Services (CMS), errors resulted in $ 36.21 billion in improper payments in fiscal year 2017. (1)
The encryption industry suffers a major setback due to the nature of its audits, which take place towards the end of the revenue cycle. Therefore, even if mistakes are acknowledged, it is too late to rectify them, as the cost of rectification is often higher than the initial damage.
Within the medical billing and coding industry, it was recently reported that billable codes have now crossed a total number of over 70,000, subsequently increasing the need for medical coders at a significant rate.
Medical coding work, when done manually, is complicated and labor intensive as there are only a limited number of accounts that each individual can efficiently handle. This is part of the reason the industry has witnessed several instances of inaccuracies, due to costly mistakes made in trying to keep up with the ever increasing new codes that are being established.
The need of the moment is to create an agile process that allows the medical billing and coding process to flow smoothly.
How does a traditional medical billing and coding process flow?
The traditional billing system involves a great deal of documentation and manual paperwork. The paper claim is a time-consuming process in which the coders entered each code individually on the printed forms. All paper forms are then passed on to the medical billing organization and then to payers.
In a paper-based configuration, the average turnaround time from claim submission to receipt of payments is between 5 and 7 weeks, while in automated medical billing systems it can be reduced to 2 weeks.
Claim-to-Pay Pursuit Using a Paper-Based System – Overview
Patient visits doctor’s office
The patient registers and receives treatment.
Doctor or assistant write superbill
Medical encoder adds treatment codes
The encrypted paper forms are sent to medical billers who then format the data and send it to insurance payers.
Pay generates check and sends payment to vendor
How will AI automation drive the medical billing process?
Today, the ongoing challenge is the accuracy of the encoding. To improve the efficiency and effectiveness of the billing and coding process, many healthcare companies are finding ways to simplify the work of manual coding with AI.
Applications.
Emerging technology in AI is based on computer-aided coding (CAC) that works on machine learning and natural language processing (NLP). The CAC automatically identifies and extracts data from documents and inserts it into the system.
The Need of the Hour is an automated web-based system that analyzes the doctor’s documentation for text / treatment and automatically recognizes the relevant medical codes.
Beyond processing code and large volumes of data, AI can significantly reduce standard work hours and human errors.
What problems does artificial intelligence solve?
A natural concern with the popularity of artificial intelligence applications is the fear, within the industry, that these emerging technologies will reduce the number of jobs available across the medical billing and coding spectrum.
However, it should be noted that these applications have the ability to substantially increase the efficiency and speed of human coders to perform accurate coding, but cannot completely replace human coders. For example, when the encoder makes a mistake, the application can immediately signal it with recommendations to rectify the mistake, and the correction is made as quickly as possible. This fixes “too late” problems and increases the speed at which the encoder works.
However, it is worth mentioning that this concern can be mitigated by observing that the target growth rate of employment within the health sector is at an unprecedented rate over the next decade. According to the Bureau of Labor Statistics, it projects an 18 percent increase in employment for health information technicians between 2016 and 2026, well above the average growth rate for all other occupations, adding 2.4 million new jobs. (two)
The obstacles of the current system: our perspective
The complex nature of medical billing and coding makes it a constant target for errors, and sometimes errors can result in considerably high loss.
This complexity also lends itself to the requirement for a more significant workforce, where coders spend more and more time executing smaller tasks that could be carried out quickly and efficiently by
automated systems of AI technologies.
Considering the current growth of this aspect of healthcare and its expected increase in the US, a robust system is the need of the moment.
AI automation is that system, which is prepared to address all the pain points that the current system is experiencing, such as inaccurate billing instance, etc.
Considering that rectifying erroneous billing, when done manually, is a lengthy and complicated procedure that can incur additional costs, AI adoption can automatically pinpoint errors immediately and mitigate those additional costs and time consumption. .
The way to follow
Medical coding and billing is the essential component of how healthcare is provided and reported in the US Inaccurate coding is a challenge that must be addressed with new technology. OSP Labs is working with healthcare technologists to create impactful solutions for medical coding companies.
Schedule a quick appointment online with our AI specialist to delve into intelligence healthcare claims management and see some of our groundbreaking AI projects. We analyze your business, understand your pain points, and create an AI roadmap to solve your critical challenges.
Considering the current growth of this aspect of healthcare and its expected increase in the US, a robust system is the need of the moment.
Source: – https://www.osplabs.com/insights/how-to-boost-medical-billing-business-using-artificial-intellegence/