It is difficult to overstate the importance of Artificial Intelligence. When implemented efficiently, AI has the ability to increase your billing business tenfold. In many cases, AI is what is scaling the business rather than the physical workforce. The question on 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 summarized version of our research findings:
Coding and billing is a method through which standard codes are established that categorize patient information records and thus 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 precision challenges.
This could be attributed to insufficient documentation, inefficient execution of procedures.
As noted in Technology Emergency, according to the Centers for Medicare & Medicaid Services (CMS), errors resulted in $36.21 billion in improper payments in fiscal year 2017. (1)
The coding 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 errors are recognized, it is too late to rectify them, as the cost of rectification is often greater than the initial damage.
Within the medical billing and coding industry, it was recently reported that billable codes have now surpassed a total number of 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 each individual can handle efficiently. This is part of the reason why the industry has seen several instances of inaccuracies, due to costly mistakes made while trying to keep up with the ever increasing new codes being established.
The need of the hour is to create a streamlined 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 large amount of documentation and manual paperwork. Paper claiming is a slow process where coders enter each code individually on paper forms. All paper forms are then passed to the medical billing organization and then to the payers.
In a paper-based setup, the average turnaround time from submitting a claim to receiving payment is 5-7 weeks, while in automated medical billing systems it can be reduced to 2 weeks.
Claim-to-Payment Pursuit Using a Paper Basis: Overview
The patient visits the doctor’s office
Patient registration and receive treatment.
Doctor or assistant writes superbill
Medical coder adds treatment codes
The encrypted paper forms are sent to medical billers who then format the data and send it to insurance payers.
The payer generates the check and sends the payment to the provider
How will AI automation drive the medical billing process?
Today, the current challenge is the accuracy of the coding. To improve the efficiency and effectiveness of the billing and coding process, many healthcare companies are finding ways to simplify manual coding work with AI.
Applications.
The 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 the data from the documents and inserts it into the system.
The need of the hour is an automated web-based system that parses physician documentation for text/treatment and automatically recognizes relevant medical codes.
Beyond code crunching and big data, AI can significantly reduce standard man hours and human error.
What problems does artificial intelligence solve?
A natural concern of the popularity of AI applications is the fear, within the industry, that these emerging technologies will reduce the number of jobs available in the medical billing and coding spectrum.
However, it should be noted that these apps come with the ability to substantially increase the efficiency and speed of human coders to perform accurate coding, but they cannot completely replace human coders. For example, when the coder makes a mistake, the application can immediately flag it with recommendations to fix the mistake, and the fix is done as quickly as possible. This fixes “too late” issues and increases the speed at which the encoder works.
However, it is worth mentioning that this concern can be assuaged by noting 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 the employment of health information technicians between 2016 and 2026, well above the average growth rate for all other occupations, adding 2.4 million new jobs. Job positions. (2)
The Obstacles in the Current System – Our Perspective
The complex nature of medical billing and coding makes it a constant target for errors, and at times, errors can result in a significantly high loss.
This complexity also lends itself towards the requirement for a more significant workforce, where coders are spending more and more time performing menial tasks that could be carried out quickly and efficiently by
AI technologies automated systems.
Given the current growth of this aspect of healthcare and its expected rise in the US, a robust system is the need of the hour.
AI automation is that system, which is prepared to address all the pain points that the current system experiences, like inaccurate billing instances, etc.
Considering that rectifying misbilling, when done manually, is a lengthy and complicated procedure that can result in additional costs, the adoption of AI can automatically flag errors immediately and mitigate those additional costs and time consumption.
The way to follow
Medical billing and coding are the essential component of how healthcare is delivered 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 deeper into intelligence healthcare claims management and see some of our innovative AI projects. We analyze your business, understand your pain points, and create an AI roadmap to solve your critical challenges.
Given the current growth of this aspect of healthcare and its expected rise in the US, a robust system is the need of the hour.
Source:- https://www.osplabs.com/insights/how-to-boost-medical-billing-business-using-artificial-intellegence/
