AI in healthcare has done a steep climb in the United States of America in terms of implementation and usability in the last decade. The onset of the pandemic in 2020 has increased the deployment of artificial intelligence solutions in effective healthcare systems, with most administrative teams working remotely. While AI is used in different areas of healthcare like robotic surgeries, nurse-like chatbots, and diagnosis assistance, medical billing is one of the most vital areas of the healthcare industry that has excelled with the help of this advanced technology. With over 70,000 codes in the medical billing workflow, it becomes challenging for the in-house billing and coding team to insert the correct codes with the corresponding medical service.
Artificial intelligence tools have been developed with advanced features to ensure that most manual errors are eliminated. When analyzing the different claim denials in the industry, it has been recorded that more than 70% of the denials can be avoided if the clerical errors are wiped out of the workflow. This can only be possible with the help of a system that can scheme through a bulk load of claims and bring out the areas of contention. This article will take you through the use of AI in healthcare billing through the years and decode its potential in 2022.
Why do you need AI in healthcare billing in 2022?
- Lack of accuracy is one of the vital areas in medical billing that need immediate improvement to ensure clean claim rates remain high and the revenue flow increases.
- The coding and billing teams at healthcare organizations often struggle with a high volume of billables. Managing the greater volume requires the teams to increase the speed of processing. Manual errors subsequently increase when working in a manual setup.
- Healthcare systems have been struggling with short-staffed teams since the beginning of the pandemic. The situation has not improved significantly two years later, in 2022.
- With Covid-19 still making its presence felt all over the world, new and evolved codes in the USA are still coming up in large volumes. Health systems need experienced billers and coders to tackle the rapidly changing codes along with the evolving state and federal regulations.
- AI systems have in-built data points which can prove to be highly useful for in-house teams. For example, if a health system has its branches in 5 different states, it can be highly likely that the states have different rules regarding the Covid-19 codes and exemptions.
- Once the biller or coder enters the information into the system, the AI tools will run the data points and figure out which rules specifically apply to the particular claim. In case of any errors made with respect to the regulations, the tool will scan through the data and identify the issues for the team to rectify.
- Translating EHR notes to the respective codes is a massive task to be done manually, making it very difficult for the in-house billing teams. AI tools can help in making the process smoother without compromising on the quality of the job.
- In 2022 with the growing and changing medical billing methods, industry experts believe that AI in healthcare billing is the most viable way to move forward.
Need for Intelligent Back-end Systems
- Back-end systems in healthcare management form a backbone of support for the revenue cycle to stay strong.
- With the pressure increasing on the in-house billing teams with complex workflow management growing by the day, it is vital for the health systems to adopt intelligent back-end support, which can expedite their speed of claim processing while eliminating repetitive clerical errors.
- The best advantage of artificial intelligence is that it learns with the responses around its existing architecture. This makes the tools easily adaptable to changing environments. This feature can be a great point for the back-end systems like medical billing workflow.
- Medical billing in 2022 and beyond needs operators who are quick learners. They need to grasp the changing rules and implement them without any delay or error. Intelligent back-end systems coming with AI can play the role of these fast learners, being excellent helping hands to the existing in-house billing teams.
- AI tools make the job easier than any other technology or manual process in the industry since they work with pre-defined data points loaded in the system. Once they are able to recognize known patterns, they can put them in a proper framework and work with them in the future.
- These properties are also very useful when it comes to providing data analysis on medical claim processing. The management at the healthcare companies can make well-informed decisions with proper predictions of the existing work patterns once they have a data-structured detailed report in hand.
- As the sophistication around AI grows, the tools are also able to audit the revenue cycle management reports by themselves. The system self-adjusts the result of these audits to the known values, thus providing a more structured approach to handling revenue management.
- AI in healthcare also helps in improving the quality of patient experience over time. With the help of AI tools, the medical bills become more precise and come with minimum error. This gives the patient a more transparent view into the healthcare management, improving their trust in the system.
Does AI in healthcare need heavy investment?
- Investing in a new AI management system for your organization could be overwhelming for your financial health. It is also true that the digital transformation journey will take up the time of your in-house team when learning and implementing the new system.
- However, the overall improvement in the financial journey will be a rewarding experience once you implement the AI system. The revenue lost due to the manual errors in medical billing workflow will be reversed along with a steady flow of revenue due to the smooth AI system.
- If you are still not sure about investing your share into a new AI medical billing system, you can get in touch with a leading RCM company that can assist you with the same services. Their team of experts will help you navigate through the existing issues while providing staff training support for your in-house team.
We hope this article helped you decode the various implementation of AI in healthcare billing. If you have any queries, please write to us in the comment section below. Subscribe to our blog and follow us on LinkedIn, Twitter, Facebook, and Instagram for more such articles and news updates.