Artificial Intelligence (AI) has extensive uses in the healthcare industry for medical practices like investigating the gene mutations that lead to autism and detecting lung cancer. The use of AI in these aspects has led experts to wonder if it can improve another critical process in healthcare – revenue cycle management in healthcare.
Interesting Areas of AI Revenue Cycle Management in Healthcare
Here are four areas of revenue cycle management where artificial intelligence can have a tremendous impact in the nearest future for revenue cycle management in healthcare:
Prior Authorizations
A lot of health professionals agree that prior authorization is the most challenging aspect of revenue cycle management. American Medical Association reports that about 86% of doctors call the burden of prior authorization high or extremely high, and about 88% say it has only increased in the past five years.
Because of the transactional nature of prior authorizations, it’s almost the perfect area for AI implementation. With machine learning and real-time analytics, AI can quickly determine cases requiring prior authorization and save a lot of time with the help of revenue cycle management in healthcare.
Determine Patient Setting
Healthcare setting differs for each patient and thanks to AI technology, you may never have to worry about that anymore. Advanced technology uses a patient’s record to determine the most appropriate setting for the best results.
It tells you whether a patient would be most suitable for inpatient or outpatient care and gives a detailed case review. With AI, you can quickly check all the risk factors of the patient setting and make a well-informed decision.
Claim Status Checks And Follow-Ups
Claims are and will always be an integral part of the revenue cycle management process. In the future, a criteria-based algorithm can make the process automated for both short and long term account receivables management.
AI systems will be able to effectively prioritize claims based on factors such as the number of outstanding days and the health professional.
Proactively Stop Denials Before it Comes
Claim denials are among the biggest headaches for hospitals or health institutions to deal with in the revenue management process. Research by Change Healthcare states that yearly, 9% of all claims get denied by the insurance companies or payers . Even though they eventually recover 63% of these claims, the administrative costs of reworking them lead to more losses.
The possibility of using AI to stop denials before they occur is an exciting aspect to explore, and it could work in the following way:
- Investigate and determine what causes denials by CPT code and payer
- Use this gathered intelligence in all of the claim review processes
- With this new information, it will be able to quickly flag areas with incorrect data. This could include incorrect identifiers with a procedure or missing charges.
- Inform staff to follow up on the identified areas
Staff would then correct the errors in the claim before submission, effectively reducing claim denials.
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Use Patient Demographics To Determine Appropriate Billing
AI can analyze previous behavior and form patterns that could predict the appropriate financial model to bill a patient. Past payment behavior, communication preferences, preferred payment methods, and demographic data will inform the AI and develop better collection strategies with revenue cycle management in healthcare.
Based on previous information, AI can also determine the most efficient type and schedule of messaging that a patient would be most receptive to. AI’s advanced technology can detect early signs that a patient may default on the payment plan and alert financial services to these signs.
Predict Claim Payment Period
Artificial intelligence can determine when a claim will be paid. It could project the date and time by reviewing payer-specific payment behavior according to CPT code. With constant development in the AI field, the accuracy of this method will increase in the coming years. This application will make it easier for hospitals to plan, forecast, and make better financial decisions.
Advantages of AI In Revenue Cycle Management in Healthcare
Revenue Cycle Management in Healthcare
While several traditional methods may have applications in the RCM areas above, none can handle them as efficiently as Artificial Intelligence. Here is why AI could be a much better option:
- It boosts revenue growth by minimizing errors in claims.
- Artificial intelligence speeds up the process while maintaining a high accuracy rate.
- Unlike manual processes that are done by humans, artificial intelligence functions 24/7, making it more efficient.
- AI ensures there is no lost information in the patient registration stage and other vital revenue cycle management stages.
- Changes and updates in medical billing will be implemented automatically with artificial intelligence. This technology keeps the health institution updated while avoiding errors and denials.
Conclusion
Some of these advances are yet to be mainstream, and a lot of healthcare institutions have not even explored the possibility of AI-based solutions. However, the healthcare industry will inevitably embrace the use of artificial intelligence in the coming years. It’s best to prepare yourself so that you can fully benefit from the changes that are coming to the healthcare sector with revenue cycle management in healthcare.
