DME billing is the process by which a patient receives treatment from a hospital, and the medical biller creates the bill based on the inputs provided by the medical coder and sends it to the insurance company to claim the charges incurred by the patient.
Even though DME billing appears to be simple, it comes with its own set of difficulties. HME/DME billing entails a variety of
- Codes
- Processes
- Data entry
- Paperwork
Among other things, human error is always a possibility.
This is where task automation can help reduce error rates. Artificial intelligence (AI) will undoubtedly bring about the following 5 major innovations in the DME billing industry.
Innovation 1: Automatic code correction
There are thousands of codes in the medical field in general. Almost every year, a new set of codes is added to the list. As a result, keeping track of it becomes even more difficult for medical coders. Even though all of the codes have been entered into the system, errors continue to occur. Errors are costly in terms of both money and time. Hospitals, EHR companies, and DME billing companies are all concerned about this.
Innovation 2: Repetitive tasks can be automated
Automation of tasks is another innovation we’ve seen in the medical billing industry. When it comes to the medical billing industry, a lot of tasks are repeated. Billers lose a lot of productive time as a result of this. Medical billers can benefit from AI to increase their efficiency and reduce monotony in their work.
Innovation 3: Pre-authorization automation
Billers can devote more time to other important tasks such as patient care, report analysis, and so on by saving time. They will be more active and productive as a result of this. Automation can be used in any process that involves a set of standard procedures, or in other words, rule-based business processes. Data recording could be one of the examples.
Innovation 4: Training for fresh recruits
In most DME billing companies, the trainer will set a specific date for all new employees to attend training. In reality, each new hire will start at a different time. As a result, the training is postponed until a batch has been formed. As a result, the actual work does not begin until much later.
When AI is used in the training phase, recruits are more likely to learn and begin working sooner. They can create an LMS (learning management system) using AI that will guide the learner through a self-learning system using text and audiovisual content. The LMS will direct them to a set of modules and will also assess their ability and proficiency.
Innovation 5: Chat-bots for Patient service
Another AI tool that is widely used in businesses is chatbots. To respond to patient questions, we can use AI-based chat bots. Patients can use a chat application to get information about their
- medical history
- reports
- insurance claims
- next visit reminders
- appointments
Aside from that, this AI-powered chatbot will be able to answer general patient questions. The same tool can be used to keep the patient up to date on the status of their insurance and other claim-related information.
The role of Sunknowledge in DME billing
We not only make sure a stringent process of
- Billing
- Coding
- Collection
with an assured 99.9% accuracy rate, but also the highest productivity metrics in the market. In addition to reducing the risk of DME billing and coding errors, our experts’ continuous AR follow-up aids in the collection of 80% of claims, that are older than 90 days. This results in efficient cash flow for all of our clients.
Unlike any other RCM vendor in the healthcare industry, our team assists remotely during pandemics. Whereas most other RCM vendors are struggling to meet their productivity targets, we continue to set the industry’s highest productivity benchmarks. Our dedicated resources, offer unrivaled and uninterrupted 24×7 supports to all of our HME/DME clients.
We also have excellent industry references if you are looking to transfer your DME billing operation to a dependable source.
