The medical billing process is the backbone of healthcare revenue cycle management, but many healthcare providers face challenges in accurately and efficiently billing patients for their services, with an estimated 30 to 40 percent of medical bills containing errors.
And those mistakes can be painful—one mistake in medical billing can result in thousands of dollars in mishandled costs for both physicians and patients.
The medical billing process requires outstanding communication across departments and payers, as well as ensuring that vital information is correctly captured in each step of the procedure. Efficient medical billing is critical for optimizing healthcare revenue cycle management and driving value-based patient care, but effectively streamlining the process is currently a pain point for the healthcare industry.
The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) is also intensifying the importance of resource effectiveness and quality improvements, and artificial intelligence (AI) can support it in doing so. Health innovators are using next-generation automation tools to drive the next stage of transformation.
Some automation solutions are even smart enough to apply the possibilities of natural language processing and machine learning to automate the coding process that is involved in classifying patient records according to the International Classification of Diseases (ICD), one of the most complex transactions in healthcare revenue cycle management.
The ability to accurately code and classify all diagnoses, symptoms and procedures recorded in conjunction with hospital care is paramount to all healthcare practices, yet this process is entirely manual and can lead to problems such as limited time for research and inflated costs of operations. Innovative automation tools can transform the process of ICD coding by mapping the physician’s comments from a consultation against a multi-level medical dictionary. Natural language processes enable such tools to extract the accurate code and, consequently, return a significant cost reduction in coding.
Healthcare is constantly evolving, and as the number of patients increases, the need for more accurate and efficient back-end systems for healthcare providers is stronger than ever. Automation also can assist with tasks such as patient scheduling and claims processing, by increasing efficiency and restoring the balance between paperwork and people.
By harnessing the power of automation, healthcare providers can focus more on providing a more patient-centric practice, in turn giving patients the treatments they deserve.
Ultimately, there is a remarkable amount of opportunity with back-end automation in the healthcare sector. From a claims processing perspective, there are still a number of manual processes as you go through the entire revenue cycle, which can contribute to errors. Automated solutions employing artificial intelligence can help organizations monitor and improve on key performance indicators.
Another outcome and value proposition driven by the implementation of automation solutions that can employ AI is fewer cancelled appointments and increased appointment turnout. Many healthcare providers suffer financial loss when appointments are missed because of last-minute cancellations or patients simply not keeping appointments. Automating scheduling and sending appointment reminders to patients has been proven to increase the number of patients that doctors see each day, thus driving efficiency and more effective management.
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