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A medical auto coding solution can incorporate the patient’s history and include all the medical services provided to the patient, bringing in value-based patient-centric medical care.

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MEDICAL CODING - KEY TO ACCURATE REIMBURSEMENTS

For organizations across industries, the annual budget planning process is essential to keep them on track and monitor areas that need improvement to deliver sustainable, profitable growth. 

Medical coding continues to be one of the most challenging parts of the revenue cycle management (RCM). It is now at the cusp of a revolutionary change—one so profound that it can transform the way RCM works. This change is brought about by AI-enabled auto coding.

Computer-assisted coding (CAC)—which generates codes directly from clinical documents—has come a long way in the past few years. It helps coders reduce errors and improve accuracy. Auto-coding encompasses a variety of computer-based approaches and goes beyond merely assigning codes.

Accuracy in coding has a direct impact on reimbursements for the providers. AI-enabled auto coding solutions reduce improper payments and enable healthcare organizations to become more compliant, while also improving the bottom line.

According to the 2021 report by U.S. Department of Health & Human Services, CMS improper payment rate was 6.26% to the tune of USD 25.03 billion. Out of this, around 24.2% were due to medical necessity and incorrect coding and 64.1% were due to missing documentation. The findings over the years are quite startling. To measure the improper payments in the Medicare fee-for-service (FFS) program, CMS implemented the comprehensive error rate testing (CERT) program, which is designed to comply with the payment integrity information act of 2019 (PIIA).

auto coding

 

INTELLIGENT MEDICAL CODING IS HERE

Strategic applications of AI can significantly reduce human error and improper payments and improve the physician query system. The benefits of AI-powered medical coding are -

Strategic applications of AI can significantly reduce human error and improper payments and improve the physician query system. The benefits of AI-powered medical coding are -

01. Increased accuracy and repeatability: 

Medical coding depends on the coder's proficiency. Not all coders have the same skill level, hence the probability of error is high either due to knowledge gap or analytical gap—the difference where a coder is unable to properly analyze the medical records to interpret the documentation and apply coding guidelines accordingly to derive accurate codes. 

AI-powered auto-coding solutions will improve accuracy and consistency, increase output matching in line with the official standard and payer reporting standard. The coding guidelines can be incorporated to reduce improper payments. As natural language processing (NLP) engine learns, the recall rate and precision improve.

02. Compliance and identification of clinical documentation gaps: 

As medical coding guidelines get updated, coders must remember the latest guidelines and the coding clinics. The proposed auto coding solution will consider the latest coding clinics and guidelines while assigning codes, thereby improving adherence to compliance requirements. 

Another critical aspect of compliance is the scope of documentation improvement with auto coding. The solution will identify missing documentation in the medical records. It can detect and flag errors and anomalies quickly, track the updated records, and send reminders to physicians to close the gaps. It can also significantly benefit clinical documentation improvement (CDI). By identifying potential documentation gaps caused by increased capture rate of comorbidities and complications, the solution will improve the overall CDI process.

03. Faster medical billing: 

AI-enabled auto coding will considerably reduce the time it takes for coders to go through each medical record and extract the diagnosis and procedures performed and deliver accurate results.

With improvement in the confidence score of auto coding solutions, the focus will shift toward machine-first delivery model and coders will be able to better handle flagged or complex inpatient and outpatient coding. This will enhance coders’ capability and performance. The accuracy and detailed coding will lead to increased revenues for the facility and reduced denial rates and dependence on coders.

 

ACCESS THE ENTIRE UNIVERSE OF THE PATIENT'S HEALTH HISTORY 

To make this happen, the AI-enabled solution will have to overcome a few key challenges.

The final code selection is based on the coders’ knowledge of the guidelines, clinical concepts, and compliance regulations. These guidelines provide clarity but are also open to interpretation. The solution needs to learn to identify the importance of specific documentation and its relation to ICD-10-CM and PCS codes. As more data is processed by this auto coding solution, the accuracy will improve. Also, these solutions need to be flexible to seamlessly integrate with the different electronic medical record (EMR) systems used by the providers. 

The solution can also incorporate the patient’s history and current medical issues. It can include all the medical services provided to the patient, bringing in value-based patient-centric medical care. With the capability of the auto coding solutions and potential future application, it is certain that AI-enabled auto coding has arrived, and its impact cannot be overlooked.