Healthcare and automation? For many, the two remain an unlikely couple. The knee-jerk reaction to “automation” is to think of industries like banking, finance, manufacturing, logistics, or retail. A few will associate the medical sector with robotics.

On the surface level, it’s easy to see why: compared to other industries, healthcare is inherently much more human-centered. That’s because health is a delicate matter and should be handled with exceptional empathy, care, and expertise that only living and breathing doctors, nurses, technicians, caregivers, and other staff can ensure.

However, any healthcare executive knows that no medical procedure could be delivered without dozens of menial back-office tasks. These necessary chores take hours, diverting medical staff from providing care and taking a heavy toll on their efficiency.

The good news is that these are precisely the tasks that can be automated.

Repetitive, patterned, and prone to errors, insurance billing and coding are fundamental activities that modern healthcare businesses delegate to Robotic Process Automation (RPA). What is involved in the process, and how do hospitals, practices, and healthcare professionals benefit? Let’s dive into medical coding automation and its implementation, from discovery to continuous development with experienced RPA consultants.

Despite its significant role in the healthcare and insurance industries, medical coding is often put down as another back-office job. While this is a huge generalization, there’s one truth to it: medical coding is foundational for the efficiency of healthcare-related processes.

To start with, we can’t delve into medical coding without mentioning medical billing. The two go hand in hand, and the same person often performs both tasks (especially in smaller practices). However, the scope of the two activities is quite different.

The main activities within the medical coding business are the interpretation of patients’ diagnoses, test results, and procedures and converting them into one of the standardized classification systems, such as the International Classification of Diseases (ICD), Current Procedure Terminology (CPT), or Healthcare Common Procedure Coding System (HCPCS).

Next, medical billers use these codes to handle insurance claim submission, reimbursement, and billing patients for medical services. Also, medical billing relies on the data translated by medical coders, facilitating communication between healthcare providers, patients, and insurance companies.

On the other hand, medical billing is just one of the many applications of codified medical records. Between EHR, insurance claims, administrative data, surveys, and trials, there’s a massive amount of data to process in healthcare every day.

In this context, having a set of unified codes instead of thousands of terms for procedures, medications, and conditions is a true lifesaver when managing the information flow. It supports:

  • Patients, who receive overall better and faster care, particularly when several healthcare providers are involved in their treatment.
  • Physicians, who can focus on delivering care rather than on decoding abbreviations and acronyms in the records transferred from another practice.
  • Administrative staff, who work more efficiently, benefitting from streamlined data entry, billing, and compliance assurance procedures.

Medical coding helps ensure that all parties in a healthcare ecosystem stay on the same page and communicate smoothly and efficiently.

Medical coding — what can you automate?

All of that sounds great, but it’s important to remember that such an efficient flow of healthcare data is only possible thanks to the everyday work of medical coders. Unfortunately, similar to medical billers, their job can get very repetitive.

The usual workday of a medical coder consists of going through medical records, interpreting them, and assigning them appropriate codes. It is an arduous task and one prone to errors, especially after several hours of mapping lines of text to digits. Thankfully, automated bots are capable of assisting coders with many of these tasks:

  • Text recognition capabilities allow bots to scan and extract structured medical data from documents.
  • The bot then analyzes the abstracted information and searches the code base for the one that corresponds to the data.
  • Finally, the bot handles data entry, filling the chart into a billing system.

Read more about claims processing automation and find out how can it improve your claims management immediately.

Pre-programmed scripts have a proven track record of handling similar duties in related fields, from medical billing to insurance.

Now, before you conclude that medical coders will soon become obsolete, there’s one important caveat. While many records fall into a predefined category, they can get tricky when patients have a long and winding medical history. In such cases, the expertise of a trained, highly-qualified human coder is crucial.

For this reason, as medical coding automation progresses, we’ll still see human coders. The US Bureau of Labor Statistics predicts a 9% employment increase for medical tech specialists, including coders. However, rather than being replaced by bots, they will work in tandem with them as auditors. The result? A human-machine dream team that can process code with far greater speed and precision than one person alone.

Medical coding automation tools

The word “automation” is an umbrella term that covers multiple solutions. The three most relevant to the medical coding automation business are computer-assisted coding (CAC), AI, and RPA. These technologies are poised to define the future of back-end healthcare automation.

1. Computer-assisted coding (CAC)

First off, there’s computer-assisted coding or CAC. It is a solution that uses natural language processing (NLP) to enable faster and easier coding of unstructured data. The tool works like a spell checker for medical records, analyzing documents in search of words and phrases related to the classification and using them to suggest which medical code should be produced.

Thanks to NLP, CAC can distinguish between phrases that include the same keywords but have different meanings due to their context. For instance, CAC will suggest a code when it detects the name of a diagnosed condition but not when it appears in the patient’s family history.

2. Artificial intelligence

AI attempts to take the improvements of CAC one step further by adding machine learning to the mix. AI leverages learning capabilities to remember corrections made by human coders and apply them in similar cases in the future. It can also analyze legacy documentation to identify patterns and make predictions, e.g. evaluating the likelihood of readmission.

Applying AI to data processing solutions results in much faster, more accurate, and autonomous software when dealing with unstructured (and often highly illegible) data such as doctor’s notes. Though AI-powered medical coding solutions have yet to achieve total autonomy, it’s only a matter of time before they become an essential tool in medical coding.

All that power, however, comes at a cost. As a complex solution, AI requires much more computing power, high-quality data, and data science experts throughout its lifecycle. Therefore, for the moment, complex machine learning systems are only available to large, well-founded healthcare institutions that lead the way in innovation. Fortunately, another solution is much more affordable and easier to implement in healthcare facilities that operate on tight budgets and cannot dream of hiring medical data analysis experts.

3. Robotic Process Automation

The specific features of medical coding make it the perfect candidate for RPA-driven optimization:

  • It’s repeatable — medical coding is a recurring cycle of data extraction, analysis, and entry. These smaller processes can be successfully delegated to RPA systems.
  • It’s rules-based — when programmed to follow a simple logic and custom, predefined rules, RPA bots can easily manage medical coding workload.
  • It uses high volumes of data — medical coding involves lots of structured data that constitutes the bulk of medical documentation and can be quickly processed by RPA scripts.

Even though RPA lacks AI’s decision-making and learning skills, it more than makes up for it with efficiency when handling simple workflows and heavy amounts of textual data. RPA is also a comparatively affordable solution requiring qualified personnel only for deployment and maintenance. Once deployed, robotic process automation systems can be easily operated by non-technical personnel.

Learn more about 5 processes for healthcare industry you didn’t know can be automated.

The benefits of RPA in medical coding

Since medical coding affects so many healthcare activities, optimizing it via RPA will have across-the-board positive consequences for the entire organization. Let’s review the top benefits that RPA can bring to medical organizations.

Compliance and correctness

Even though medical coding is the driving force behind simplifying other medical processes, the code systems themselves have grown in size and sophistication over the years. For instance, the most recent version of ICD contains around 17,000 unique codes and a staggering 120 000 codable terms. With numbers, this vast, errors will eventually sneak in even when working with seasoned coders.

Immune to routine and distraction, RPA eliminates human error from the equation. That’s extremely important in an industry where finance, health, and regulations are all involved.

Increased efficiency

With RPA scripts, medical coders can process more charts per day. As a result, they don’t need to pay much attention to simple, common cases and are more focused on complex ones. The additional benefits are better working comfort and lower fatigue; invaluable gains in the working environment where professionals experience severe burnout and exhaustion.

RPA deployment will have an even greater effect on small practices that don’t always have a dedicated coder. Medical coding automation tools will free up their administrative, billing, and medical staff, giving them more time for other tasks.

Having feedback & reviews from former clients is really useful in such a case. There are several platforms that have this capability like Clutch and Upwork.

Cost savings and revenue optimization

Repetitive tasks cost time and resources, so optimizing them for higher efficiency will translate into savings. At the same time, faster records processing allows healthcare organizations to handle more patients.

But these aren’t the only ways in which the deployment of RPA solutions in the context of medical coding can help medical providers reduce costs and shorten the revenue cycles. Think about claims management, for example. Inaccurate or wrongly coded claims delay revenue collection. By closing the door to potential errors and inaccuracies, RPA solutions streamline and speed up the process, enhancing the cash flow for providers.

Improved patient experience

Reducing the margin of error in coding and billing also helps patients focus on recovery rather than worrying about their insurance. In addition, faster record turnover and flow of information between providers lead to overall better care, especially when urgency is essential. Medical facilities can achieve these benefits by deploying RPA-based medical coding, contributing to the enhanced patient experience.

Medical coding automation step by step

Despite a relatively low technological barrier to entry of robotic process automation solutions, they are still a sophisticated technology. This makes RPA implementation a complex process that’s best done one step at a time.

  1. Audit and discovery

No two organizations are ever the same. That’s why research always precedes the implementation of RPA solutions. At this stage, the implementation partners like Flobotics audit and analyze currently used systems, evaluate existing workflows and data structure, define KPIs, and identify high-impact automation candidates.

2. Automation roadmap

We set objectives for each process and plan a schedule at this stage. Usually, we start from relatively easy tasks to automate; this way, any blockers are discovered and can be managed faster, so they don’t stand in the way of more complicated processes later on.

3. Test automation

Before the actual deployment, RPA is tested for use in the organization-specific context. This step allows us to identify potential problems when they are easier to fix.

4. Deployment

Following automation production, a Proof of Concept (PoC) build is deployed as the final trial before the solution goes live. Then, with the last tweaks done, the automation engine is ready.

5. Maintenance and improvement

The de facto implementation is now complete. But as new challenges arise, RPA is adjusted and maintained to help you face them efficiently in the future. Additionally, updates can be made to support emerging use cases, optimize workflows, unburden staff, and increase revenue potential.

Conclusion

Medical coding is one of many repetitive but essential administrative tasks in healthcare that can benefit from robotic process automation. This shows that the potential for RPA to become an industry-defining tool is surely there. Affordable and effective, RPA is also the perfect stepping stone into the world of automation.

So if you’re looking to optimize your medical insurance billing and coding workflows, you’ve found just the right people for the job. Send us a message, and talk about how we can make your organization more efficient by providing RPA consulting services.

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karl mielnicki

Karl Mielnicki

Expert and fanatic in RPA - Robotic Process Automation with over 5 years of IT experience working for consulting companies and tech startups. UiPath consultant, an accredited BluePrism developer.

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