How AI, ML can transform medical record reviews for insurers

If you are involved in the legal, insurance, or healthcare space and deal with injury claims (workers’ compensation, liability, no-fault), can you think of any other task that results in more work and more time spent than dealing with medical records? It doesn’t matter what type of litigation it is, medical records are the foundation of every bodily injury claim and it is critical that these records are complete, organized, and thoroughly reviewed.

It is also important to note that in a workers’ compensation claim this process – collecting and reviewing medical records – is a moving target as a claim progresses from date of injury to maximum medical improvement, to date of settlement. Updates and new records are typically being added to the claim file while discovery may be ongoing.

And yet, these records are critical to understanding things like causation, assessing damages, and forecasting treatment and settlement potential. The insights gathered from a review of these records include: documentation of current treatment, identification of any previous injuries or pre-existing conditions, changes in condition, subsequent injuries, prescription drugs, ICD codes, etc. Therefore, this process is essential to ensure that the records are complete and tell the entire story.

Back in the day, when medical records would come in the mail at my law firm they would be reviewed, organized, sorted, and summarized before the client was billed. Rinse and repeat when the next stack of documents comes in the mail. And all of this was done manually, gobbling up huge chunks of time.

Honestly, other than the delivery method, that process really has not changed much in 15 years. A good question to ask is how many people are doing these activities and how much time are they spending on any one claim? There are usually numerous professionals involved in a claim, including adjusters, nurse reviewers, attorneys, expert witnesses, and physicians providing a second opinion

I likely missed some, but you get the point – so much time spent dealing with medical records. Let’s plug in some data from ChatGPT and do some very rough math.

Adjuster’s time and skills are being wasted on clerical tasks

The average time spent per day by insurance adjusters reviewing medical records can vary depending on several factors such as the complexity of the case, the number of medical records to review, the experience level of the adjuster, and the specific requirements of the insurance company. However, in general, insurance adjusters may spend anywhere from two to six hours per day reviewing medical records.

So, let’s take the median – and say that the average adjuster spends 4 hours per day reviewing and organizing medical records. That is literally half a day spent reading, highlighting, sorting, and getting an understanding of the medical treatment involved in a claim. If an adjuster had four extra hours a day, how much more effective could they be? How much more time could they spend on the complex and difficult tasks and the files that they are uniquely qualified to handle?

Between the great resignation and an aging workforce, every minute an adjuster can spend on the tasks they are uniquely qualified for, such as settling claims, is critical. Additionally, while adjusters may skim medical files to save time, is that really the most efficient use of time and is it driving the best quality? Even the best adjuster can miss critical information buried in a medical document. 

Lawyer and physician review costs

The amount of time that a bodily injury attorney typically spends reviewing medical records can vary depending on several factors, such as the complexity of the case, the volume of medical records, and the lawyer’s experience and expertise. It is common, however, for lawyers to spend several hours reviewing medical records per day. 

Similarly, the cost of reviewing medical records by doctors can vary depending on the complexity, the type of case, the amount of time required to review and/or organize the records, the location, and the specialty of the doctor. According to a survey conducted by the American Medical Association, the average hourly rate for reviewing medical records in 2021 was $238 per hour for non-specialists and $301 for specialists. It is important, however, to note that some doctors may charge a flat fee, while others may charge a per page or per hour rate. But if they are spending several hours reviewing and organizing records, the costs add up quickly.

You get the point: the costs of time and money dealing with medical records is significant for many people  on both the Plaintiff and Defense side. 

So, how can we bring AI and ML to the table and not only help reduce expenses, but also give everyone back some time to focus on the difficult tasks that they are uniquely qualified to handle?

Simplify the process with technology 

The good news is insurers can now enter a new era of efficiency with cutting-edge Artificial Intelligence and Machine Learning. AI simply refers to the development of intelligent machines that can perform tasks that typically require human intelligence such as reasoning, learning, and decision making, according to ChatGPT. 

ML, on the other hand, is a specific subfield of AI that focuses on the development of algorithms and models that enable machines to learn from and make predictions or decisions based on data. ML involves training a machine using large amounts of data, where the machine can learn and improve its performance over time. A good analogy to understand the distinction between ML and AI is to think of AI as a toolbox and ML as one of the tools inside. AI has the goal of creating intelligent machines and ML is one of the techniques used to achieve that goal. 

One exciting use case of AI and ML is in the field of medical record review. 

Given advances in technology we can now successfully review unstructured documents to identify and extract key terms and medical data resulting in expedited file reviews. Cracking the complexity of unstructured documents was the key. Medical records are extremely complex because the data is not in a structured format. Just about every doctor, hospital, office, or provider has a different form or format for maintaining records. Some are typed and some handwritten. Some provide a background on the injuries and prior history, others do not. Some start with a description of the injury, others start with a prior history. You get the point. 

Cracking this code has allowed software to now review medical records with AI and ML. This technology can successfully organize records and put them in chronological order; remove duplicates; provide a timeline of treatment; retrieve critical information such as ICD Codes, medications, and comorbidities; tag medical terms to allow filtering; and identify information in an easily uploaded table or document. As a result, users can achieve significant cost and time savings. How much time can be saved? Our research has shown the average person takes about two minutes per page to review medical records. Technology, however, can do the job in six seconds per page, representing time savings up to 90% with accuracy rates up to 95%.