How Intelligent Automation Tames the Healthcare Document Beast
June 22, 2020 / Insurance, Intelligent Process Automation, Robotic Process Automation
Few vertical industries are as document-intensive as healthcare, whether on the provider or insurance side. That makes the healthcare industry ripe for tools that can automate insurance claims processing and other chores, for both providers and insurers alike.
The challenge is heightened by the fact that most of the documents in question are unstructured, consisting of text, numbers and images that vary in nature and in terms of content. That means approaches to intelligent document processing that rely on templates to identify and extract content will be ineffective, because you can’t reasonably create a template for every potential document an insurance company or healthcare provider may have to process.
Rather, healthcare providers and insurers need intelligent document processing tools that can “read” a document much like a human would, extract the relevant information and transfer it to a format suitable for input to a downstream tool, such as JSON, CSV, or XML.
Related Article: Transforming Insurance Operations with Intelligent Automation
Mountains of unstructured documents
The complexity of the situation can hardly be overstated. A large health insurance company, for example, likely processes upwards of 3 million documents per year of various types, each one containing potentially dozens of pertinent data fields. A clinical document could include free form text from doctors notes; various numbers, including ID numbers for the case, member and provider; patient name and date of birth; date of service; various health insurance codes to depict the procedure performed, diagnosis, and so on.
On the healthcare provider side, the roles are essentially reversed, as they must deal with forms and correspondence from a multitude of 3rd party insurance carriers, each with their own forms and formats.
As you can imagine, it takes a small army of humans to process these forms, which is why providers and insurers are investigating process automation software. Many have found robotic process automation (RPA) tools, as well as solutions that combine optical character recognition (OCR) with templates, can not adequately address the problem. While they work well for tasks or documents that are the same every time, they tend to hit a wall when it comes to all the variation inherent in unstructured documents, such as emails, patient records, doctors notes etc.
Automating document processing for unstructured content requires an intelligent process automation (IPA) solution that incorporates technologies including natural language processing and deep learning. This is key to the platform being able to handle highly variable documents and images without the need for writing thousands of rules in the background.
The training component is key. With IPA, it doesn’t take thousands of documents to train the tool. Because if intelligent automation’s unique application of transfer learning, it takes only a few hundred. From there, the tool will be able to, as an example, discern a discharge summary document from a medical history record document or a case ID number from a member ID number on different forms – even if the tool has never before seen that exact form or document. There’s no need to continually tweak the model each time a new type of document comes along, meaning model maintenance all but goes away.
Dramatic productivity gains with IPA
The benefit of intelligent automation tools is hard to overstate. IPA can dramatically reduce the human resources required to process mountains of paperwork – reductions around 80% are common. To learn about how it all works, download this white paper from process automation software experts at the Everest Group, “Unstructured Data Process Automation.”