Data Hygiene in Claims: How AI Medical Record Review Tools Help Detect and Clean Duplicate Medical Records

Duplicates, typos, and commas can all make for “messy” datasets that slow down workflows. They can also increase risk. According to Gartner, poor quality data costs companies an average of $15 million each year in losses. Duplicate documents, inflated record volumes, and increased error rates during claims review add up to real costs – but AI medical record review tools can help detect, flag, and manage these inefficiencies. 

The Importance of Clean Data for Claims

In a 2017 report by MIT’s Sloan School of Management, poor data quality can cost as much as 15-25% of revenue. Today, according to Monte Carlo’s 2023 survey, this number is more like 31%. Medical records contain vast amounts of unstructured data. This data is often siloed across IT systems and duplicated in messy piles of paperwork. 

When claims teams have access to clean, organized data, they spend less time verifying numbers, retrieving documents, and correcting errors. Having an efficient method of cleaning and refining your data not only adds revenue, it reduces cost. Even without adding new tasks, simply eliminating some of the bulky data overhead leaves time for social activities like building relationships with co-workers or learning from a mentor or supervisor – which is where data from Pew Research shows the most employee satisfaction. Automating your data cleanup can help find the sweet spot between high productivity and low turnover. 

How AI Helps Clean Up Claims with AI Medical Record Review Tools

Duplicate medical records create inefficiencies, increase risks, and unnecessary paperwork. These medical duplicates present challenges across healthcare, litigation, and insurance sectors. A record might appear in two different places with slightly different formatting, duplicates might exist with missing pages, or duplicates can appear from different EHR systems, each generated on a different time or date. These documents from hospitals or insurers appear on the desks of claims teams – all related to the same patient. 

One record from a hospital can be requested by an insurance team, duplicated in a full medical history from another hospital, and requested again by the claimant’s lawyer. In this example, 3 copies of the same medical record will show up on the claims team’s desk. The end result is 3 times as much paperwork and a longer timeline for the claim. An AI medical records summary or an AI medical chronology can clean this data and produce a usable document in a fraction of the time. 

Claims professionals often rely on manual methods or basic software automations to flag and remove duplicates, which can be time consuming and costly – especially if there are errors. In the earlier example, the claims team might accidentally delete all 3 copies, thinking there was a 4th. The document is now totally removed and time consuming to replace. 

Simple automations or manual reviews with flag false positives or negatives lead to unnecessary review in some cases and errors in others. Delays in decision making can compound (in the earlier example, the claims team, lawyer, and healthcare provider might all be looking at the same 3 duplicates in the case, and all processing these documents differently) to increase the risk of a privacy or security breach. AI medical record review tools can reduce some of these redundancies and make for a faster, easier claim. 

AI Medical Chrononologies & AI Medical Summaries Keep Data Clean

AI medical record review tools with expert human supervision analyze dates, provider names, formatting, and patient identifiers, with the ability to reason and a vast dataset of training.  This allows it to detect duplicates, even when the duplicates aren’t a perfect match, as well as flag inconsistencies. AI medical record review tools can catch and flag documents, fix out of sequence pages, retrieve missing information between versions and compare metadata. This helps generate clean, consistent documents ready to be picked up by claims teams and streamline the adjudication process. 

Wisedocs’ AI platform is flexible, configurable, and trained on over 100 million industry specific documents. Wisedocs helps enterprises delete duplicate records, flag inconsistencies, generate AI medical records summaries, and put data into an AI medical chrononology. With human-validated quality control (an “expert in the loop” model) and secure, compliant hosting, Wisedocs is carefully designed to make life easier for claims teams. The end result? More reliable, more scalable claims. To see how Wisedocs condenses the claims lifecycle through duplicate detection, speak with one of our experts today.