They cause problems with billings and collections, hurt relationships with payers, and force hospital staff to spend countless hours correcting errors.
Much of the discussion on problems with duplicate records centers on the medical risk they pose for patients, but they also incur financial and administrative costs for healthcare systems.
Duplicate records cause problems with billings and collections, hurt relationships with payers, and force hospital staff to spend countless hours finding and correcting errors and resubmitting claims.
According to a 2021 survey of 1,500 health technology managers by Black Book, an estimated 35% of all denied claims resulted from inaccurate patient identification or information. That cost the average hospital $2.5 million in 2020 and the U.S. healthcare system over $6.7 billion annually.
Duplicate records also cause hospitals to inaccurately bill patients, which leads to financial distress, weakens the relationship between patient and provider, and can even expose the healthcare system to charges of fraud and the resulting legal action.
These problems are even more acute now at a time when hospitals are struggling with shrinking revenues and rising labor costs that threaten their viability. The American Hospital Association projected 2022 to be the worst financial year for hospitals since the start of the COVID-19 pandemic, with operating margins declining by as much as 133%.
In addition, denied claims are on the rise, according to consulting firm Kaufman Hall, which surveyed healthcare leaders in 2022. Around 67% said they’d seen an increase in denials over the past year, up from 33% in 2021.
And even claims which are accepted are being paid later, according to consulting firm Crowe, which found that in the summer of 2022, hospitals on average collected 94% of their expected revenue within six months, down from 97% the previous year. Also, accounts receivable that aged over 90 days went from 32% in January 2021 to 37% in August 2022.
How duplicate records are created
Healthcare is full of difficult and demanding processes, from diagnosis to surgery. From the outside, it doesn’t seem like properly identifying patients and keeping their medical records straight should be one of them.
But it has been for decades. If anything, the digitization of records has worsened it by making it easier to duplicate and share records instantaneously. Duplication rates vary wildly by healthcare system, but we commonly see a rate of 10%, with some hospitals as high as 20%.
Duplicate records are defined as two or more records assigned to the same patient in a healthcare system. Sometimes, a patient’s record is mixed with data from another patient, creating a combined record, or overlay, which can be more dangerous than a duplicate.
Duplicate records are created by data entry errors, inaccurate or inconsistent information provided by patients, mutable identifiers, and poor data transmission among different systems with a hospital or between different healthcare systems.
In addition to posing a danger for patients, duplicate records and overlays make it difficult for healthcare systems to accurately measure their performance and quality metrics. Low-quality data also degrades any research for which it is used.
The good news about the financial and administrative problems caused by duplicate records and overlays is that they can be eliminated by the labs and hospitals that create them.
The first solution should be deployed when a patient enters a healthcare system for the first time and at every subsequent registration. The patient information required at registration should be extensive and standardized throughout the system (and, ideally, throughout healthcare). It should have as many unique identifiers as possible: full name, address, phone number, DOB, Social Security number, etc. Of course, some of this information can change so it’s important that updates be recorded as soon as possible after they occur. This can go a long way toward eliminating the creation of duplicate records.
However, while more accurate and detailed registration can block many duplicate records, it’s inevitable that some will occur, regardless. That’s why healthcare systems need to scrub them from their databases. This is best accomplished by creating an electronic Master Patient Index (EMPI) for all patients in the system.
Advances in AI and machine learning allow automation technology to reduce human intervention and error in patient matching. To eliminate duplicates and overlays, a multilayered process first runs data through the EMPI to identify and merge obvious duplicates, while a second layer uses machine learning to correct errors. Referential matching and data enrichment then further reduce duplication. Lastly, data analytics resolves remaining duplicates and checks for overlays. Previous steps are then rerun. From there, staff can address any unresolved questions.
Using intelligent automation to improve health data produces better results faster than manually performing the tasks. It’s possible to reduce duplication rates to less than 1%.
Eliminating duplicate records and overlays is not only the right thing to do for patient safety, it also boosts healthcare systems’ financial health.
This article originally appeared on Chief Healthcare Executive®.