By Randy Jones, business development, ARGO.
The healthcare industry has a dupe problem. Today, on average, providers are seeing almost one in five of their patients’ records contain duplicates (meaning that two or more records are in existence with a variation of a patient’s name), according to a report by Black Book. This represents a significant threat as it can potentially lead to inaccurate billing and compromised patient safety. For years, providers have invested heavily in technology and systems designed to improve operational efficiency (while also mitigating the number of duplicate records) yet the problem persists.
According to the same report by Black Book, duplicate medical records cost an average hospital $1.5 million annually – and those are 2017 numbers, so today’s impact is even higher. The average cost of repeated medical care due to inaccurate patient identification with a duplicate record is roughly $1,950 per inpatient stay and more than $800 per emergency department visit. Likewise, A study from Boston Children’s Hospital estimates that one in three patients received duplicate tests because of duplicate health records.
It seems like a simple enough problem to solve, so why is it still so pervasive? As with so many issues in the complex world of healthcare, there is no single cause to the problem. Most commonly, the origin of duplicate records can be traced to a rushed patient intake experience — one that often leads to human error like typos; misunderstanding words or phrases due to language barriers and accents; or harried friends and relatives scrambling to remember information in an effort to assist loved ones in medical distress.
Additionally, patient name changes, due to common instances like marriage and divorce, aren’t often reported to healthcare providers in the expedient manner that they are with other agencies. Combine these factors with infrequent patient visits and the data quickly becomes inaccurate, resulting in duplicate records.
Pressure to act
As if these factors aren’t enough, the Office of the National Coordinator for Health Information Technology (ONC) has published industry-wide patient matching error goals of 2 percent by 2017, 0.5 percent by 2020 and 0.01 percent by 2024. For the many organizations that have yet to achieve the stated 2017 goal, the far more stringent 2020 standard presents a daunting challenge.
Although there is no mandate or enforcement mechanism attached to these goals at present, it’s not hard to envision the government taking a more aggressive approach in the absence of demonstrable industry-wide progress. The hard truth is that many organizations do not currently have plans in place that would even make it possible to demonstrate progress. Many continue to leverage the same processes and legacy technology that have been in place for years and find themselves no closer to meeting the ONC’s deadlines.