Telehealth Explosion adds to Patient Matching Woes
By Karen Proffitt, Vice President of Data Integrity Solutions, MHIIM, RHIA, CHP
The explosive popularity of telehealth to ensure ongoing access to care as COVID-19 ravaged the nation has added to the growing list of ways patient matching issues have impacted the healthcare industry’s response to the unprecedented global pandemic—and escalated the sense of urgency to identify meaningful solutions.
Nor is anyone anticipating telehealth’s popularity will wane anytime soon. In 2020 Virtual Care Forecast, US, released in October 2020, Forrester estimates that virtual visits for general medical care will exceed 440 million in 2021. That is a relatively small decline from 2020 projections of 481 million visits, considering that pre-pandemic expectations for the year were just 36 million telehealth visits. High patient satisfaction with telehealth is also a factor. A recent HIMSS report, Consumer Perspectives on Telehealth, indicates that 77% of patients are willing to use some form of telehealth post-pandemic and 41% citing it as their preference in specific circumstances.
The accelerated adoption of telehealth has revealed that it’s not immune from one of healthcare’s most intractable problems: patient identification errors that lead to duplicate and overlayed medical records. Anecdotally, a number of our clients have shared that telehealth has led to a bump in duplicate records. This typically happens when patients create new accounts to self-schedule telehealth visits. When the new account doesn’t match an existing MRN, a duplicate record is created in the system for HIM to deal with.
As we’ve discussed in earlier posts, inaccurate patient identification is a common problem in healthcare, one that costs the average healthcare facility $1.2 million per year and contributes to everything ranging from denied claims and adverse events to duplicate testing and delays in diagnosis and treatment.
How common are patient identification problems? Very. About 18% of patient records are duplicates and approximately 1 in 5 are incomplete, including an estimated 40% of demographic data missing from commercial laboratory test feeds for COVID-19. This hampers efforts to gain control over the pandemic, as contact tracers rely on accurate and comprehensive information to locate patients, public health agencies rely on consistent, reliable, and reproducible data for reporting, and a widespread and safe vaccination program requires a consistent and accurate means of identifying individuals.
As the nation’s response to the COVID-19 pandemic continues to lay bare the plethora of challenges confronting healthcare when it comes to patient matching and identification, it is imperative that we take a deep—and realistic—dive into the possible solutions. Everything from a national patient identifier to USPS address formatting tools to stronger matching algorithms has been put on the table, and all have their merits. However, there is no magic bullet.
Ultimately, the cure for the industry’s patient matching woes will be a multifaceted approach that includes all these elements, along with industry-wide standardization, third-party data, and expert analysis and intervention.
