By Beth Haenke Just, MBA, RHIA, FAHIMA, Founder, CEO &
Karen Proffitt, MHIIM, RHIA, CHP, Vice President of Industry Relations/CPO, Just Associates, Inc.
Twitter: @PatientMatching
Twitter: @BethJust13
Twitter: @kproffitt2
An overlay is one of healthcare’s most dangerous misidentification problems, in part because its infiltration into the medical record system can be so subtle that it often goes unnoticed until it’s unleashed in the form of an adverse event, HIPAA violation, or billing error. The co-mingling of two patients’ information within one medical record (overlay) and the dangers it presents have intensified with the proliferation of electronic health record (EHR) systems capable of rapidly infecting multiple internal and external systems with erroneous data. Over-reliance on technology centric solutions to resolve possible duplicates has compounded the problem.
The American Health Information Management Association (AHIMA) puts the average duplicate rate between 8 percent and 12 percent. Meanwhile, an analysis of projects involving overlays for which Just Associates has been engaged reveals a sizable increase in the number of overlays in facilities alone, from 3.56 percent in 2012 compared to 6.16 percent in 2016.
The challenge for health information management (HIM) professionals tasked with maintaining the integrity of patient records is three-fold: 1) identifying and resolving existing overlays, 2) determining the root cause of overlays and 3) putting in place policies and procedures that will prevent the creation of new overlays.
Failure to accomplish these objectives is not an option, as overlays are a primary source of patient safety errors, lost revenues and have high costs to correct.
The Birth of an Overlay
Overlays are most often created at the time of registration, when an incorrect patient record is selected, core demographic information is changed, and a new visit is added. This leads to co-mingled demographic and clinical information for the two patients involved in the overlay.
Technology can exacerbate the overlay problem. For example, when two records are auto-linked using established patient matching algorithm logic, either routinely or for a specific MPI conversion, some percent of those linkages will result in an overlay situation. It happens often, for example, with twins’ medical records. Additionally, overlaid records can be easily generated when relying solely on third party data and patient matching thresholds that are set too low.
Overlay creation can also be traced back to multiple departments. One study published on an eight-hospital multistate healthcare organization found that most of that health system’s errors happened in the emergency department (ED) and, to a lesser extent, in registration, scheduling and ancillary areas, such as lab and radiology (Journal of AHIMA, September 16, 2017). These findings, the researcher wrote, “prompted a deeper dive in the data, revealing that the roles of users who created these errors varied and were not limited to registration staff. Indeed, many clinical users who perform initial patient search and selection duties had created overlay errors.”
The hospital system had begun tracking and keeping detailed statistics on overlay errors for five years, beginning with the implementation of an EHR system. In doing so, it amassed an impressive bank of data from which researchers could draw on for a study of the problem. The findings are an important addition to the limited body of knowledge on overlay errors, providing important insights into their prevalence, cause, identification, and mitigation.
Working from a considerable sample size of 555 errors for the five-year study period, researchers determined an error rate of one in every 10,734 admissions—equivalent to more than nine errors per month with potentially far-reaching effects—of which 97.5 percent were caused by user oversight or error. The study also identified an upward trend in overlays, which researchers attributed to growth of the health system and utilization of better error identification tools that reveal more issues than manual methods. They note that “overlay errors ‘hide’ in data and are not caught until later downstream, if at all. This trend showed that some of these EHR tools prove their worth when utilized regularly.”
Indeed, while the majority (54%) of overlays were found by registration users, the use of EHR tools, such as a demographic data change report, came in second at 31 percent. Clinicians were a distant third, identifying 6 percent of errors. Patients also found overlay errors via patient portals, which allowed them inappropriate access to highly-sensitive protected health information (PHI) and laying the groundwork for HIPAA violations.
In terms of the length of time an overlay existed before being identified, proactive EHR tools found the bulk of overlays within 10 days of occurrence. This is important, because the longer an overlay goes undetected, the less likely it will be found. Once identified, most errors were fully corrected in 30 days, although the health system struggled to generate bills within 90 days. Noted the researcher: “This was interesting in that it showed just how much reimbursement may have been lost. It also showed the resource intensity necessary to correct even one overlay error.”
The High Costs of Overlays
A wide net is required to determine just how costly overlays are, as few studies have been done to establish industry averages. Factors contributing to the full financial impact of an overlay include denied and delayed claim filing, lost revenues and the resources required to identify and correct the error.
Time is a huge factor when looking at resources required to correct overlays and often depends on the type of record in question. For paper-based overlays, it can take 60-100 hours. For EHR-based errors, it can take months, depending upon the complexity of the system and the amount of clinical documentation involved.
A survey by the College of Healthcare Information Management Executives (CHIME) further found that respondents typically had at least two people dedicated to “data cleansing,” which includes overlay correction.
In the case of an overlaid electronic record involving twin girls at a pediatric medical center, it took 16 staff members three months to correct the problem. In addition to the cost to correct the overlay, the facility lost nearly $43,000—the amount the hospital had to absorb because an overlay record prevented officials from piecing together accurate patient information to bill the insurer within the 90-day bill filing requirement.
In terms of the impact of overlays on revenues, in a fee-for-service environment, the issue centers on delays in issuing claims due to problems with patient demographic data integrity. When a facility is unable to combine bills for visits occurring within 72 hours, they risk scrutiny from Medicaid/Medicare. Overlays also make it difficult to identify patients who have payments due or who may already have bad debt.
For risk-bearing entities like Accountable Care Organizations (ACOs), the threat to providers is even greater. Overlays inhibit their ability to longitudinally trend data accurately for one patient to assess care received and determine the appropriate course of subsequent care. This also means they cannot accurately assess quality and effectiveness of services provided due to inaccurate views of specific provider quality and efficiency. All of these will impact an ACO’s ability to report metrics and earn incentive payments.
Part two of this two-part series will examine methods of correcting and preventing overlays.