Electronic Health Reporter

By Beth Haenke Just, MBA, RHIA, FAHIMA, founder and CEO, and Karen Proffitt, MHIIM, RHIA, CHP, vice president of industry relations/CPO, Just Associates, Inc.

The introduction of overlays into a medical record system can be so subtle that they often go unnoticed until one causes an adverse event, HIPAA violation or billing error—making them a primary source of patient errors, expenses and lost revenues in hospitals today.

Caused when the information of two patients is co-mingled within one medical record, the dangers of overlays have intensified with the proliferation of electronic health record (EHR) systems, which accelerate the rate at which multiple internal and external systems can be infected with dirty data. Compounding the problem is an overreliance on technology-centric solutions to resolve possible duplicates.

The American Health Information Management Association (AHIMA) puts the average duplicate rate at between 8 percent and 12 percent. A more recent survey by Black Book found an average of 18 percent. Meanwhile, an analysis of EMPI cleanup projects Just Associates completed between 2012 and 2016 showed that as many as 1.3 percent of these possible duplicates are actually potential overlaid records.

When it comes to overlays, there are three challenges facing health information management (HIM) professionals tasked with maintaining the integrity of patient records: 1) identifying and resolving existing overlaid records, 2) determining the root cause(s) and 3) implementing policies and procedures that will prevent the creation of new ones.

The birth of an overlay

The most common way an overlay is created happens at the time of registration when an incorrect patient record is selected, core demographic information is changed, and a new visit is added. Occasionally, the records of two different patients are erroneously merged during the duplicate resolution process.

Overlay creation can also be traced back to multiple departments. A study in the Journal of AHIMA involving an eight-hospital, multi-state healthcare organization found that most of the errors happened in the emergency department (ED) and, to a lesser extent, in registration, scheduling and ancillary areas such as lab and radiology.

The hospital system that was the subject of the study had been tracking and keeping detailed statistics on overlay errors for five years, beginning with the implementation of an EHR system. This provided researchers with the rare opportunity to analyze a considerable sample size of 555 errors, from which they determined an error rate of one in every 10,734 admissions. That is the equivalent to more than nine errors per month, of which 97.5 percent were caused by user oversight. The study also identified an upward trend in overlays attributed to growth of the health system and higher utilization of error identification tools that reveal more issues than manual methods.

For example, 54 percent of overlays were found by registration users while data integrity change reports that made use of EHR tools found 31 percent. Clinicians were a distant third, identifying just 6 percent of errors. Patients also found overlay errors via patient portals, which could have allowed them inappropriate access to highly-sensitive protected health information (PHI) — access that could lead to HIPAA violations.

Proactive EHR tools found most overlays within 10 days of their occurrence, and most were corrected in 30 days. This is important because the longer an overlay goes undetected, the less likely it will be found. When it is found, the older overlaid record is much more time-consuming and expensive to correct.

The high cost of overlays

To determine just how costly overlays are, it is necessary to cast a wide net, as few studies have been done to establish industry averages. Factors contributing to the full financial impact of an overlay include denied and delayed claims, lost revenues and resources required to identify and correct the error.

Time is a huge factor in the costs associated with overlay correction resources. For paper-based overlays, it can take between 60 and 100 hours, while EHR-based errors can take months depending upon system complexity. 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,” including overlay correction.

One case involving twin girls at the Children’s Medical Center of Colorado took 16 staff members and three months to fix. In addition to the cost to correct the overlay, the hospital absorbed nearly $43,000 because officials couldn’t piece together accurate patient information to bill the insurer within the required 90 days.

Overlays can also have a negative impact on revenue. When a facility is unable to combine bills for visits occurring within 72 hours, they risk scrutiny from Medicaid and/or Medicare. Overlays also make it challenging to identify which patients have outstanding bills or who may already have bad debt.

The risks to providers and accountable care organizations (ACOs) is even higher as overlays inhibit their ability to track the patient’s care and determine the appropriate course for subsequent care. This also means they cannot accurately assess the quality of services provided to that patient. All of these will impact an ACO’s ability to report metrics and earn incentive payments.

Prevention requires diligence

Preventing overlays is challenging, particularly when EHR adoption has resulted in merging multiple MPIs and the pushing of erroneous information into multiple systems. The best approach is to implement a comprehensive overlay correction plan to guide the identification and repair process.

Overlay correction plans are complex but worth the time and resources. The first step is to assess the required time and available resources, starting by determining how many downstream systems are impacted by overlays and how long it will take to fix the issues.

The amount of time and resources it takes to repair each record varies. One large health system calculated that it can take eight hours of HIM resources alone to correct a single basic overlay. More complicated cases involving multiple visits can take anywhere from 16 to 30 hours.

Industry best practice dictates that HIM data integrity staff own the overlay correction process and be the main facilitators. However, HIM typically cannot perform all the required steps on its own. It is usually necessary to collaborate with teams from other areas, such as IT, clinical documentation, orders, pharmacy, providers, billing, etc., to correct existing overlays across all impacted information systems.

Certain departments require special consideration due to the nature of their work. Release of Information (ROI) is among the most sensitive because of the potential HIPAA violation if co-mingled information is released. As such, the ROI team should be alerted immediately when a request is made for documentation involving a suspected or confirmed overlay. This process can sometimes be automated, as some EHR systems can place a warning alert on effected records to let the ROI staff know when certain portions of the record are accessed.

Correction plans should also include the notification of patient billing, allowing a bill-hold flag to be placed on impacted accounts. This helps avoid inappropriate billing or release of records to payers. The department responsible for patient portal management should also be notified so access can be deactivated for both patients involved and then reactivated when the issue is resolved.

The HIM data integrity staff should also be alerted so charts involved in the correction process can be flagged and the best approach to reconciling data — the patient’s problem list, past history, current medications, allergies, etc. — can be established. Attending and ED physicians, physician assistants, nurses, and/or residents must be tapped to clarify which medical information belongs to each patient.

Finally, once the clinical/EHR records have been corrected, there should be additional key steps to cover re-analyzing the chart for deficiencies, coding, etc.

Best practices for prevention

Preventing the creation of new overlays is as important as correcting past ones. Training the staff on policies and procedures of creating or updating a patient’s record, especially when the patient is in-house, goes a long way toward limiting mistakes.

One effective method for preventing overlays is to require legal proof before updating a patient’s key demographics, e.g. name or date of birth. AHIMA recommends requiring a driver’s license, passport or other state-issued identification card at check-in, though that may not be a viable option for certain populations such as children and immigrants. Patients can also be asked to verbally state their name, birth date and address at registration. Adding photo identification to the EHR lets the staff quickly determine if the person they are speaking to belongs to the record they are viewing. Finally, comparing patient signatures on consent forms, developing guidelines around enrollment for patient portals and limiting change authority to HIM data integrity or patient access management team members can further limit the potential for overlay creation.

Leveraging the functionality available in your existing system is also a smart option. Many EHRs provide possible overlay reports. If no report is available, utilize an ADT audit that tracks all key demographic changes for each day. Many EHR systems have a data-change report that is helpful, although it can be cumbersome because it provides all data changes, including when a value is changed from a default data element to real data.

Evaluate incoming interface matching logic and ensure the proper algorithms are deployed to uncover more overlays as early in the process as possible. However, given the previous discussion around technology’s role in creating overlays, it is important to use it prudently. Avoid auto-linking any same-system duplicates, even at very high thresholds and avoid auto-linking any cross-system duplicates using only name and date of birth. Auto-linking cross-system duplicates should only occur using exact match criteria of at least five identifiers to ensure overlaid records are not created.

Finally, be cautious when using third-party data. A significant percentage of possible duplicates that third-party data provider algorithms indicate to be a true duplicate can often be determined as a non-duplicate when a quality assurance process is employed. A quality check of more than 137,000 records by Just Associates identified that 9.1 percent of the decisions by the third-party data vendor were changed. Technology, after all, is not infallible; there is no magic button.