Readers Write: The Importance of Well-Managed Patient Identity Queues

The Importance of Well-Managed Patient Identity Queues
By Megan Pruente, RHIA, MPH

Megan Pruente, RHIA, MPH is director of professional services for Harris Data Integrity Solutions of Niagara Falls, NY.

Identity queue management is an important aspect of an effective value-based care strategy. It lays the foundation for establishing an effective person index, minimizing overlays, and facilitating streamlined care coordination. Left unresolved, backlogged work queues can have costly implications for patient care and safety, as well as revenue integrity.

However, many provider organizations are struggling to stay ahead of burgeoning identity error queues, with health system clients reporting that weekly error tasks have more than doubled. At one health system, the volume of potential overlays queue swelled from 2,000 per week to more than 5,000 per week over the course of just a few months, while another organization found itself dealing with a backlog of 100,000 identity interface errors. The health information management (HIM) director at a third health system shared that his team evaluated up to 400,000 potential overlay tasks in the last year to identify just 60 true overlays.

Many HIM departments lack the staff resources and experience that are necessary to address this volume of mismatched data, and the backlog continues to grow. What’s more, many hospitals and health systems may not be catching potential overlays or identity interface errors because their EHR systems lack the functionality or tools that alert end users to such errors.

Blame for this surge in errors can be traced back to several events, starting with the pandemic. The rapid uptick in adoption and use of patient portals, implementation of self-registration processes, and internal workflows to accommodate telemedicine and vaccination appointments led to a sharp increase in overlays, duplicates, and other identity-related errors. Exacerbating this were staffing shortages created by illnesses, caring for sick loved ones, and an exodus of healthcare professionals due to fears of COVID-19 and burnout, an ongoing challenge that has identity management teams stretched to the breaking point.  Another factor involves changes to fields that are used to capture patient identity data, such as expanded options for sexual orientation and gender identity (SO/GI).

Ironically, some of the blame also lies with the EHR workflow tools that were designed to address patient identity management challenges. For example, Epic’s EMR includes a Possible Overlay Queue, a useful workflow tool that identifies and segregates potential overlays until they can be analyzed and either verified or cleared from the queue if it is determined not to be a true overlay. However, its sensitivity to any change to the patient’s demographic information, whether significant (a name change or new Social Security number) or routine (adding a middle initial or completing SO/GI fields) can sometimes lead to an increased backlog volume as every alteration triggers an overlay task to be added to the queue.

Similarly, when data such as order results and documents cannot be filed automatically into a patient’s existing medical record due to a mismatch or fuzzy match on demographic data points, medical record number (MRN), or other patient-level data point, these messages error out and must be manually reviewed and resolved. When left unresolved, these errors can lead to repetitive orders, duplicate tests, and other issues that could result in denied claims.

The challenge for HIM is that some EHRs do not have interface error work queues that streamline resolving such errors. Even when EHRs do offer such functionality, staff often struggle to keep up with the high volume of errors requiring attention.

The reality is that managing identity error backlogs is a time-consuming and resource-intensive task that few HIM departments have the capacity to handle. The intricate nature of these processes requires meticulous attention to detail and often diverts focus from more critical tasks and strategic initiatives. Exacerbating the challenge, new tools and reports being released to HIM designed to help address duplicate, overlays, and interface errors are contributing to the increase in workload with the same or fewer resources to review the errors.

Healthcare organizations can take a number of actions to reduce the volume of identity errors and prevent backlogs from spiraling out of control. These include:

• Invest in staff training. Provide comprehensive training to enhance HIM professionals’ identity management skills. Keep staff updated on changes in patient data capture fields and the use of EHR workflow tools to reduce errors caused by lack of awareness.
• Prioritize staff resources. Allocate adequate staff resources to address identity queue backlogs and ensure that HIM departments have the capacity to handle the volume of tasks. Also, consider hiring additional staff or redistributing existing resources to focus on resolving identity errors and preventing the backlog from growing.
• Collaborate across departments. Foster collaboration between IT, HIM, and other relevant departments to collectively address identity management challenges. Also, establish cross-functional teams to develop and implement solutions that consider the perspectives and requirements of different stakeholders.
• Outsource MPI management. Evaluate the cost-effectiveness and efficiency of outsourcing MPI management to a vendor or partner with experienced staff overseen by credentialed professionals. Short-term MPI management support should also be considered during M&A activities to ensure integration of clean data and quick turnaround times.
• Implement robust data governance. Establish a strong data governance framework to ensure the accuracy and integrity of patient data throughout its lifecycle, including ongoing quality checks to ensure the accuracy of any automation and other patient matching tools, including AHIMA’s Naming Policy Framework and the Project US@ AHIMA Companion Guide.
• Enhance EHR workflow tools. Collaborate with EHR vendors to fine-tune sensitivity of algorithms to reduce false positives in the identification of potential duplicates and overlays and to customize workflow tools that better align with the organization’s specific needs and processes.
• Use third-party data. Use third-party data like historical addresses and phone numbers that are obtained from outside vendors to help prevent and accelerate remediation of overlays.
• Invest in enhanced patient matching tools. Biometrics and other patient matching technologies can prevent the creation of identity errors by improving accurate identification during front-end registration processes.
• Automate data matching processes. Explore, implement, and closely monitor advanced technologies such as machine learning and AI to automate matching and reduce the reliance on manual reviews. Integrate systems that allow for automatic filing of order results and documents into patient records to minimize errors related to mismatched data.
• Use analytics for insights. Use analytics tools to gain insights into patterns and trends that are related to identity errors and to identify root causes.
• Regularly monitor and evaluate processes. Implement a continuous monitoring system to track the performance of identity management processes and identify areas for improvement. Regularly evaluate the effectiveness of implemented solutions and work closely with IT staff or vendors to optimize processes, as even seemingly minor AI errors can have significant and widespread impacts.
• Don’t overlook the patient’s role in maintaining clean patient identity queues. Implement patient education programs to encourage accurate self-reporting of demographic and other relevant information. Also, promote to patients the importance of maintaining up-to-date and accurate information, including creation of talking points to help staff engage in these discussions.

Unresolved identity errors pose a significant threat to a hospital’s financial health. These errors can lead to reimbursement delays, costly repeat studies, and denied claims, creating unnecessary financial strain. A backlog can also impact patient care by creating gaps in medical histories, unnecessary delays in diagnosis and treatments, and risks to patient safety.

To avoid these impacts, patient identity error queues should be part of an overall MPI management strategy. Whether outsourcing to an outside MPI vendor or increasing internal resources to put in place workflow processes for eliminating the backlog and sustaining ongoing management, hospitals and health systems must prioritize patient identity queue management. Doing so empowers healthcare institutions to optimize operations that are being dragged down by unresolved patient identity errors, generating measurable cost savings, mitigating financial setbacks, and creating room for strategic investments in areas that truly matter.