Highlights from AHIMA’s 2023 Naming Policy Framework
By Rachel Podczervinski MS, RHIA, Vice President of Professional Services for Harris Data Integrity Solutions
The lack of standardized naming policies continues to have multiple impacts on the healthcare industry, contributing significantly to inefficient and inaccurate patient identification and matching processes that can affect care quality and patient safety. It also limits the success of large data set migrations and impacts the effectiveness of EHR and other health IT systems and tools.
To help address these challenges and advance the healthcare ecosystem’s “obligation to capture and manage high-quality data where integrity is foundational to health data being accurate, complete, and timely throughout its lifecycle,” AHIMA has released AHIMA Naming Policy Framework 2023: Enhancing Person Matching with Essential Demographic Data Elements. I’m proud to have been involved in the creation of this updated framework, which provides everything HIM professionals and healthcare organizations need to know about person matching in health IT.
The goal of AHIMA’s updated demographic data element framework is to assist in identifying and matching patients in health IT systems. Accurately matching patients to their medical records is an ongoing challenge for the healthcare industry, one that contributes to incomplete or duplicate patient records. These, in turn, can lead to:
Delayed, inappropriate, or unnecessary care
Reduced utility and trust in patient data for research
Inaccurate analysis and reporting
Inefficiencies in care coordination, prior authorization, and billing
Challenges with fraud detection and unauthorized disclosures
Decreased or limited interoperability
According to AHIMA, the standardized framework serves as a “rising floor” that will evolve over time with advances in technology and operational procedures to ensure it remains relevant and effective. It further notes that “the guidance and best practices in this updated framework build upon existing industry guidance and practices to standardize person(s) demographic data elements.”
The framework also recognizes the evolving healthcare ecosystem by acknowledging the changing landscape of HIM, where patient demographic data goes beyond traditional MPIs/EMPIs. With entities collecting and sharing EHI, additional data elements are needed for effective identification, matching, and management of health records.
I encourage all HIM leaders and professionals to review and put the Framework into practice to help resolve what has thus far been an intractable problem across the healthcare ecosystem. It can be accessed here.