Critical Factors for Successful Post-Merger Data Interoperability

41

Part 2 of 2

By Karen Proffitt

Part One of this two-part series on patient identity management best practices looked at strategies for mitigating errors during data conversion. In Part Two, we examine the factors that are critical to successfully achieving clinical data interoperability. 

While the debate underway at the national level focuses on a national patient identifier and what it will take to achieve nationwide interoperability, closer to home healthcare organizations need to keep accurate patient identity and data exchange within their own walls at the forefront. 

Specifically, provider organizations should focus on linking all a patient’s health information across the enterprise with a single unique identifier to enable safe, appropriate care decisions and facilitate accurate billing and reporting. Also needed are processes for ongoing evaluation of possible duplicate records and associated reconciliation efforts, and a medical record number (MRN) synchronization model so that core downstream systems are in sync with the “source of truth” system, typically an EHR or EMPI, which plays a key role in achieving internal interoperability. 

Outlined below are the factors that can make or break post-conversion interoperability.  

Messaging and MRN Synchronization

For example, in optimized HL7 ADT data flows, it is the source-of-truth system that, when triggered by a specific event like patient admission or discharge, transmits messages to downstream systems via established standard protocols. Thus, information sharing requirements need to be carefully evaluated with the key data owners of all systems, including downstream and financial systems and data warehouse/analytics teams.  

Another consideration for effective MRN synchronization is patient merge messaging and downstream systems. When duplicate records are resolved in the source-of-truth system, immediate manual corrections are often required in downstream systems, many of which don’t have the technical capability to process merge messages or aren’t configured to do so. 

An in-depth assessment will determine which downstream systems need to be synchronized with MRNs. The information gleaned during this evaluation will also help identify next steps for enabling merge processing functionality wherever appropriate. 

MPI Data Synchronization

If a source-of-truth system has not been established, core inpatient and ambulatory registration systems must stay in sync via bi-directional interfaces to present a holistic view of all patient information within one unique identifier. If an EMPI application is being utilized, active integration between the registration system and the EMPI prior to adding new MRNs is an excellent strategy. This allows the registrar to search the EMPI using an advanced patient matching algorithm before creating a new MRN in the registration system. 

With bi-directional data flows, it is imperative that all system users follow the same standard procedures for capturing demographic data. Otherwise, new MRNs can be inadvertently created in the source-of-truth system when data fields are different due to exact, deterministic matching logic in place which rejects matching/linking if incoming demographics are not identical. 

Avoid Assumptions

Even when all precautions are taken, all may not always be well when it comes to information exchange. It can be a critical mistake to assume that received messages are always processed—not to mention the challenges to which systems are exposed with highly configurable interfaces. 

Thus, the final factor of successful interoperability is testing, including a comprehensive review of all messages that “error out.” This allow issues to be resolved and errors minimized once interfaces are live. 

When data mapping isn’t adequately designed, and when testing is not conducted, the result will be compromised data integrity and diminished interoperability.

Karen Proffitt is Vice President of Industry Relations for Just Associates, a nationally recognized leader in patient matching and health information data integrity and management.

LEAVE A REPLY

Please enter your comment!
Please enter your name here

10 − 8 =

This site uses Akismet to reduce spam. Learn how your comment data is processed.