M&A and Affected person Knowledge Integrity: An interview with Rachel Podczervinski and Julie Pursley of Harris Knowledge Integrity Options

Merger and acquisition (M&A) exercise continues at a speedy tempo, posing a danger to knowledge integrity. As impacted hospitals and well being techniques search to consolidate their operations and applied sciences, duplicate and crossover information surge.  Whereas these errors current fast challenges, the longer-term concern lies in sustaining the accuracy and integrity of affected person knowledge throughout newly merged techniques.

We sat down with Harris Knowledge Integrity Options’ govt vice chairman, Rachel Podczervinski, MS, RHIA, and director of business relations, Julie A. Pursley, MSHI, RHIA, CHDA, FAHIMA, for an in-depth exploration of the obstacles confronting these tasked with sustaining the accuracy of affected person knowledge in a quickly consolidating healthcare surroundings.

Digital Well being Reporter (EHR): What are the important thing parts of and finest practices for knowledge conversion planning throughout M&A processes, notably regarding the Grasp Affected person/Particular person Index?

A important element is the meticulous evaluation and documentation of an MPI’s “present state” and the envisioned “future state.” This entails an intensive evaluation of database buildings for each current and forthcoming techniques, in addition to the evaluation of present and future medical document numbers (MRNs).

Moreover, partaking key stakeholders is important for creating a complete technique that addresses the varied wants of the group. Deciding on the correct instruments for duplicate and crossover remediation helps guarantee accuracy and integrity all through the MPI administration course of. Clear MPI knowledge extract specs are important for capturing all accessible identifiers for every affected person from the system. Lastly, conducting a frequency evaluation on key demographic knowledge fields can uncover patterns and outliers, reveal the construction of MRNs throughout amenities, and spotlight any structural changes wanted for the brand new system.

For testing and validation, confirm the accuracy of the extract by cross-referencing affected person info and conducting focused spot checks. Make sure that accounts marked for retirement are excluded from the extract to forestall duplicates from being created throughout subsequent evaluation. This reduces the workload for well being info groups and maintains knowledge integrity all through the extraction course of.

Develop methods to handle duplicate information, safeguarding knowledge accuracy and integrity.  Set up clear protocols and tips for resolving duplicates and reconciling crossovers. Lastly, outline a threshold for acceptable error charges and permit enough time to rectify errors earlier than that threshold is reached.

A number of finest practices can be utilized to make sure seamless integration:

• Prioritization – consider match standards, corresponding to weights, to allocate sources effectively for duplicate pair decision.
• Algorithm optimization – collaborate with the technical staff to higher perceive how potential duplicates are recognized and discover alternatives to refine studies.
• Audit MPI knowledge – assess the MPI’s present well being to establish areas for enchancment, whether or not by way of retraining, enhanced processes, or enterprise-wide requirements.
• Establish exterior sources – many instruments may help design enchancment methods, together with sources from AHIMA element associations, Mission US@ and its companion information, AHIMA’s naming coverage, and many others.
• Contain the registration staff – set up suggestions loops and enhance coaching supplies to strengthen their important function in MPI administration and organizational success.

M&A exercise inherently will increase the chance of disrupting the integrity of affected person knowledge as organizations merge disparate techniques. Strategic planning and finest practices that concentrate on aligning individuals, processes, and expertise can mitigate these dangers and assist navigate the intricacies of pre- and post-merger MPI administration with confidence and effectiveness.

EHR: Why are the Caring Algorithm and the People-in-the-Loop mannequin important facets of a affected person knowledge integrity technique, notably throughout M&A exercise?

Caring Algorithms adhere to an AI governance framework that prioritizes safeguards and promotes moral utilization whereas precisely figuring out people and supporting honest and unbiased id selections throughout numerous affected person populations. Importantly, Caring Algorithms incorporate a human-in-the-loop evaluation mechanism for these matches the place the algorithm shouldn’t be 100% sure. Doing so acknowledges each the restrictions of automated algorithms and the potential for automation to influence security and care coordination by introducing gaps in affected person identification.

Ideally, the human-in-the-loop evaluation leverages a wide range of instruments past the matching algorithm to validate discrepancies. These embrace guidelines concentrating on particular matching parts, knowledge standardization instruments, and third-party sources that offer historic demographics corresponding to names, addresses, and telephone numbers from credit score establishments and public utilities.

Harris Knowledge Integrity Options (HDI) lately analyzed 137,080 pairs (two affected person information) of potential duplicates. What we discovered highlights how preliminary selections made by third-party knowledge can change when a human-in-the-loop evaluation is included into the workflow.

• HDI modified the third-party remediation choice in 9.1% of the pairs.
• Of “sure” selections, 7.2% required modifications, as did 2% of “no” selections.
• Not altering the third-party choice would have created 512 (0.4%) overlays.
• Adjustments from “no” to “sure” concerned 2,490 pairs (1.8%).

These findings clearly point out that the presence of each Caring Algorithms and a human-in-the-loop oversight mechanism is important to restoring and retaining knowledge integrity earlier than, throughout, and after a merger.

EHR: What function do info expertise professionals play in correctly leveraging AI to resolve duplicate information throughout M&A actions and mitigate its influence on knowledge integrity?

Automation can cut back the necessity for human intervention, nevertheless it can’t utterly substitute it.  With out clear boundaries, governance, and safeguards, AI’s limitations can create gaps that require human evaluation and intervention.  Whereas people are liable for many—however not all—affected person identification errors, they’re important to figuring out, verifying, and correcting them.

AI-enabled applied sciences corresponding to EMPIs with superior algorithms, biometrics, MLMs, and predictive analytics with augmented knowledge are highly effective however imperfect. They might overlook inconsistencies and can’t make contextual judgments and selections based mostly on nuanced concerns. These require judgment and decision-making, creativity, innovation, and agility, in addition to emotional intelligence and empathy—decidedly human qualities which might be important to dealing with the complexity of affected person knowledge.

EHR: How do well being info professionals contribute to navigating complexities corresponding to particular person matching, error administration, and collaboration with registration companions throughout M&A?

A important function of well being info professionals is managing the accuracy and accessibility of affected person knowledge throughout a number of techniques, making them very important to efficiently navigating the complexities of sustaining knowledge integrity throughout M&A. Correct affected person identification ensures that well being knowledge seamlessly follows the affected person throughout the continuum of care post-merger. Well being info professionals are liable for establishing standardized knowledge seize practices and coaching workers to make sure that these requirements are persistently maintained.

Additionally they safeguard the continued integrity of the EMPI, enabling seamless info sharing throughout techniques, a functionality that’s particularly important for big, multi-facility well being techniques. As consolidation accelerates throughout the healthcare business, well being info professionals will proceed enjoying a central function in sustaining knowledge integrity and making certain that correct affected person info is obtainable at any time when and wherever it’s wanted throughout the continuum of care.

EHR: The place is the business with affected person matching IDs? Any motion? Any hope?

Whereas there is no such thing as a federal motion towards implementing a singular affected person identifier (UPI) within the U.S., Congress has launched bipartisan laws with the Affected person Matching and Transparency in Licensed Well being IT (MATCH IT) Act of 2025. This invoice goals to enhance affected person security and privateness by lowering affected person misidentification whereas selling interoperability.

AHIMA up to date and launched the Naming Coverage Framework 2023: Enhancing Particular person Matching With Important Demographic Knowledge Parts to assist seize standardized knowledge and help in figuring out sufferers in well being IT techniques. A nationwide workgroup reconvened this 12 months to replace the useful resource, offering a one-of-a-kind customary within the business because of the lack of a nationwide affected person identification and matching technique.

Different initiatives are additionally advancing affected person identification. Affected person ID Now launched a framework for a nationwide technique for efficient affected person identification and matching and continues working to take away legislative limitations that hinder the exploration of a singular affected person identifier. Moreover, Mission US@ printed a technical specification for amassing affected person addresses, supported by a companion information from AHIMA that gives operational steerage and finest practices.

EHR: What are among the issues that encourage you most about the place the business goes long run, based mostly on what you’re seeing by way of your work?

We’re impressed on daily basis by the chance to work alongside distinctive well being info professionals, together with these on the HDI staff and inside consumer organizations {and professional} associations. Their dedication to safeguarding knowledge integrity immediately influences the standard of care delivered to our sufferers, our family members, and ourselves.