Eliminating MPI/EMPI Roadblocks to Optimize IT, Advance Interoperability
By Jason Caturano, Vice President of Research & Development, Harris Data Integrity Solutions
Implementing advanced health IT remains a top priority among hospitals and health systems, with 88% of healthcare executives planning to increase their third-party technology investments in 2023-24. That’s according to a recent IDC/Redox survey, which tied increased IT spending to the push for digital transformation to reduce organizational waste, lower costs and optimize efficiencies.
Many of the clinical and clinical IT executives surveyed indicated they expect to see data reliability (40%) and availability (39%) improve with their technology investments. However, the reality is that unresolved patient matching and other data integrity issues will impede IT initiatives.
Clean patient data is the foundation for digital transformation. By ensuring that the MPI/EMPI has no duplicate or overlaid patient records, any technology initiative – such as deploying the latest automation or AI tools or switching to a new EHR system – can set the stage for an accelerated ROI and optimized benefits.
Dirty Data Damage
Data is the underpinning of health IT. Whether their purpose is to share, store, exchange, analyze or act upon it, today’s advanced technologies rely on quality patient data to accomplish the end users’ goals.
When that data is compromised – such as a duplicate-riddled MPI/EMPI – it negatively impacts the quality, performance, and reliability of AI models for clinical decision support and population health management and hinders interoperability by impacting standards-based information exchange like HL7’s FHIR.
There are three primary areas where interoperability and advanced health IT will be most impacted by dirty patient data:
Clinical: a dirty MPI/EMPI means clinical decision support and automated health screening tools do not have a comprehensive or accurate patient history and/or problem list to leverage in their analysis.
Value-based care: duplicate and/or incomplete patient records can skew the metrics that drive payment formulas and contribute to clinical errors, avoidable readmissions, and adverse events that reduce Medicare payments and/or reimbursements under value-based payment models.
Administrative: a contaminated MPI can hamper efforts to automate coding and billing or enact a robust AI-enabled risk-based audit strategy and increases the likelihood of incorrect claims or patient billing – resulting in lost revenues, longer days in A/R, higher costs for resources to correct the patient record and rejected/returned claims, and dampening productivity of an HIM team that is likely already under-staffed due to ongoing shortages.
Finally, in the case of migrating to a new EHR system, whether due to M&A activity or IT consolidation, if the MPI/EMPI isn’t cleaned of duplicates, overlays, crossovers, and other patient data integrity issues the merged systems will be compromised to an even greater degree than the originating system. This will, in turn, put other downstream systems at risk, and could potentially contaminate systems at other facilities with which data is shared.
Smart Mitigation Practices
Prevention is always the best strategy for ensuring the integrity of your patient data doesn’t impact the effectiveness of your health IT investments, beginning with establishing policies that govern how patient data is collected. This should include standardized formats for names, addresses, birth dates and social security numbers – including acceptable abbreviations.
Additionally, schedule regular assessments to determine the health of the organization’s MPI/EMPI. This includes identifying the current duplicate rate, comparing it to the desired duplicate rate – which should ideally align with AHIMA’s recommended 1% – and setting a rate that triggers the need for action.
Consider including technologies that support patient data integrity in any health IT strategy. Depending upon the organization’s specific needs, this could be a robust MPI management platform providing end-to-end patient identification solutions or a standalone solution that automates patient duplicate detection and resolution.
Further, because no technology can resolve 100% of duplicates or address every patient data integrity issue, seek to establish a relationship with a partner that can provide the “humans in the loop” to step in when automation isn’t enough. Bringing a partner in to clean up the organization’s MPI/EMPI prior to implementation of new or updated technologies can help accelerate ROI and optimize benefits.
Finally, understand how the quality of your patient data impacts or is impacted by interoperability initiatives such as TEFCA and mandates like information blocking prohibitions so proper action can be taken to optimize benefits and minimize the risk of enforcement actions. Tasking someone to stay current on regulatory and other changes can ensure the organization is always prepared.
Keeping it Clean
No data is perfect, yet reliable patient data is imperative when it comes to optimal use of advanced technologies. A clean MPI/EMPI is the first pillar of a strong health IT foundation.
Taking steps to resolve duplicate and crossover records and putting the policies in place to maintain data integrity will eliminate a significant obstacle to gaining full value from the AI, automation and analytics tools designed to improve care, maximize revenues, and protect patients.