Patient matching issues that result in duplicate records cost hospitals $1.5M a year, at an average of $1,950 per patient, and the U.S. healthcare system over $6 billion annually, according to a new survey by Black Book Research. The poll of 1,392 health technology managers found that before implementing an enterprise master patient index (EMPI) for managing patient identification, duplicates accounted for 18 percent of an organization’s records. Respondents utilizing EMPI technology reported accurately identifying patients at the point of registration 93 percent of the time and at a rate of 85 percent for records shared outside the organization. Those hospitals not using an EMPI reported a match rate of just 24 percent when exchanging medical records with out-of-network providers.
As robust data sharing and health information exchange proliferates, incomplete and duplicate records will remain a significant barrier to informed clinical decision-making, population health management and a better patient experience, as well as a threat to cost, quality and safety.
Duplicate patient records often occur as a result of multiple name variations, data entry errors, and lack of data standardization processes. A typo or absence of a single digit in one’s birth date, address, phone or social security number only compounds the issue. Patients move, marry, divorce and visit multiple providers in their community—where new records are created and the potential for duplicates grows.
The reliance on EHR matching functionalities to manage patient populations perpetuates the issue of patient identification. Master patient indexes (MPI) within EHRs are exceedingly limited in their ability to compare records from disparate sources, predominantly those outside the organization. EHR systems inadvertently duplicate patients’ information, creating multiple individual records since they lack the sophisticated algorithms to compare and link records across multiple data sources and geographic locations. When sent to downstream systems, these duplicate and disjointed records trigger further harm, leading to skewed analytics and reporting, denied claims and billing inaccuracies, increased risk and cost from redundant tests and procedures, and medical errors.
In health IT, enterprise patient identity management refers to a fully-integrated patient record that moves beyond a single EHR. An “enterprise” master patient index (EMPI) is a centralized, cross-platform solution designed to link and reconcile records in real-time from diverse systems and settings of care, including HIEs, ACOs, radiology groups, outpatient clinics, physician practices, labs and rehabilitation facilities to name a few. When coupled with the benefits of cloud, an EMPI that is continuously maintained and updated can enhance the scalability and performance of the patient matching engine.
An EMPI provides superior matching accuracy over an MPI since it compares multiple demographic fields by leveraging both probabilistic and deterministic matching algorithms to account for minor variations in patient data. Additionally, the EMPI allows for higher accuracy in identifying individuals and a considerable reduction in remediation efforts by recognizing more records as a match or potential match. In contrast, MPIs have very limited data fields for patient matching, which creates an influx of erroneous MPI data and risk of associating two different individuals with the same record. Therefore, MPIs must continually undergo clean-up to resolve patient record discrepancies and missing demographic data fields.
Unlike an MPI, an EMPI can provide extensive data stewardship capabilities to maintain the integrity of the patient record and minimize manual remediation by health information management (HIM) professionals across the enterprise. By pre-defining workflows and thresholds, an EMPI can not only link records automatically, but flag potential duplicate for remediation and review. The EMPI is also able to send notifications downstream to keep the master patient record synchronized and facilitate accurate data exchange in and out of the network.
Achieving the goals of the Triple Aim can only flourish when patients are accurately and consistently matched with their data. To ensure organizations are providing a complete view of individuals across the care continuum, medical records must be free of errors, duplicates and incomplete information. Superior identity management technology, like an EMPI, yields immediate value in data interoperability and integrity to make quality interventions possible and support the requirements of coordinated, accountable, patient-centered care.
[callout title=”Download” link=”https://www.healthitanswers.net/white-papers/download-patient-matching-cloud/” new_tab=”yes” icon=”icon-download” animation=”left-to-right”]Download “Moving Patient Matching Capabilities to the Cloud: How a cloud platform can improve patient data management.’ by NextGate[/callout]