An Enterprise Master Person Index Enables Accurate and Consistent Identity Data

By Jitin Asnaani, Chief Product Officer, Rhapsody
LinkedIn: Jitin Asnaani
LinkedIn: Rhapsody

Healthcare is the world’s fastest-growing source of data. This wealth of information originates from many diverse sources, such as hospitals, retail clinics, provider offices, wearable devices, etc., and holds immense potential to revolutionize healthcare. However, the sheer amount of information generated and the variability of sources increases the risk of duplicate, inaccurate, incomplete, or inconsistent identity data.

This can result in numerous hurdles, including delays in treatment (leading to potentially life-threatening patient safety issues), compromised care, increased legal risks, reimbursement delays, and operational inefficiencies. Furthermore, these challenges can erode patient and clinician trust, making it difficult to implement patient-centered initiatives and ultimately resulting in revenue loss.

Accurate identification is critical to optimizing experiences

With healthcare data, there is only one constant: the patient. An individual’s data should remain consistent and reliable whether they visit a lab, imaging center, wellness clinic, provider’s office, hospital, or vaccination center. Each person is unique, and positive care experiences require targeted and accurate data.

Unfortunately, studies indicate that errors in matching records to the correct person occur alarmingly frequently, up to 50% of the time. Moreover, the financial impact is substantial. The average large hospital can spend $1 million annually fixing the duplicate data in person records. 35% of all denied claims result from inaccurate patient identification, costing the US healthcare system over $6.7 billion annually.

The role of an enterprise master person index in addressing identity challenges

To overcome these challenges, healthcare organizations can leverage an enterprise master person index (EMPI) to address the complexities of identity management. By providing a centralized index that associates common records, an EMPI ensures that identity data remains consistent and accurate across disparate systems, enabling the delivery of higher-quality care and health information exchange, more engaged patients, improved business insights and analytics, and reduced costs.

According to the American Health Information Management Association (AHIMA), the stakes for patient identification are high—and EMPI technology can provide a foundation that helps accurately identify and engage people, no matter where they present. Furthermore, Gartner describes EMPIs as crucial tools for reconciling identity and addressing medical record-matching challenges.

This not only enhances patient safety but also streamlines operations and fosters organizational growth. However, not all EMPI solutions are created equal. Healthcare organizations should look for an EMPI explicitly designed for healthcare that supports future integration and interoperability, is scalable, does not comingle third-party reference data, leverages recent advances in machine learning, minimizes duplicates, offers deployment flexibility (on-premises and cloud), and prioritizes privacy and security. Ultimately, an EMPI’s best value is when used in a complete digital health enablement platform with comprehensive health data management capabilities, including other critical solutions such as integration and semantic technologies.

Utilizing AI for enhanced identity data governance

Identity data governance has become resource-intensive as healthcare information is created at an accelerating rate. Therefore, leveraging an EMPI alone might not be enough to support all use cases. Healthcare organizations can also benefit from advanced EMPI solutions that leverage Artificial Intelligence (AI) and Machine Learning (ML) to automatically link person records, using the organization’s data quality preferences and guidelines to ensure consistent and transparent data governance practices. This, in turn, enables healthcare organizations to achieve unprecedented accuracy and efficiency in identity management while resolving data quality issues and creating a more comprehensive view.

Using a neural network-based model trained with data steward tasks, AI technology can mirror human decision-making to resolve data linking and quality issues, automating preferred actions and improving downstream credibility. By automating these data stewardship tasks, AI-driven EMPIs ensure consistent decision-making, reducing the workload on data stewards and consumers like clinicians.

As a result, healthcare organizations can achieve lower duplicate rates, create higher-quality data, build a strong foundation for managing data effectively, apply AI and ML for better decision-making, and ensure that critical healthcare systems speak the same clinical data language.


With healthcare data rapidly expanding, ensuring the integrity of identity information is critical. Healthcare data must be matched, accurate, and available—in the right context—for the person using and receiving it. Highly accurate and current person data unlocks new possibilities for improving patient experiences, clinical outcomes, and operational efficiency. Driven by recent advances in interoperability, it also leads to opportunities to advance value-based care initiatives, digital health adoption, and other innovative programs.

EMPI solutions, augmented by AI technologies, offer a robust foundation for achieving accurate and consistent identification across the healthcare ecosystem. By embracing these innovative solutions, healthcare organizations can increase accuracy, consistency, and reliability in an increasingly interconnected technology landscape.