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HSBlox Unveils AI-Powered EMPI Solution to Ensure Secure Patient ID Matching & Sharing

by Fred Pennic 06/26/2018 Leave a Comment

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Medical Records_Healthcare Data_Health Data

HSBlox’s new Enterprise-wide Master Patient Index (EMPI) utilizes machine learning to improve patient safety with secure, accurate sharing of patient data throughout the healthcare landscape.

HSBlox, a healthcare blockchain-focused company that is bringing innovation and transparent economics to the healthcare ecosystem, today announced the launch of its SmartMPI solution, which utilizes machine learning to provide next-generation patient ID matching and secure, transparent sharing of patient data across the care continuum, solidifying the foundation for longitudinal patient records. The solution’s high level of accuracy in patient identification contributes to decreased preventable medical errors, better medication management, and increased time and cost savings for providers due to ease of data sharing and the avoidance of duplicate records.  

The Importance of Accurate Patient Identification

Ensuring In a fragmented industry with a multitude of disparate organizations and health systems, patient medical records are often dispersed across multiple providers. Additionally, the same health system often maintains multiple records for the same patient, which can lead to delays in patient care, medication management challenges and billing issues. In the absence of a national patient identifier, solutions for enterprise-wide patient matching, such as EMPI, drive comprehensive, correct patient data sharing across concurrent care delivery modalities and technologies, elevating patient care delivery, efficiencies and outcomes. 

According to a study by Johns Hopkins University, preventable medical errors are the third leading cause of death in the U.S., and frequently can be linked to inaccurate patient data. In addition, approximately 33 percent of all denied claims are associated with inaccurate patient identification, which costs the average hospital $1.5 million and the U.S. healthcare system over $6 billion annually, according to a survey from Black Book Research.  

SmartMPI Overview

SmartMPI is a machine learning solution that analyzes and consolidates patient data from multiple systems—including disparate EHRs, medical charts, e-prescribing technologies, clinical documentation solutions and revenue cycle management platforms—resulting in longitudinal patient records that can be transparently shared among the patient’s care team, optimizing care coordination. Furthermore, the solution provides detailed analytics and a way to address these duplicates in a phased approach. It also allows for merge/unmerge capabilities which can be automated based on configurable thresholds.  Streamlined workflows and a simple implementation and deployment model also lead to heightened efficiencies for the multiple organizations involved in the patient’s care journey. 

“Hospitals deal with hundreds of thousands, and sometimes millions, of electronic patient records,” said Navneet Verma, director of data science for HSBlox. “In today’s healthcare climate of consolidation among physician practices—and mergers and acquisitions among health systems—many organizations are facing challenging migrations of critical patient data from one EHR to another, significantly increasing the need for effective solutions for patient matching, such as SmartMPI.”

 

“HSBlox’s SmartMPI solution has achieved the highest degree of accuracy for patient matching, which is essential for healthcare innovations,” said Verma. “In scenarios where data is being consolidated from multiple constituents, a secure, unique patient identifier is required— or bad data will be input. This leads  to inaccurate or at least incomplete data sharing—the worst scenario for patient care,” added Verma. “We’re thrilled to make SmartMPI generally available to healthcare organizations of all sizes, ensuring that each provider is empowered to deliver the best patient care.”

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Tagged With: Artificial Intelligence, Healthcare Blockchain, HSBlox, Machine Learning, National Patient Identifier, patient ID matching, Revenue Cycle Management, secure patient data

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