US-based digital health enablement company Rhapsody has introduced a tool to automatically link person records in accordance with customers’ preferences utilising machine learning (ML) technology.  

Known as Rhapsody Autopilot, the new tool aims to provide a comprehensive view of health data to the users.  

This solution has a companion feature, called Rhapsody Copilot, which is an artificial intelligence (AI)-driven tool to assist data stewards in decision-making.  

The initial release of the solution is set for late summer as part of Rhapsody EMPI v12.1. 

According to Rhapsody, its platform emulates human decision-making to address data linking and data quality issues, automating preferred actions to enhance credibility and minimise the burden on data stewards and clinicians.  

The technology also promises to improve patient safety and quality by lowering duplicate rates. 

The company said that the ML technology consistently makes decisions that align with an organisation's guidelines, in contrast, a team of ten people might only reach the same decision 72% to 85% of the time.  

Rhapsody Autopilot has demonstrated a 98% alignment with organisational matching guidelines, which translates to improved accuracy and significant savings in time and costs, the company noted.  

Additionally, Rhapsody estimates that the automation of data stewardship tasks could save healthcare teams up to $150,000 for every 100,000 data quality tasks and 50,000 hours of data steward time by processing over two million records in under 80 minutes. 

The company describes Rhapsody Autopilot as a platform which helps in analysing customer’s data, using the organisation's own data quality preferences to resolve issues, ensuring transparency in decision-making processes and data lineage.  

Rhapsody's future plans include enhancing its products with AI and ML, and creating infrastructure to support AI companies in accelerating innovation.  

Rhapsody CEO Sagnik Bhattacharya said: “Healthcare organisations seek ways to drive higher-quality data while reducing cost. Using AI to automate data stewardship is the perfect use case for technological advancements to achieve those goals. 

“With Rhapsody Autopilot, we are helping improve the effectiveness of teams and products otherwise hampered by poor data quality and incomplete views.”