Wolters Kluwer accelerates healthcare data mapping with artificial intelligence to bridge data silos

Focus on lab results adds scale and support for more accurate detection of hospital acquired infections.

As the healthcare industry undergoes rampant merger and acquisition (M&A) activity, health systems are faced with the challenge of rapidly integrating data silos across hospitals to ensure continued quality of care and avoid revenue disruptions. In Health, Wolters Kluwer is now harnessing AI to bridge  data in electronic health records (EHRs) and disparate systems, such as lab results, to improve how organizations identify and report hospitals acquired infections.

“Healthcare has reached a tipping point when it comes to actionable data, but the language of healthcare remains largely unstandardized, limiting what can be understood across platforms and the people who need to act upon the information,” said Jean-Claude Saghbini, Chief Technology Officer for Wolters Kluwer, Health. “AI is increasing data-mapping capabilities exponentially, which enables the rapid identification of findings that benefit decision-making. For example, hospitals using our surveillance solutions for early detection and intervention of hospital acquired infections (HAI) will benefit from AI’s ability to map lab results faster and more accurately to reduce risks and help keep patient’s safe.”

Real-world data challenges

Wolters Kluwer’s data science team worked with Health Language® to use AI and machine learning to enhance the process of mapping lab results to fully standardized LOINC codes (Logical Observation Identifiers Names and Codes), a common challenge among hospitals and payers post-mergers or when aggregating data from disparate EHRs or systems. Manually mapping lab results to LOINC is error-prone and can take months to complete. AI reduced the process considerably and enabled Wolters Kluwer’s Sentri7® customers to accurately and quickly comply with reporting HAIs to the Centers for Disease Control and Prevention and to state health departments.

Saghbini added, “AI creates tremendous business value in healthcare helping to dramatically scale how healthcare organizations map troves of fragmented, non-standardized data. With a record number of M&A deals observed in 2018, the need for data science and mapping expertise to enable timely onboarding and provide a big picture, population level view of health system data in post-M&A organizations has only intensified.”

Beyond increasing the speed and accuracy of how healthcare organizations report HAIs, Wolters Kluwer is also applying AI to several other areas supporting patient engagement and clinical effectiveness.

To learn more about Wolters Kluwe's AI capabilities in healthcare and how they are helping organizations across the country improve quality of care and patient safety, visit https://www.wolterskluwer.com/en/expert-insights/connecting-the-dots-on-disease-ai.