IBM has announced plans to acquire Merge Healthcare, a provider of medical image handling and processing, interoperability and clinical systems designed to advance healthcare quality and efficiency for $1 billion. The acquisition will bring IBM Watson’s advanced image analytics and cognitive capabilities with data and images obtained from Merge Healthcare medical imaging management platform to surface new insights from a consolidated, patient-centric view of current and historical images. Merge’s medical imaging platforms are used at more than 7,500 U.S. healthcare sites, including most of the leading clinical research institutes and pharmaceutical firms.
Acquisition Details
Under terms of the acquisition, Merge shareholders would receive $7.13 per share in cash, for a total transaction value of $1 billion. The closing of the transaction is subject to regulatory review, Merge shareholder approval, and other customary closing conditions, and is anticipated to occur later this year. The acquisition marks IBM’s third major health-related acquisition – and the largest – since launching its Watson Health unit in April, following Phytel (population health) and Explorys (cloud based healthcare intelligence).
Benefits of Merge Healthcare’s Integration with Watson Health Platform
IBM’s Watson Health unit plans to integrate Merge’s product and solution offerings with its existing expertise in cognitive computing, population health, and cloud-based healthcare intelligence offerings to:
– Offer researchers insights to aid clinical trial design, monitoring and evaluation;
– Help clinicians to efficiently identify options for the diagnosis, treatment and monitoring a broad array of health conditions such as cancer, stroke and heart disease;
– Enable providers and payers to integrate and optimize patient engagement in alignment with meaningful use and value-based care guidelines; and
– Support researchers and healthcare professionals as they advance the emerging discipline of population health, which aims to optimize an individual’s care by identifying trends in large numbers of people with similar health status.
“As Watson evolves, we are tackling more complex and meaningful problems by constantly evaluating bigger and more challenging data sets,” Kelly said. “Medical images are some of the most complicated data sets imaginable, and there is perhaps no more important area in which researchers can apply machine learning and cognitive computing. That’s the real promise of cognitive computing and its artificial intelligence components – helping to make us healthier and to improve the quality of our lives.”
