The health services industry is ripe with mergers & acquisitions (M&A). In fact, 2021 deal volumes have exceeded levels from the past three years.1 While healthcare M&A can have significant benefits to patients including access to a larger breadth of services or decreased costs, it often causes major pain points for IT teams tasked with maintaining operational efficiency. Research firm Deloitte notes that IT system integration accounts for 70% of organizational synergies.2
Healthcare organizations produce and collect mountains of data every day that is subsequently stored in various formats and silos. When healthcare providers merge, IT teams are faced with swamps of data consisting of valuable insight from content such as:
Privacy & security protocols as well as interoperability issues make accessing and unifying this data a challenge.
Advancements in deep learning are revolutionizing the way healthcare organizations can manage, access and extract insights from their most important content. With Vyasa’s Layar data fabric, those in charge of managing data across the healthcare network can unify data sources regardless of file format or where it’s stored and without requiring a data lake. Deep learning models built within Layar automatically catalog the integrated data making it easily accessible.
By leveraging a deep learning data fabric architecture, healthcare organizations can make access to insights a matter of seconds or minutes, instead of days or weeks. Research and analysis is accelerated, as is the accuracy of outcomes, leading to safer clinical trials, improved disease research and a healthier patient population.
1 PwC (2021). Health services deals insights: 2021 midyear outlook https://www.pwc.com/us/en/industries/health-industries/library/health-services-deals-insights.html
2 Deloitte (2018). Health care mergers and acquisitions | The IT factor https://www2.deloitte.com/us/en/pages/life-sciences-and-health-care/articles/healthcare-it-mergers-and-acquisi- tions-technology.html