Crucially, deploying an automation program does not require existing applications to change in any way. In fact, the most robust Intelligent Automation programs can interact with insights and triggers driven by an organization’s data science assets to create evolving solutions that are resilient in the face of changing internal or external factors.
This means that healthcare institutions can realize benefits with minimal up-front investment and no disruption to existing processes in a way that is highly scalable and adaptable to changes in the business environment. Gartner predicts that 50% of healthcare organizations in the United States will invest in automation by 2023, driven by the accelerated need to reduce costs and optimize resources triggered by the COVID-19 pandemic.
To get the most out of an investment in IA with software agents that can work fast and around the clock, the infrastructure supporting the application environment must be up to the task. Minimizing latency and eliminating downtime become even more important when software agents are working around the clock, 7 days a week. Access to data from different applications is simplified and sped up if that data resides in a consolidated environment.
With NetApp® ONTAP® adaptive quality of service (AQoS), you can deploy all your healthcare applications in a single clustered storage environment that scales out. The result: You can eliminate data silos, guarantee peak performance, and lay a solid foundation for a successful IA implementation. Adding NetApp Cloud Insights to the mix strengthens the foundation even further by securing your data and increasing uptime through early detection of ransomware and automated responses to threats. Cloud Insights uses machine learning to detect greedy or degraded resources, enable you to customize targeted and conditional alerts, and a host of other features.
We'd love to have a conversation with you about intelligent automation. Contact us at netapp.com/healthcare
Esteban joined NetApp to build a Healthcare AI practice leveraging our full portfolio to help create ML-based solutions that improve patient care, and reduce provider burnout. Esteban has been in the Healthcare IT industry for 15 years, having gone from a being storage geek at various startups to spending 12 years as a healthcare-storage geek at FUJIFILM Medical Systems. He's a visible participant in the AI-in-Healthcare conversation, speaking and writing at length on the subject. He is particularly interested in the translation of Machine Learning research into clinical practice, and the integration of AI tools into existing workflows. He is a competitive powerlifter in the USAPL federation so he will try to sneak early-morning training in wherever he's traveling.