The main goal of a hospital is to provide patients with optimal care. Unfortunately, events of the past few years have made achieving that objective more difficult. Increasing cyberattacks have forced hospital IT administrators to turn their attention to cybersecurity to protect sensitive patient data. Decreasing revenue streams and rising labor costs have led to budget constraints. Staffing shortages are leaving clinicians with less time to devote to patients. Despite these challenges, many institutions are still committed to innovating patient care.
Hospital systems are investing in artificial intelligence–based solutions to help mitigate these and other challenges while expediting and improving the quality of patient care. However, when it comes time for deployment, healthcare organizations are often stymied by questions of how to optimize their use of AI tools. They know they need to provide clinicians with real-time intelligence at the point of care, but they may be unsure of how to do this in a way that’s practical, cost-effective and scalable, especially if their infrastructures are reliant on older legacy systems.
The answer is twofold. First, healthcare organizations should consider adopting flexible hybrid edge-to-cloud infrastructures that allow them to process data at the edge and in the cloud cost-effectively. Second, they must optimize their computing resources, so they are able to extract valuable information while maintaining maximum performance and efficiency.
Click below to learn how to optimize healthcare’s connection to the hybrid cloud.