How Artificial Intelligence and a New System Architecture Are Changing Imaging
Whitepaper | Todd Doherty
Product Manager and Director of Product Management in Data Services, Change Healthcare
Mr. Doherty has 20+ years of IT experience, including delivery of scalable cloud solutions in global markets. His team manages the cloudnative Change Healthcare Enterprise Imaging solution as a service.
In today’s world of value-based care, better outcomes and lower costs are imperative. Recognizing the need for innovative solutions is critical to achieving those objectives. To thrive in a crowded market, healthcare providers must also distinguish themselves from their competition.
Artificial intelligence (AI) and cloud-native solutions are making dramatic improvements in clinical outcomes possible. Their continued use will be vital as healthcare heads into the future of greater automation, sharing, and collaboration. By leveraging technology innovation, the world of enterprise imaging is embracing a new normal that will eventually shape the entire healthcare industry: cloud-native architecture.
Cloud-based Versus Cloud-native Technology
Before continuing, let’s distinguish between “cloud-based” and “cloud-native.” These terms sound similar, but the differences are important.
Cloud-hosted applications are defined as those that are stored, managed, and processed on a network of remote and leased servers hosted on the internet, rather than on local servers or personal computers.
Described another way, cloud-hosted solutions are traditional on-premises applications that have been “lifted and shifted” to an independent and leased data center location. This process achieves some economies of scale, as such solutions can share some network, platform, and storage components. However, the cloud-hosted solutions are limited by the need to manage each instance separately; the operation of potentially older technologies; and traditionally lengthy and manual upgrade processes.
In contrast, a full cloud-native solution is designed specifically for the cloud. According to a May 2019 article in Forbes, “cloud-native is about how applications are created and deployed, not where. Something can’t just be in the cloud to be cloud-native; it must be of the cloud—designed, optimized, and operated for the cloud.”1
A cloud-native solution typically uses many automation features in its application to operate, support, and upgrade many customer accounts from a single instance, which uses far fewer resources than traditional IT solutions. As the Forbes article explains, cloud-native solutions help to enable flexibility, interoperability, efficiency, and resiliency—advantages that are not achieved by simply lifting legacy applications to the cloud.2
The differences between cloud hosting options are very important when deciding on a new vendor for an enterprise imaging solution.
Healthcare Leaders Weigh in on Cloud Technology
To better understand how the healthcare industry feels about cloud technology, Change Healthcare surveyed healthcare executives, finance leaders, VPs, and IT directors in late 2018. Our survey results indicate that 90% of respondents with a cloudhosted EHR believe that “cloud is where the industry is headed.”3
Along with other important questions, the survey asked whether the healthcare leaders currently had any IT systems in the cloud. Respondents cited EHRs (41%) and analytics solutions (32%) as the top two cloud-based systems currently being used.4
Clearly, cloud-based and cloud-native solutions are not a novelty. The movement to the cloud is already in progress, and expectations for measurable success are helping to guide the transition.
Artificial Intelligence in Healthcare
We all know that healthcare produces volumes and volumes of data, which can be instrumental in helping healthcare organizations manage costs and improve treatment outcomes.
But with mountains of data, the need to uncover actionable insights becomes an imperative. AI helps to guide clinical decision-making at the point of care by enabling fast analysis of huge quantities of data.
A recently published article in FierceHealthcare on the importance of AI in healthcare claims that AI clinical decision-support tools have given physicians “the ability to understand, access and analyze a wealth of real-world data…to produce trusted best practices that can be rapidly applied to their clinical practice.”5
The article also cites a report by Dell EMC and the research firm IDC, which found that “health data volumes increase by a staggering 48% annually.”6 This creates a great opportunity to use AI to mine this wealth of data for trends and medical analysis for improved clinical outcomes.
When used in conjunction with patient diagnosis, AI also helps to improve the efficiency of analysis and clinical results. For example, the use of integrated AI capabilities in radiology tools is replacing the need for tissue samples in certain tests, such as biopsies—minimizing the need for invasive procedures and reducing the patient’s risk of infection.7
Benefits of Cloud-native Solutions
Now that we have a bit of a framework around the terminology and the uses of AI in healthcare, let’s talk about the specific benefits of cloud-native solutions for healthcare.
The primary benefit lies in superior accessibility. When data is properly organized and hosted in the cloud, caregivers can access the information they need more easily, resulting in more effective collaboration.
Some providers choose to adapt their legacy, onpremise architectures to the cloud. Unfortunately, this “lift-and-shift” approach does not take full advantage of cloud computing’s scale across multiple tenants, which results in beneficial services automation, ease of interoperability, and most importantly, security controls. In addition, cloudnative solutions are easier to deploy, operate, monitor, and upgrade.
When migrating to a cloud-native service, there is no need to design project- or department-specific requirements for hardware, software, or loadbalancing resources. The migration and onboarding process can be accomplished rapidly—within days or weeks, not years—with no need to plan for future hardware or storage. In addition, moving to the cloud is generally associated with low switching costs from legacy solutions.
A cloud-native architecture can request system resources for performance demands and expansion as needed, and reduce systems resources when not. Resource efficiency is optimized through automatic system monitoring that recognizes peak and nonpeak times. The system is therefore able to provide millisecond access response for all storage tiers, without delays, regardless of file age.