What can the cloud offer for enterprise imaging?
Healthcare organizations are increasingly pursuing an enterprise imaging strategy, driven by factors such as growing volumes of clinical and imaging data and the desire to integrate everything on a single platform. For some, cloud technology has become a key element in the decision-making process.
Cloud technology offers a number of potential advantages to enterprise imaging, from improved disaster recovery to more flexible budgeting to reduced strain on hospital IT staff.
Although the market for cloud-based enterprise imaging is still in the early phases, new options are emerging to get started, from hybrid approaches that combine on-premise data archives with cloud storage to architectures that are totally native to the cloud.
Healthcare organizations are increasingly pursuing an enterprise imaging strategy, driven by factors such as growing volumes of clinical and imaging data and the desire to integrate everything on a single platform. For some, cloud technology has become a key element in the decision-making process.Cloud technology offers a number of potential advantages to enterprise imaging, from improved disaster recovery to more flexible budgeting to reduced strain on hospital IT staff.
Although the market for cloud-based enterprise imaging is still in the early phases, new options are emerging to get started, from hybrid approaches that combine on-premise data archives with cloud storage to architectures that are totally native to the cloud.
Fulfilling the promise of enterprise imaging
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At the 2019 RSNA annual conference, Change Healthcare hosted an engaging panel discussion about the future of enterprise imaging and how to realize its potential. The panelists -- a mix of Change Healthcare experts, development partners, and longtime customers -- examined the advantages, challenges, and necessity of establishing a truly cloud-native network architecture.
"The problem with enterprise imaging in the cloud today is that most solutions are not developed specifically for that platform, but instead are lifted from legacy technologies and replatformed," said Tomer Levy, vice president and general manager of Cloud Solutions at Change Healthcare. "This means providers aren't realizing the full benefits in improved care coordination, cost realization, and reduced infrastructure complexity that true cloud-native solutions can provide."
Change Healthcare's new Enterprise Imaging Network -- currently in development with key partners -- is being built from the ground up to exploit the flexible nature of cloud services and delivery. As a solution that doesn't simply replicate conventional on-premise systems, the Enterprise Imaging Network promises to deliver everything providers expect from an enterprise imaging service with the addition of clinical and operational capabilities that are only available through a truly cloud-native software-as-a-service (SaaS) platform.
— Sponsored Content
At the 2019 RSNA annual conference, Change Healthcare hosted an engaging panel discussion about the future of enterprise imaging and how to realize its potential. The panelists -- a mix of Change Healthcare experts, development partners, and longtime customers -- examined the advantages, challenges, and necessity of establishing a truly cloud-native network architecture."The problem with enterprise imaging in the cloud today is that most solutions are not developed specifically for that platform, but instead are lifted from legacy technologies and replatformed," said Tomer Levy, vice president and general manager of Cloud Solutions at Change Healthcare. "This means providers aren't realizing the full benefits in improved care coordination, cost realization, and reduced infrastructure complexity that true cloud-native solutions can provide."
Change Healthcare's new Enterprise Imaging Network -- currently in development with key partners -- is being built from the ground up to exploit the flexible nature of cloud services and delivery. As a solution that doesn't simply replicate conventional on-premise systems, the Enterprise Imaging Network promises to deliver everything providers expect from an enterprise imaging service with the addition of clinical and operational capabilities that are only available through a truly cloud-native software-as-a-service (SaaS) platform.
Workflow applications drive radiology analytics market
The utilization of artificial intelligence (AI) to assist with image interpretation may generate much of the headlines in radiology analytics, but it's workflow-enhancing tools -- some based on AI and some not -- that currently offer the most proven value for today's world of radiology.
To better manage costs and improve efficiency across all imaging departments in an enterprise, healthcare institutions are increasingly turning to analytics applications that provide business intelligence -- enabling better understanding of the radiology department's working processes at scale and driving operational improvements.
Some examples include enterprise-wide fleet management services across image modalities, staff tracking and training, radiation dose management, image quality analytics, and even analyzing patterns in missed patient radiology appointments. Other notable analytics trends where AI can help include the development of "smart" tools that can provide load balancing for radiology worklists in larger networks.
The utilization of artificial intelligence (AI) to assist with image interpretation may generate much of the headlines in radiology analytics, but it's workflow-enhancing tools -- some based on AI and some not -- that currently offer the most proven value for today's world of radiology.To better manage costs and improve efficiency across all imaging departments in an enterprise, healthcare institutions are increasingly turning to analytics applications that provide business intelligence -- enabling better understanding of the radiology department's working processes at scale and driving operational improvements.
Some examples include enterprise-wide fleet management services across image modalities, staff tracking and training, radiation dose management, image quality analytics, and even analyzing patterns in missed patient radiology appointments. Other notable analytics trends where AI can help include the development of "smart" tools that can provide load balancing for radiology worklists in larger networks.