High-Performance Data Architecture for Healthcare

Top performing healthcare organizations are optimizing their systems with a high performance analytics framework to improve business results. Watch this video to learn more.

IBM’s reference architecture for healthcare and life sciences consists of key infrastructure components from IBM’s high-performance compute and storage portfolio, and it supports an expanding ecosystem of leading industry partners. The reference architecture defines a highly flexible, scalable, and cost-effective platform for accessing, managing, storing, sharing, integrating, and analyzing big data within the constraints of limited IT budgets.

IT organizations can use the reference architecture as a high-level guide for overcoming data management challenges and processing bottlenecks frequently encountered in personalized healthcare initiatives and other compute- and data-intensive biomedical workloads.


The healthcare industry is transforming at a velocity that is catching many organizations unprepared.

The industry aspires to become a system focused on value -- delivering better quality care and outcomes at the most affordable cost. These changes require transparency — into both the costs and the effectiveness of care — along with greater insights to be gleaned from the exponentially expanding volume of health information available today and in the future.

The digitization of healthcare, accelerated by the deployment and adoption of electronic medical records is now being exploited and augmented with technologies like mobile, social, cloud computing and analytics. This digital re-invention is laying the foundation for the future and empowering individuals and organizations to:

Improve health

Measured by healthcare outcomes for individuals, populations and communities

Provide value

Improve quality and experience at the best possible cost.

Engage the individual

As a person, reflective of their condition, needs and preferences

Yet, while digitization is producing more and more data, organizations still struggle to unlock its full value. To successfully make the shift from volume to value, healthcare and life sciences organizations need more precise and better information on their true costs, the quality (and relevancy) of the service they deliver, the risk models and segmentation of their populations and their relationships with those they serve.

The good news: there are answers in all that data. The industry is on the cusp of new learnings, thanks to vast quantities of medical, genomic and life sciences data, along with new cognitive systems to help make sense of all of it. And these new tools to analyze and glean the relevant information from this ocean of data are helping practitioners, researchers and caregivers discover and apply the answers in innovative ways.




Technology plays a critical role in enabling healthcare transformation. Technology can improve operations, support collaboration and provide the groundwork for data-driven decision making. The ability to capture, integrate and analyze data across different stakeholders, care settings and geographies is essential, as is modernizing infrastructure to increase agility.

New modalities, diagnostics and innovative medical devices, as well as the use of telemedicine and remote monitoring, add to technological enablement by increasing access and expertise. A key enabler of transformation, technology eliminates current borders of the business by overcoming barriers such as distance, knowledge or practice. Today's healthcare industry can now take advantage of the advances information technology — as so many other industries have — to innovate business models and eliminate disparities in access to care.

Thanks to advances in DNA sequencing technologies, genomic information is now being collected at an unprecedented pace, revolutionizing the depth, breadth and pace of biomedical research. The amount of data produced is overwhelming. Yet with cognitive technologies, researchers are able to more quickly analyze and understand this data to help answer important biological questions.


Cognitive systems, with their ability to fundamentally change the way humans and computers interact, can accelerate the work in clinical research, genomic studies, personalized medicine, as well can assist the transition to more person-centered care -- across the entire continuum empowering care providers, families and the individuals themselves.

Given their potential, cognitive capabilities can significantly extend insight and knowledge by providing expert assistance right into a clinician’s or caregiver's workflow, to enable organizations to dramatically change how and where care is delivered.


Today, the amount of health information is doubling every three years; by 2020 it is estimated to double every 73 days. This growing body of data may hold the answers to many of the world's most enduring health challenges and could help individuals live healthier lives. But the sheer volume and variety of this information overwhelms many organizations' ability to make sense of it—the modern-day paradox of too much data, too little insight.

For many healthcare organizations, biomedical research institutions, and pharmaceutical companies today, data are collected in such large volumes that these organizations can no longer process, properly store, or transmit these data in a timely and efficient manner. Compute and storage silos are proliferating across clinical and research groups, as the demands of complex analytical workloads grow.

To address this growing need, IBM has developed a reference architecture for healthcare and life sciences that addresses many of the technical challenges organizations face in the era of personalized healthcare.

Built on IBM's history of delivering best practices in high-performance computing (HPC), it allows healthcare and life science organizations to easily scale compute and storage resources as demand grows, and to support the wide range of development frameworks and applications required for industry innovation—all without unnecessary re-investments in technology.





Today's CIO in healthcare and life science organizations worldwide must find new ways to manage, access, store, share, and analyze these increasing volumes of clinical and scientific data within the constraints of their IT budgets.

IBM reference architecture: A diverse computing platform  built on a common infrastructure

IBM reference architecture: A diverse computing platform built on a common

It also provides a seamless bridge between on-premise and hybrid cloud environments while establishing a foundation for the journey to cognitive health-care applications.

The reference architecture was designed to reflect the current evolution in HPC, where technical computing systems need to address the batch workloads of traditional HPC, as well as long-running analytics involving big data.

The ability to take compute and storage components that are running HPC algorithm codes, and then dynamically provision them to handle other types of analytics is a more cost-effective and more easily managed alternative to maintaining two distinct systems. In the era of diverse computational workloads, diverse infrastructure needs, and diverse versions of application frameworks, it is important to avoid creating siloed compute clusters that typically underutilize IT resources and result in poor IT cost containment. The use of intelligent, policy-based workload and data management tools is a key aspect of supporting a dynamic research and/or healthcare environment.

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