Learnings from Clinical Research Forum's IT Roundtable

Main Storyline: Navigating the Transition from On-Premise to Cloud Infrastructure in Healthcare Research

The healthcare research sector is at a pivotal crossroads in terms of data management and infrastructure. Dominated by on-premise data systems due to legacy investments, these structures now pose significant challenges to the dynamism and collaborative spirit essential in modern healthcare research.

The Challenges of Legacy Systems

The persistence of on-premise systems is not merely a technological concern but a barrier to innovation. These legacy systems, often entangled in a web of outdated practices and infrastructures, have left many CRIOs and research leaders grappling with inflexible and isolated environments. This scenario is particularly problematic when considering the integration of open-source large language models. The inability to efficiently access and implement these models stifles the potential for advancements in data processing and patient care analysis. Similarly, the lack of flexible testing environments within these legacy systems hinders the ability to experiment and innovate safely. Collaborative efforts, crucial in the realm of healthcare research, are significantly impeded, as these outdated systems do not readily support shared workflows or data pools, limiting the scope of team science and multi-institutional collaborations.

Shift in Leadership Perspective

In response to these limitations, a transformative shift in perspective is underway among healthcare research leaders. The realization that on-premise infrastructures are no longer tenable has led to an increased interest in cloud-managed services and open-source tools. These technologies are not just enhancements but necessities for fostering an environment conducive to innovation, efficiency, and collaboration. Research leaders are now acknowledging that to stay at the forefront of healthcare innovation, transitioning to a more adaptable and collaborative infrastructure is imperative.

The Evolving Business and Research Environment

The transition from individualistic 'hero' science to a more integrative 'team' science approach reflects the broader evolution in healthcare research. The necessity for data sharing, model sharing, and collaborative analytics has become more pronounced than ever. This sea change is driven by the understanding that collective intelligence and shared resources are key to tackling complex health challenges. The barriers imposed by on-premise systems are becoming increasingly untenable in this dynamic environment, prompting a concerted move towards more flexible and collaborative cloud-based solutions.

The Challenge of Transitioning to Cloud IaaS

The journey from on-premise to cloud Infrastructure as a Service (IaaS) is fraught with challenges, particularly concerning the sensitive nature of health data. Compliance with regulatory standards is paramount, and the intricacies involved in ensuring data privacy and security in the cloud are significant. The complexity of these challenges is compounded by the need to maintain data integrity and ensure seamless operation during the transition. While there is no one-size-fits-all solution, embracing best practices in cloud migration can significantly mitigate risks and facilitate a smoother transition.

Empowering Researchers Beyond EPIC

The limitations of EPIC systems in fully enabling researchers have led to an exploration of more adaptable architectures. Transitioning clinical data from systems like Clarity or Clarity2 into a Spark-based platform such as Databricks is gaining significant traction in our experience. This approach, while necessitating a re-modeling of data, offers considerable advantages. The medallion layer model, with its multi-tiered structure (bronze, silver, gold), is instrumental in ensuring data is not only secure and scalable but also accessible with nuanced access controls. This model effectively balances the need for comprehensive data security with the flexibility required for advanced analytics and collaborative research.

Leveraging Strong Foundations in the Cloud

The transition to cloud infrastructure is supported by robust, accessible solutions. For instance, Azure's Secure Research Enclave script, available on GitHub, illustrates a practical pathway to creating secure cloud environments tailored for healthcare research. Azure and AWS emerge as the preferred platforms, with Azure's specialized secure research and health learning system landing zones offering distinct advantages for healthcare data applications. These platforms provide the foundational support needed for scalable, secure, and compliant data management, paving the way for more effective and collaborative healthcare research.

Conclusion

The transition from on-premise to cloud infrastructure in healthcare research is not just an upgrade; it's a fundamental shift towards a future of innovative, collaborative, and efficient healthcare research. By embracing cloud-based solutions and the myriad benefits they bring, research institutions can transcend legacy infrastructure limitations, and building on these institution's rich history of innovation and collaboration.