AI-Driven Data Strategy for Academic Medical Center Research

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The ability to align research data with universally accepted data standards, such as the OHDSI OMOP Common Data Model, is a strategic imperative for AMCs. By standardizing data, they can easily share information with other organizations, enhancing collaborative research efforts and enabling them to participate in larger and more competitive funding opportunities. They can power collaboration internally between the clinical practice and research departments, as well as externally with research partners. Interoperability and transparency, which can lead to broader scientific and clinical advancements, are also key criteria for funding agencies.

However, on-premises data platforms and legacy technologies create data silos and cumbersome data-sharing processes, making it difficult for AMCs to standardize and collaborate on data. These platforms lack the scalability needed to manage the extensive data volumes and multiple concurrent research workloads essential for AMCs. They also cannot easily collect, process or share multimodal health data, which encompasses a wide variety of data types — including clinical notes, protein sequences, chemical compound information, medical imaging and patient data. Each of these data types can require specialized software packages, hardware environments and data processing techniques. The lack of a simplified, scalable technology platform leads to delays in research, wasted staff time and lost funding opportunities. 

Critically, legacy systems can also create serious data privacy and security issues. AMCs must ensure data remains private and secure across the entire research lifecycle to comply with regulations such as HIPAA. But outdated software may not be compatible with modern security protocols or meet regulatory standards for data protection, leaving AMCs vulnerable to data breaches and noncompliance penalties. The complexity of legacy systems also makes it challenging to consistently monitor and manage security as well as preserve privacy.