Rhino Health Federated Computing Platform illustrative examples of the Federated Datasets new feature.
Given the complex technology landscape, regulation, and legal issues, accessing high-quality healthcare data is challenging. Privacy regulations like Health Insurance Portability and Accountability Act (HIPAA)¹ in the United States and General Data Protection Regulation (GDPR)² in the European Union, combined with data fragmentation across multiple sources often hinder the seamless exploration and use of health data. These barriers limit the scope of collaborative research efforts. Now, imagine a world where healthcare research is not hindered by data silos and privacy concerns, where collaborative research across countries and regions is a seamless process. Rhino Health’s Federated Datasets (FDs) feature brings this vision to life within Rhino Health’s Federated Computing Platform (FCP). This technology empowers researchers by enabling distributed data exploration and collaboration.
Advancing Global Health Research Through Federated Datasets
Rhino Health’s FCP FDs feature catalyzes research advancements by making high-quality datasets from academic medical centers & other data sites (1) better curated and (2) more easily explored. A prime example is a recent collaboration with partners in the Rhino Health network creating a cross-country, cross-site dataset to enable ophthalmic biomarker research. This dataset encompasses structured EHR³ data and Optical Coherence Tomography (OCT)⁴ studies, and will be used to develop new biomarkers crucial for identifying patients for intervention and assessing drug efficacy in clinical trials in age-related macular degeneration (AMD) and diabetic retinopathy.
Another example is an FD composed of pathology datasets, which is an example of how the Rhino Health's Federated Computing Platform can address the challenges of collaborating with high-volume data. Digital pathology slides, known for their vast size (up to 6GB per image and very high resolution), make data transfer to a centralized repository impractical. The federated approach facilitates the efficient handling of these extensive datasets, which is crucial in developing predictive algorithms for chemotherapy responses. This innovation is a significant step towards personalized cancer treatments post-surgery, demonstrating the federation’s value in managing large-scale data effectively.
A third example is Assuta Medical Centers’ six meticulously curated surgery datasets, each representing surgeries in a different medical field such as Gastroenterology, General Surgery, Gynecology, Urology, Orthopedic Surgery, and Otolaryngology. These datasets, containing over 750,000 records in some categories, are formulated as metadata. This structure allows data consumers or licensees to efficiently examine specific data elements that may be of interest, thereby enhancing accessibility and relevance. These datasets encompass 68 distinct features and provide a comprehensive view of patient records and surgical procedures. Information ranges from detailed demographic data to clinical metrics like BMI type, background diagnoses, and drug codes, creating a foundation for in-depth research and analysis.
Rhino Health’s dedication to expanding research avenues through FDs is also evident in its support for major initiatives like the ELISE-funded digital pathology for breast cancer and the National Cancer Institute's Early Detection Research Network (EDRN)⁵‘s Pancreatic cancer early detection work. These projects demonstrate the wide-ranging applications of the FCP FDs feature, from cancer research to other critical areas of medical inquiry.
Strengthening Healthcare Collaboration through Federated Datasets
Rhino Health FCP’s FDs feature enhances the collaborative capabilities of healthcare organizations by providing a secure platform for data sharing and fostering partnerships across the globe. By facilitating a privacy-centric, longitudinal collaboration of valuable data, the FDs feature advances medical research and broadens the reach of institutions’ findings.
The FDs feature supports an integrated healthcare and industry partner ecosystem, enabling seamless connection between researchers, clinicians, data scientists, and analysts - regardless of organization, and without data transfer. This synergy expedites research, optimizes clinical trials, and strengthens post-market analysis.
Using Federated Learning, the FDs feature maintains the confidentiality of patient data, conforms to international privacy regulations such as HIPAA¹ and GDPR², and promotes collective data analysis without exposing sensitive information. The architecture of the FDs feature curtails the risk of re-identifying patient data by sharing derived AI model insights instead of raw data, reinforcing the FCP’s security posture.
By combining advanced federated data capabilities with uncompromising data security and privacy, the FCP FDs feature streamlines the preliminary evaluation of research data, providing critical statistical insights that inform licensing and reduce uncertainties in the research lifecycle. This alignment with NIH⁶ policies furthers the FCP's commitment to open science, ensuring data is used efficiently.
The FDs feature transforms the interaction between data providers and consumers by improving discoverability and facilitating the sharing of up-to-date data for ongoing studies. This efficiency gains significance in early engagement, where rapid access to data is paramount. Finally, the FDs feature allows healthcare entities to showcase their data assets to potential biopharma partners and support the progression of scientific and therapeutic discoveries.
Rhino Health Federated Computing Platform’s Federated Datasets.
In summary, Rhino Health’s FDs feature is not just a technological innovation but a cornerstone in the evolving landscape of healthcare research. By enabling global collaboration, enhancing data value, streamlining operations, and reducing IT investments, Federated Datasets set the stage for a future where data-driven healthcare innovations are more accessible, efficient, and impactful.
Whether you are a data partner, supplier, licensor, or part of a research consortium seeking collaborative opportunities in health research, Rhino Health FCP’s FDs feature is your gateway to innovation and progress. You’ll be at the forefront of healthcare innovation by joining our network. Connect with us to explore how our FCP’s FDs feature can revolutionize your research and data strategies.
Daniel Feller, PhD
AI Program Lead
Lili Lau, MSF, MSIB
Director of Product Marketing
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Notes:
(1) HIPAA: The Health Insurance Portability and Accountability Act is a US federal law that governs the privacy and security of Personal Health Information (PHI) in the United States.
(2) GDPR: The General Data Protection Regulation is a legal framework that sets guidelines for collecting and processing of personal information from individuals living in the European Union.
(3) EHR: Electronic Health Records are digital versions of a patient’s medical history, medication and allergies, immunization status, laboratory test results, radiology images, vital signs, and personal stats like age and weight.
(4) OCT: Optical Coherence Tomography is a non-invasive imaging test that uses light waves to take cross-section pictures of the retina, the light-sensitive tissue lining the back of the eye. OCT allows visualizing the retina’s distinctive layers, enabling clinicians to map and measure their thickness. These measurements help diagnose and manage retinal conditions such as age-related macular degeneration, diabetic eye disease, and glaucoma.
(5) EDRN: The Early Detection Research Network is a collaborative program that maintains comprehensive infrastructure and resources critical to discovering, developing, and validating biomarkers for cancer risk and early detection.
(6) NIH: The National Institutes of Health is a part of the U.S. Department of Health and Human Services and is the nation's medical research agency — making important discoveries that improve health and save lives.