Can Federated Networks Solve Healthcare’s Data Monetization Challenges?

As the healthcare sector generates more data than ever, organizations face increasing challenges in monetizing it responsibly and effectively. Traditional data-sharing models, which often involve cumbersome agreements that restrict data flow, have led to substantial underutilization of healthcare data. These models are further complicated by strict compliance and control requirements such as those mandated by HIPAA in the U.S., and operational challenges associated with managing large datasets.

These challenges include de-identification- especially for unstructured data such as images and clinical notes- and data preparation and standardization complexity. Ethical considerations concerning patient consent and data de-identification have worked to deter many organizations from fully leveraging their data resources. Centralized data vaults, once the mainstay of data monetization, pose significant risks, including security breaches and loss of control.

Traditionally, these models often don’t favor organizations that own healthcare data, or what we’ve termed “data custodians”, as they often require significant upfront investment and limited revenue sharing. Enter the federated network—a decentralized model designed to facilitate secure, flexible data sharing while addressing the inherent risks of traditional approaches.

The Concept and Evolution of Federated Networks

In response to these enduring challenges, there is a growing shift towards innovative data monetization models that prioritize privacy and maintain control over the data. Federated learning stands out as a promising approach, allowing for data to be processed and analyzed locally at its source without the need to centralize it. Federation is not new; it originated in sectors like finance and telecommunications, where data privacy and ownership are paramount. Unlike centralized networks that pool data in one location, federated networks allow data to stay within its originating organization, while insights are drawn through shared analytics. In healthcare, this approach emerged as organizations recognized the need to access valuable patient data without compromising security or regulatory compliance. Federated networks use a “local-first” approach, where data resides on-premises and only specific insights, not raw data, are shared.

Addressing Security and Privacy Challenges

One of the key benefits of federated networks is enhanced data privacy. In traditional data monetization, data custodians transfer datasets to third parties or central platforms, risking exposure and potential misuse. Federated networks mitigate this by processing data locally; data never leaves its original site, drastically reducing the risk of a breach. For healthcare, where patient privacy is crucial, this decentralized model supports compliance with privacy regulations like HIPAA, ensuring patient information remains secure and within control.

Overcoming Data Quality and Control Issues

Federated networks also address the longstanding problem of data utility and de-identification efforts. Traditional data-sharing models require custodians to invest significant time and resources in preparing data for centralized use, including de-identification. This approach can be cumbersome and risks losing key attributes and a level of granularity essential for meaningful analysis. Additionally, removing identifiable information, such as from images, requires specialized expertise, and access controls and encryption must be implemented to meet regulatory standards. Standardizing data from diverse systems also demands considerable expertise, as much of the data is originally structured for billing and administrative purposes rather than for clinical insights, limiting its value in medical and life sciences research. Federated networks address these challenges by allowing each organization to retain control, ensuring data is relevant, contextualized, and better suited to supporting high-quality, actionable insights.

Additionally, federated models empower data custodians by allowing them to retain control over their data. Traditional models often deprive custodians of visibility into data usage post-transfer, which could result in the use of data in ways that may be misaligned with their mission. In contrast, federated networks facilitate transparent, monitored data use, enabling ongoing revenue generation while protecting data integrity and ownership rights.

Securing Data from Health Systems, Labs, and Molecular Networks

Federated networks allow diverse data sources from health systems, clinical labs, and molecular labs to be securely shared, providing a well-rounded view of patient health. In federated networks, each contributing organization retains the ability to contextualize and prepare its data for clinical relevance. By avoiding the limitations of data structured solely for administrative or billing purposes, federated networks create a data environment where insights can be both specific and actionable, enriching research and precision medicine efforts.

Health systems contribute electronic health records (EHRs), encompassing patient demographics, medical histories, and treatment records—foundational data for understanding patient care pathways and outcomes. Clinical labs add diagnostic information, such as imaging studies, blood test results, and biomarkers, essential for tracking disease progression and evaluating treatment responses. Molecular labs offer highly-specific data, including genomic, proteomic, and metabolomic profiles, enabling insights at the cellular and genetic levels. These combined data sources empower a federated network to support advanced research and precision medicine initiatives while maintaining strict data governance and privacy standards.

The federated network approach marks a pivotal shift in healthcare data monetization, offering a sustainable, privacy-centered alternative to traditional centralized models. As organizations seek to responsibly monetize data, while safeguarding patient privacy, federated networks provide the flexibility, security, and control necessary to support ethical, impactful data sharing in healthcare. This new paradigm not only addresses the weaknesses of traditional data monetization but also empowers the healthcare industry to unlock the full potential of its data assets in a compliant, patient-first manner.