Harmonizing Regulatory Spheres to Overcome Challenges for Governance of Patient-Generated Health Data in the Age of Artificial Intelligence and Big Data
28 Pages Posted: 17 Dec 2020
Date Written: December 15, 2020
Abstract
Patient-generated health data (PGHD), created and captured from patients via wearable devices and mobile apps, are proliferating outside of clinical settings. Examples include sleep tracking, fitness trackers, continuous glucose monitors, and RFID-enabled implants, with many additional biometric or health surveillance applications in development or envisioned. These data are included in growing stockpiles of personal health data being mined for insight via big data analytics and artificial intelligence/deep learning technologies. Governing these data resources to facilitate patient care and health research while preserving individual privacy and autonomy will be challenging, as PGHD are the least regulated domains of digitalized personal health data (U.S. Department of Health and Human Services, 2018). When patients themselves collect digitalized PGHD using “apps” provided by technology firms, these data fall outside of conventional health data regulation, such as HIPAA. Instead, PGHD are maintained primarily on the information technology infrastructure of vendors, and data are governed under the IT firm’s own privacy policies and within the firm’s intellectual property rights. Dominant narratives position these highly personal data as valuable resources to transform healthcare, stimulate innovation in medical research, and engage individuals in their health and healthcare. However, ensuring privacy, security, and equity of benefits from PGHD will be challenging. PGHD can be aggregated and, despite putative “deidentification,” be linked with other health, economic, and social data for predictive analytics. As large tech companies enter the healthcare sector (e.g., Google Health is partnering with Ascension Health to analyze the PHI of millions of people across 21 U.S. states), the lack of harmonization between regulatory regimes may render existing safeguards to preserve patient privacy and control over their PHI ineffective. While healthcare providers are bound to adhere to health privacy laws, Big Tech comes under more relaxed regulatory regimes that will facilitate monetizing PGHD. We explore three existing data protection regimes relevant to PGHD in the United States that are currently in tension with one another: federal and state health-sector laws, data use and reuse for research and innovation, and industry self-regulation by large tech companies We then identify three types of structures (organizational, regulatory, technological/algorithmic), which synergistically could help enact needed regulatory oversight while limiting the friction and economic costs of regulation. This analysis provides a starting point for further discussions and negotiations among stakeholders and regulators to do so.
Keywords: Patient-generated health data, PGHD, governance, privacy, Big Tech
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