Swoop Granted Patent for Privacy-by-Design Data Processing Techniques

CAMBRIDGE, Mass., March 10, 2020 /PRNewswire/ — Swoop, a Cambridge-based health technology company, today announced they have been granted a patent for their privacy-safe sensitive data processing techniques. The patent leaves the organization uniquely positioned to ingest, manipulate and analyze sensitive data, such as health data, in a way that ensures the protection of the privacy of individuals while also ensuring the accuracy of its AI models and the positive impact they have on patient outcomes and healthcare costs.

This patent, and the core concept of Privacy by Design that it embraces, is a recognition that historical perspectives on privacy can and should evolve to embed privacy foundationally into an organizations’ architectural DNA in the rapidly evolving privacy environment of today.

“Though HIPAA has had an enduring institutional legacy as a privacy law, we are seeing that, in today’s dynamic ecosystem, the regulatory environment is rapidly evolving. GDPR, CCPA, and self-regulatory bodies like the NAI, are all reconciling what consumer and patient privacy looks like in the digital world,” says Swoop co-founder and CTO Simeon Simeonov. “Our invention embodies the concept of Privacy by Design. Not only do we embrace privacy as the default state, but our patent outlines a de facto privacy architecture that maintains strict compliance as these and other new privacy regulations and self-regulatory best practices develop.” 

The patent, titled “High-Accuracy Data Processing and Machine Learning Techniques for Sensitive Data,” enables systematic compliance with the Health Insurance Portability and Accountability Act (HIPAA), the California Consumer Privacy Act (CCPA), the Network Advertising Initiative’s 2020 Code of Conduct, and the General Data Protection Regulation (GDPR). 

“We specialize in protecting the privacy of individuals by performing disclosure risk assessments on our clients’ healthcare datasets,” says Jamie Blackport, CEO and Co-Founder of Mirador Analytics, which handles Swoop’s HIPAA compliance. “While working with Swoop to ensure HIPAA compliance, their commitment to developing systems with privacy in mind was clear and we have been impressed with the paramount importance they have placed on patient privacy.”

“AI and big data are a potentially transformational, yet significantly untapped resource for healthcare,” says Swoop CEO and co-founder Ronald Elwell. “We are absolutely convinced that the power of data can save lives and improve outcomes, helping to reduce overall healthcare costs. Whether it is importing emerging and non-traditional Real-World Evidence data to help find undiagnosed rare disease patients, or creating custom NAI compliant DTC targeting segments, our system guarantees adherence with the growing number of privacy regulations, a statement we’re not convinced others can make.

“We’re very proud to be on the cutting edge of this revolution. Swoop has invested a tremendous amount of time and resources into expanding AI’s ability to positively influence health outcomes without sacrificing patient privacy, and we believe this patent represents a large step forward in our and the healthcare industry’s ability to do so.”

Swoop’s patent No. 34933040 can be found at patft.uspto.gov

About Swoop

Based in Cambridge, Swoop offers best-in-class health segments for audience targeting. By modeling populations based on deidentified health and demographic data, Swoop provides biopharma clients with the digital messaging capability they need to educate patients and healthcare providers about their products and the conditions associated with them. Swoop is the first consumer health data-oriented member of the Network Advertising Initiative (NAI).

Additionally, Swoop subsidiary IPM.ai is a high-tech data and analytics company that focuses exclusively on utilizing artificial intelligence and machine learning to enable biotech and pharmaceutical companies to solve for commercialization challenges that require patient-centric analytical approaches. The combination of market-leading domain expertise in identifying appropriate patient cohorts combined with cutting-edge AI techniques helps clients throughout the commercial analytics process.

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