ASCO CancerLinQ teams with Privacy Analytics
Today, Privacy Analytics announced it is teaming up with the American Society for Clinical Oncology’s (ASCO) initiative, CancerLinQ. Privacy Analytics will de-identify electronic health record (EHR) data. This de-identified data will be used to advance cancer treatment and care, and help produce new knowledge and insights that improve treatment outcomes.
Through the use of Privacy Analytics’ de-identification expertise and software, CancerLinQ will be able to safely and securely unlock cancer patient data without risk of re-identification. This data will be used to connect and analyze real-world cancer care data to improve the quality and value of care for all. With CancerLinQ, a physician will be able to search through de-identified data on similar patients to determine how others have responded to the planned treatment. In other cases, this data and analytics can help inform the patient’s treatment decision when medical literature is not yet available.
This new partnership is an exciting opportunity for both ASCO CancerLinQ and Privacy Analytics, as it showcases the value of de-identified protected health information (PHI) and a practical application of a risk-based approach. The Privacy Analytics de-identification methodology built upon the expert determination method is compliant with the guidelines of respected health organization like the Institute of Medicine, Health Information Trust Alliance (HITRUST), PHUSE (Pharmaceutical Users Software Exchange) and the Council of Canadian Academies.
To read the full press release, please click here.
For more on ASCO’s CancerLinQ project, click here.
You can see more benefits of de-identification in practice with another featured case study found in De-Identification University: IMS Health: Unlocking the Value of EMR Data for Advanced Research and Analysis, Better Health Metrics, and Product Innovation. Privacy Analytics’ de-identified EMR data so that it could be safely utilized without putting patient privacy at risk. IMS Brogan gained the ability to evaluate unmet population healthcare needs, compare cost and effectiveness of existing treatments, find connections between diseases, and improve patient healthcare overall.
- Can you comply your way to greatness?November 21, 2019
- When to Integrate Anonymization of Documents and DataSeptember 26, 2019
- Deep-Diving into Re-identification: Perspectives On An Article In Nature CommunicationsSeptember 26, 2019
- Learning at Scale: Anonymizing Unstructured Data using AI/MLSeptember 26, 2019
- Early Impact of Health Canada’s New GuidelinesJune 21, 2019
- GDPR and The Future of Clinical Trials Data SharingMarch 18, 2019
- Advancing Principled Data Practices in Support of Emerging TechnologiesMarch 15, 2019
- “Zero Risk Does Not Exist”February 7, 2019
- Is Anonymization Possible with Current Technologies?January 9, 2019
- Comparing the benefits of pseudonymisation and anonymisation under the GDPRDecember 20, 2018