Confidential Computing and Data Security in Healthcare
Challenges
The healthcare industry is struggling to keep pace with the ever-growing demand for data-driven insights and services while at the same time needing to manage and protect sensitive patient information across different providers.
- Healthcare organizations must consolidate and analyze information from sources such as clinical laboratories, EMR suppliers, pharma manufacturers, health IT companies, insurers, health service providers for optimal patient outcomes.
- The legal requirements to protect confidential patient data privacy present a significant obstacle to accessing this data, perform analysis and gain insights.
- Approaches that only mask or tokenize data can limit the health data analytics and insights across the information.
- Data needs to be kept confidential and secure, including protecting against external and internal exploits while data is at rest, in transit, and during use.
The Opaque Solution
The Opaque Confidential Analytics and AI Platform provides an efficient, secure, scalable, and privacy-preserving solution for healthcare organizations to overcome these challenges and secure sensitive data. As a result, you will have improved patient health outcomes, identified inefficiencies to reduce costs, and effectively managed risks.
Opaque enables organizations to unlock the value of confidential and sensitive data. Opaque Platform advantages include:
- Enabling secure collaboration on data containing highly sensitive patient information across providers, keeping all the data encrypted even while in use.
- Providing faster access to data, removing the need for human intervention to identify and preprocess PII data, which streamlines governance.
- Delivering higher quality insights and model development by empowering healthcare data analysis on encrypted data fields, as compared to tokenization or redaction approaches.
- Supporting scalable cloud deployment
Confidential computing is a game-changer for the healthcare industry. It allows us to securely share and analyze patient data without compromising privacy, which is essential for improving patient care and preventing fraud.
Use Cases
- Improve Patient Health Outcomes
Opaque unlocks additional data sources for predictive analytics to identify patients who are at risk for certain diseases or complications. This information can be used to help direct preventative care and treatment plans. Additional AI and machine learning applications can be developed to drive prescriptive analytics and determine the best course of action for your patients.
- Optimize Provider Matching
Matching care providers with clients entails navigating sensitive patient data across organizations while protecting access and usage of this sensitive data. The Opaque Platform enables collaborative analytics and secures data sharing on confidential data to facilitate a match while fully complying with HIPAA data privacy requirements.
- Accelerate Medical Research
The use of analytics can help accelerate medical research and development into new treatments and therapies. HIPAA prohibits healthcare providers from sharing patient data with third parties without the patient’s permission. This can make it difficult for drugmakers to obtain the data they need to analyze and gain a comprehensive understanding of a disease or condition. Opaque enables health data analytics without exposing individual patient information.
- Increase Insurance Efficiency & Prevent Fraud
The ability to unlock data across your network of providers enables our advanced AI to identify and combat insurance fraud. We leverage your full health data analytics capabilities to improve claims processing and customer service, resulting in proven efficiency and cost-savings for your healthcare organization.
See Opaque in action and confidential analytics and AI use cases across AdTech, Finance, Insurance, Healthcare and more.
