By leveraging real-world evidence (RWE), healthcare providers can deliver value-based care that is both patient-centric and cost-effective.
Value-based care is a healthcare approach that prioritizes better patient outcomes and lower costs. Unlike traditional fee-for-service models that reward the volume of services, value-based care ties compensation to the quality of care provided. This model shifts the focus from merely treating illnesses to genuinely improving the health and well-being of patients.
How do healthcare providers achieve this? One way is using real-world evidence (RWE) to inform decisions, guiding treatment plans and care strategies with data-driven insights.
Real-world evidence (RWE) is clinical data gathered outside controlled clinical trials—think electronic health records (EHRs), insurance claims, wearable devices, and patient registries.
The shift from traditional fee-for-service models to value-based care has placed a spotlight on patient outcomes. RWE supports this transition by providing a comprehensive view of how treatments perform in everyday clinical settings, not just in controlled trials. It allows healthcare organizations to move beyond assumptions and make decisions grounded in real data.
The result? More effective treatments, fewer unnecessary procedures, and, improved patient satisfaction.
For example, chronic conditions like diabetes or heart disease require ongoing management. RWE can pinpoint which approaches have the most success in keeping these conditions under control, ensuring patients receive the right care at the right time.
Using predictive analytics, providers can anticipate patient needs before they become critical, reducing emergency visits and hospital readmissions. This proactive approach allows care teams to deliver timely interventions, offering a smoother patient journey.
Adopting a data-driven approach in value-based care benefits both patients and the healthcare system. Real-world evidence (RWE) plays an important role in this shift, helping transition from fee-for-service models to value-based care, where the focus moves from volume to value.
Here’s how this approach makes a difference:
In value-based care, it’s not just about treating illnesses—it’s about preventing them. And RWE provides the insights needed to make this shift.
Real-world data has already significantly transformed patient care.
Accountable care organizations (ACOs) provide a great example. By pooling clinical data from multiple providers, ACOs can assess which interventions have the greatest impact on their patient population. This collaborative effort leads to a win-win—better care for patients and lower costs for the healthcare system.
Take the example of a hospital network using advanced analytics to monitor high-risk patients with chronic conditions like diabetes. By analyzing patterns in their EHRs, the hospital can identify patients likely to benefit from extra support. The result? A reduction in emergency room visits and a boost in patient satisfaction.
Data-driven decision-making is not just about knowing what to do; it’s about knowing when and how to do it.
Real-world evidence (RWE) is essential for success, but organizations face several hurdles in utilizing this data effectively.
Visibility into patient data: As the healthcare system grows, it becomes increasingly tricky to determine where exactly data privacy might be compromised. This is further complicated by the fact that different departments might be prone to varying levels of risk, making it difficult to maintain a consistent approach to data security.
Ownership of Data Privacy: Data privacy responsibilities have traditionally been spread across multiple roles, leading to a severe gap in ownership of data privacy issues as they arise. The fact that enterprises are now beginning to hire or assign a privacy-specific role highlights the importance of this function.
Budget Constraints: Privacy tools often extend beyond security concerns, affecting multiple areas of an organization’s infrastructure, which can be costly. For organizations with limited resources, investing in the necessary privacy tools becomes a significant hurdle.
Lack of Urgency: Often, data privacy is not prioritized until a problem, like a breach or regulatory challenge, occurs. This reactive approach makes it harder to maintain consistent compliance and proactive data management.
To fully leverage real-world evidence while maintaining compliance and data security, healthcare organizations need solutions that address these pain points effectively.
How can we unlock the power of data effectively and safely?
Secure computation of sensitive data could be the answer. By carefully processing data and maintaining privacy, confidentiality, and compliance, providers can gain the insights they need to improve care, all while keeping patient information safe.
For example, healthcare providers, especially in clinical research, often need to identify risk factors for chronic conditions within their patient populations. Traditionally, this means gathering large volumes of patient data and analyzing it for patterns, trends, and correlations. Yet, this can raise privacy concerns, not to mention the logistical challenges.
A solution is the concept of ‘secure computation of data.’ Here, the data is encrypted throughout the analysis process, so providers can extract insights without ever exposing sensitive patient information.
Through this method, healthcare professionals can access the insights they need to deliver better care while reassuring patients that their data remains protected. It’s proof that data privacy and data utility can work together, allowing providers to use real-world evidence to improve care and outcomes.
With a focus on privacy-preserving data analysis, Duality’s solution helps healthcare providers achieve data-driven value-based care without compromising patient confidentiality.
Our technology uses advanced cryptographic methods, including multiple Privacy-Enhancing Technologies (PETs). PETs enable complex computations on data while the data or the model itself remains encrypted, without ever revealing more than the computational result.
This capability allows healthcare organizations to perform tasks such as running descriptive statistics, training, tuning, and deploying AI/ML models, and executing SQL-like queries on
encrypted data—all without exposing sensitive Real-world evidence and healthcare data.
This method takes us a step closer to executing data-driven value-based care as it allows secure collaboration with partners in any environment, unlocking the value of data, driving revenue, and augmenting efficiency across the organization.
Duality Technology also integrates with existing systems, enabling healthcare organizations to set up collaborative projects quickly, securely, and at scale.
Ready to safely leverage real-world evidence for value-based care? The future of the health care system is about making decisions that are backed by real-world data, not just theories. With Duality’s privacy-preserving computations, healthcare organizations can unlock the potential of their data to drive improvements, promoting the objective of improved patient outcomes and lower healthcare costs.
