As a technology leader with a decade in healthcare, I’ve seen how crucial data is for advancing AI in healthcare. The unspoken truth is that most organizations are far from being ready to effectively utilize AI. The quality of AI is primarily dependent on the quality of the underlying data, and right now, that data is a mess. At b.well, we are revolutionizing the management and utilization of healthcare data through innovative AI strategies. By breaking down data silos and standardizing information, we are enhancing patient AI experiences and setting new industry standards. Our 13-step Data Refinery produces high-quality data, and our built-in integration with LLMs enables healthcare providers and patients to access actionable AI, ultimately achieving better outcomes.
Data is the exhaust of healthcare operations; it is created as a by-product of healthcare operations but requires refinement to unlock powerful insights. Despite sitting on a wealth of data, many organizations struggle to fully harness its potential due to fragmentation and lack of refinement processes. This is where b.well steps in, offering a transformative approach to integrating AI into healthcare. By converting raw data into refined data that is ready for AI, b.well is not only improving the quality of care but also paving the way for a more efficient and patient-centered healthcare system. Our mission is to create a seamless and proactive healthcare experience for all stakeholders through the strategic application of AI.
Point 1: You’re Not Ready for the AI Revolution – How to Prepare Your Data Strategy
As healthcare organizations strive to harness the power of AI, they encounter significant challenges. Data is often fragmented across various stores and formats, making it difficult to leverage effectively. For AI to truly revolutionize healthcare, it requires high-quality, clean, and aggregated data, along with governance and transparency in both data handling and AI algorithms.
6 Key Elements to Succeed with AI in Healthcare
- Data Quality: The Foundation of Trustworthy AI
- Clean, standardized, and reliable data is crucial for building trust in AI systems. At b.well, we employ a 13-step Data Refinery approach to ensure data integrity and quality.
- Data Conversion and Standardization
- By transforming diverse data formats into canonical FHIR, b.well creates a unified, interoperable data ecosystem, facilitating seamless integration and analysis.
- Comprehensive Data Lineage and Trust
- Tracking the origin and transformations of data is essential for regulatory compliance and audit trails, instilling confidence in data-driven decisions. b.well has full lineage tracking so you can inform AI consumers how AI came to its conclusions.
- Intelligent Data Enrichment
- Augmenting raw data with contextual information enables deeper insights and more sophisticated analytics, enhancing decision-making processes. For example, AI can understand medications better if it knows the ingredients in that medication and knows that generics and brands are interchangeable. The b.well 13-step data refinery enriches the data with information like this, making AI become more accurate.
- Privacy and Ethical AI Readiness
- Protecting Health Information (PHI) is paramount. b.well implements robust privacy measures, ensuring transparency and control for both patients and clinicians. b.well enables granular access to a patient record, allowing AI to restrict itself to parts of the patient record that the patient or clinician has allowed it to access. b.well also automatically tags sensitive data like reproductive data or HIV related data, so AI can easily skip parts of the health record if requested by the patient or clinician.
- Continuous Improvement and Monitoring
- Ongoing assessment of data quality and adaptive AI model refinement are key to maintaining the effectiveness and reliability of AI solutions. b.well provides tools for AI to track answers and user feedback in a HIPAA and HITRUST-compliant environment. This enables AI to continuously improve without worrying about PHI concerns.
Point 2: You Have the Data, Now What? Turning Data into Actionable Insights
What Does Successful AI in Healthcare Look Like?
Intelligent Data Linking and Reconciliation
By connecting patient records across systems and resolving conflicts, b.well eliminates duplicates, ensuring a comprehensive view of patient information. For example, b.well links a prescription from the doctor to the fill record from the pharmacy to the payment record from the payer.
Advanced Data Interpretation
Transforming raw data into meaningful insights allows for the creation of comprehensive patient profiles and predictive models, driving proactive healthcare interventions. b.well automatically generates care gaps, quality measures, and risk scores that can be used by AI to provide answers using industry standard guidelines.
Trust-Driven AI Development
b.well’s structured approach to AI trust involves a phased testing and validation process, ensuring that AI solutions are reliable and effective. Patients and clinicians are deeply involved throughout the process, and their feedback is used to improve and validate AI.
Point 3: The Data Refinery – b.well’s Approach to AI-Powered Healthcare
Key Focus Areas: Data Quality, Trust, and Strategic Implementation
Data Quality Dimensions
- Data Quality can be measured in five dimensions: Accuracy, Actionability, Impact, Timeliness, and Safety
- Accuracy – How accurately does the data represent the real-world situation?
- Actionability – How easy is it to take an action based on this data?
- Impact – What impact is enabled by this data?
- Timeliness – Is this data available in a timely manner?
- Safety – How does this data enable safe use of the data?
Building Trust Through Transparency
By clearly communicating AI capabilities and limitations, and providing user control and feedback mechanisms, b.well fosters trust in its AI solutions.
Continuous Innovation
Regular model retraining and adaptive AI improvement strategies ensure that b.well’s AI solutions remain at the cutting edge of healthcare technology.
Conclusion
Data is a strategic asset that, when harnessed correctly, can transform the healthcare landscape. By focusing on data quality, trust, and continuous innovation, b.well is setting new standards for AI integration in healthcare. We encourage healthcare organizations to invest in data and AI capabilities, recognizing the transformative potential of AI in creating a more efficient and effective healthcare system.
We’ll be at HLTH 2025 in Las Vegas, discussing these topics in our session, “Inside the CMS Conversational AI Assistant Pledge.” Stop by our booth for engaging discussions and live demonstrations on AI-powered consumer experiences.
Book a time with us in advance for a chance to win a Samsung Galaxy Watch8!
