AI may be the hottest topic in healthcare, but most organizations still aren’t ready to use it at scale. In this episode, host Sandy Vance chats with the CEO of Hart, Dominique Gross. Together, they break down the real barriers holding healthcare back: from fragmented data and legacy EHR systems to inconsistent standards and limited access. Dominique shares how building a semantic data layer is helping organizations unlock their data, scale innovation safely, and move from pilot projects to real enterprise impact.
In this episode, they talk about:
Many healthcare organizations are eager to adopt AI, but they struggle to scale beyond pilot programs due to foundational data challenges.
The most immediate barrier to innovation is simply gaining access to all relevant data across fragmented and legacy systems.
Data quality is just as critical as access, as organizations must normalize and clean their data before it can be used effectively.
Legacy electronic health records often contain valuable historical data, even if organizations are hesitant to use it due to inconsistencies.
Patients ultimately benefit when their full medical history is accessible, rather than only recent encounters.
HART has developed a semantic data layer that acts as a “translation system” across different EHRs, enabling consistent data use.
This approach allows organizations to aggregate, migrate, and stream data more efficiently across dozens of systems.
One health system successfully scaled from connecting a small number of affiliates to centralizing more than 60 data sources over time.
The same organization was able to complete a major EHR migration in under 12 weeks by extracting, normalizing, and preparing data for a new system.
Proprietary data models within EHR systems create significant barriers to interoperability and data portability.
Despite increasing regulation and improved standards, accessing complete and meaningful data remains a challenge across vendors.
Market consolidation is likely to continue, as organizations seek fewer vendors that can handle multiple data needs.
Clinical research remains an underutilized opportunity, with many organizations still relying on manual processes to identify eligible patients.
Improving data accessibility could dramatically accelerate patient recruitment and engagement in clinical trials.
Simple improvements in data completeness and standardization can have immediate impacts on reimbursement, efficiency, and patient care.A Little About Dominique:
As CEO of Hart since 2023, Dominique Gross provides healthcare data leadership, guiding the company’s mission to eliminate healthcare data fragmentation and empower organizations to achieve true interoperability. With more than two decades of experience driving health IT innovation and go-to-market strategies, Dominique has shaped Hart’s focus on making the impossible possible every day, ensuring that every innovation at Hart advances both operational efficiency and equitable patient care.
Prior to joining Hart, Dominique led strategy and growth initiatives at multiple firms, working as one of the industry's prominent healthcare technology executives to launch connected care solutions for veterans and major health systems. Her leadership philosophy centers on collaboration and integrity, guiding Hart to serve as both a technology provider and a trusted partner for healthcare’s most complex data challenges. Dominique is a frequent speaker on the future of healthcare data ecosystems and a strong advocate for patient empowerment through healthcare data accessibility.
