Healthcare AI
March 6, 2024

This AI Startup That You Haven’t Heard Of (Yet) Is Set to Transform Healthcare and Health Data Management

Fulcra Dynamics' Co-Founder Ash Kalb shares how their platform integrates health data, enabling personalized insights for preventative care and precision medicine.
Written by Ankur Patel
This is a summary of an episode of Pioneers, an educational podcast on AI led by our founder. Join 2,000+ business leaders and AI enthusiasts and be the first to know when new episodes go live. Subscribe to our newsletter here.

Smart devices like Apple Watches and Fitbits produce billions of health data points, highlighting the crucial need for AI to aggregate and interpret this information effectively. Fulcra Dynamics, led by Co-Founder Ash Kalb, leads this charge with a unified app that not only consolidates health data but also unlocks insights and patterns, signaling a revolution in healthcare. In this week’s episode of Pioneers with Ash, we explored Fulcra's potential to reshape healthcare.

With over $35 billion invested by the U.S. Department of Health and Human Services in healthcare IT, platforms like Fulcra are poised to merge personal device data with clinical records, enriching individuals' health perspectives.

Fulcra's approach transforms personalized, preventative healthcare by melding data from wearables, medical records, and apps into actionable insights for users to proactively manage their wellness. This platform benefits both individuals and healthcare providers by delivering comprehensive patient data for improved care. The integration of AI agents with Fulcra's technology is set to revolutionize precision medicine, highlighting AI's vital role in healthcare's future.

Here are the key points from our conversation:

  • Wearables are producing unprecedented personal health data, but data silos limit insights. Platforms like Fulcra integrate data for analysis.
  • Complete health timelines help practitioners detect emerging patterns earlier and prescribe preventative care. Patients can also self-assess lifestyle correlations.
  • By relating diverse data inputs, Fulcra produced a tailored nutritional tweak for significantly improved sleep.
  • Broad wellness advice fails to account for personal variability. Fulcra contextualizes AI for customized recommendations.
  • Digestible integrated data augments practitioners’ expertise to spot multi-week trends and personal needs.
  • Voluntary participation combining health data at scale will uncover individual differences and power next-generation personalized care.

Before we dive in, check out the full episode here:

The Power of Longitudinal Health Insights

As Ash points out, traditional doctor check-ins are often episodic, only providing a snapshot of a patient's health at that moment in time. Doctors rely heavily on patient reports of symptoms along with limited testing data.

“You're showing up to the doctor, they're doing an exam, they're maybe doing some tests,” Ash explains. “They perhaps have the results of the last time that you did that test, but what they don't really have is any qualitative data since the last time you saw them."

This episodic nature of care limits practitioners' abilities to detect emerging patterns or provide tailored preventative health advice. Having access to longitudinal integrated data can fill those gaps with a more complete picture. As McKinsey reports have highlighted, aggregating data across the entire cycle of care allows for continuous improvement through ubiquitous analytics. Integrating symptom data from wearables along with electronic health records, treatment plans, and outcomes can enable precision insights.

Platforms like Fulcra offer the potential to arm practitioners with richer longitudinal patient data, including both device metrics and testing history. Rather than relying primarily on patient recall of intermittent issues, doctors could make assessments based on emerging multi-week patterns. Preventative interventions could then be prescribed based on a holistic data-driven view, enabled by integrated personal data platforms.

The benefits of longitudinal data also extend directly to patients themselves. By de-siloing data from wearables, medical records, lifestyle apps, and more, individuals can self-assess health and wellness patterns that previously required a doctor visit to detect.

"You can just see all your data lined up horizontally and start to glean insights just by looking at it. And people have found some really interesting things just by exploring their data and their timeline," Ash adds.

Patients become empowered to make connections between lifestyle factors, address issues proactively, and take greater agency in preventative care when equipped with integrated longitudinal personal data. The potential for self-directed optimization and improved quality of life is immense.

Personalized Insights Lead to Lifestyle Improvements: Case Study

As a prototype for the potential of personalized insights, Ash discussed an example of how Fulcra led to quantifiable lifestyle improvements for him personally. By intersecting diverse data streams including food logs, sleep data, calendar appointments, and more, a computational notebook analysis was able to detect a dietary change that could optimize Ash’s sleep patterns.

Specifically, the analysis showed that "You're not getting enough protein before you go to bed, and because of this, you're not producing the right enzyme to help you stay asleep."

Simply adjusting his evening nutrition to add more protein resulted in Ash sleeping 1-2 more hours per night. This dramatic improvement was only possible because of the integrated multi-modal view of his personal data.

The limitations of generalized health advice become clear in light of the success of this customized recommendation. As Ash explained, a device like the Oura Ring provides only average sleep optimization suggestions based on aggregated user data.

"It's giving me advice based on effectively the average of all Oura Ring users. It's not giving me really great personalized advice,” he explains.

The Limitations of Generalized Health Advice & Contextualizing AI Agents for Better Health Support

As the previous personalized sleep insights case illustrates, general wellness recommendations often fail to provide tailored guidance due to lack of data specificity. Forward-thinking experts in the AI space have discussed the potential of AI agents, including natural language models like GPT, to generate highly customized health optimization advice when equipped with integrated personal data context.

However, as Ash emphasized, the current limitations of many AI assistants stem from having no visibility into users' actual lives.

”AI agents are incredible, and the advancements we've seen in this space over the past couple of years are just mind blowing. But the state of the art today is an agent that you can interact with, but that doesn't know very much about you."

Thought leaders highlight how properly normalized and cleansed data is crucial for AI agents to draw accurate inferences. By handling tedious data pipeline tasks like deduplication and semantics alignment behind the scenes, Fulcra's platform ensures context reliability for downstream AI. Centralizing data also enables efficient permissioning changes.

"You'll have one place to look and see where you've shared your data," and can revoke access.

With user trust as the highest priority, the potential for AI agents to provide personalized support hinges on controlled data sharing that balances privacy and functionality. As algorithms continue advancing, the agents personalized with integrated life data access could offer invaluable, customized health guidance.

Optimizing the Patient-Practitioner Relationship

While integrated personal data offers tremendous potential to enhance preventative care, realizing that potential depends on human practitioners’ ability to parse insights.

“I don't think we're going to get anywhere by just giving doctors huge amounts of data and expecting their very busy schedules to expand to consume that.”

The data, he believes, must be digestible. Platforms like Fulcra allow patients to share tailored data access with their providers to promote more holistic care. That data can include device metrics, testing history, and even subjective factors like mood or diet.

“More data presented correctly to the medical practitioner or your coach, empowers them. It doesn't overwhelm them.”

Enabling practitioners with richer longitudinal insights stretches their expertise further as well. Rather than rely solely on symptom recalls and static lab tests, doctors can spot multi-week trends. This transforms the practitioner’s role to proactive pattern-hunter. AI assistance further expands possibilities – not as a replacement, but as a diagnostic force-multiplier.

“Having systems in the loop that help everybody by making suggestions are very, very powerful.”

With the right data foundation, he argues, human expertise augmented by AI will reshape patient relationships and outcomes.

The Path Towards Precision Medicine

While personalized insights at the individual level showcase the power of integrated data, advancing precision medicine ultimately hinges on voluntary participation in large-scale studies. As Ash explains, Fulcra’s privacy-first architecture technically precludes anonymized aggregation of user data. But, the platform facilitates opt-in sharing into third party research efforts.

Specifically, Ash discussed an example around using Fulcra for competing in the ongoing XPRIZE longevity challenge. Participants can choose to integrate and share multi-modal device data, medical records, genetics, and more to help uncover new insights into extending healthy lifespans. Maintaining user control via permissioned access, rather than reliance on anonymization or de-identification, represents a trust-based path to population health discoveries.

Enabling this type of voluntary data sharing fuels a virtuous cycle – not just surfacing personalized recommendations, but also understanding variability. As research powered by integrated data better elucidates which interventions work remarkably for some individuals versus others, truly personalized medicine emerges. Embracing and planning for diversity of outcomes leads to more tailored solutions.

Platforms like Fulcra sit at the center of this transformation – acting as high integrity data integrators, stewards, and permission engines. By tackling the challenges of aggregating, normalizing and aligning, Fulcra’s “data layer for AI” liberates researchers, practitioners, and individuals to gain insights which strengthen preventative care. In the future, maintaining voluntary participation and trust will shape the advancement of database precision medicine.

Conclusion

The path towards preventative, precision medicine lies in embracing integrated personal data. By deconstructing walled gardens and intelligently intersecting scattered inputs from devices, records, apps and daily life, platforms like Fulcra empower individuals and practitioners. But responsibly scaling understanding also touches researchers, regulators and the greater ecosystem collaborating around trust-based health data integration.

Through securely connecting authoritative medical knowledge with rich longitudinal patient context, the next generation of diagnosis, treatment and coaching more comprehensively and continuously curates optimal interventions for each body and mind. Precision springs from mass customization capabilities finally matching medicine's personalization promise. By empowering practitioners and individuals alike with carefully-harnessed data abundance, Fulcra leads towards this high-definition future fueled by greater goodwill, participation and awareness in managing secure access to power and better living.

Want to learn more about AI in healthcare? Check out this episode on AI-driven solutions for healthcare cost reduction with Mark Michalski, CEO of Ascertain.

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