Conference Presentation, Panel, Fireside Chat
Boundless Potential: How Unlocking Big Data Can Change Health
- Big data is expected to meaningfully impact drug discovery, development, clinical trial efficiency, patient enrollment, and value demonstration over the coming period, though its current maturity lags behind five-to-ten-year-old anticipations due to episodic, incomplete data collection and NLP barriers.
- The analysis paradigm is projected to shift from massive, episodic phenotype databases toward smaller, more complete, and highly examined data subsets, with AI layers running on big data sets becoming inexpensive to facilitate structural cost changes.
- Synthetic comparators utilizing curated historical data for small cell lung cancer trials are projected to reduce trial time by at least 50%, lower costs by at least 15%, and potentially increase overall survival lengths, supported by new FDA guidance allowing the use of Project Data Sphere.
- Financial incentives representing 5% to 10% of a doctor's take-home pay are likely to be tied to personalization and value-based care, driving the delivery system to reorganize around these needs, while payers must implement risk models to drive cultural change on provider selection.
- Immediate financial efficiency requires prioritizing the 5% of patients consuming 50% of healthcare resources, whereas the industry must simultaneously assemble feedback loops to connect unlinked data sets and improve the speed of consumer experience results to match modern application standards.
- The "All of Us" precision medicine program expects roughly 40% of its one-million enrollment target to be achieved through direct consumer enrollment via apps or health portals, and genomic sequencing costs are projected to continue declining to benefit diverse patient populations.
- Project Data Sphere is projected to surpass the 100,000th patient milestone as the largest open-access cancer clinical trial repository, while blockchain technology is expected to scale within the next year to enable private, de-identified linkage of distributed genomic information.
- Environmental mitigation is anticipated to reduce particulate matter concentration by around 10% and asthma risk by 27% through the use of GPS chips on inhalers to map attack locations, while the NSA is exploring healthcare datasets to refine small signal detection algorithms.
- Current systemic challenges include the transition discharge service rate for eligible Medicare patients remaining under 15%, generic Avastin distribution lagging at 15% despite cost advantages, and a culture where nearly zero patients request copies of discharge instructions despite hospital claims of compliance.
- Risks to progress include the need for evolved policy frameworks and patient willingness to link data across jurisdictions, the absence of organizational structures to fully utilize pain treatment variability reduction models, and the persistence of data silos despite administrative efforts to break them down.