The phrase “we are not saving lives” is a familiar refrain in advertising, a self-effacing nod to the industry’s secondary role in public life. In most contexts, it’s a healthy reminder not to overstate our impact. But in healthcare, the line between messaging and meaningful intervention can blur. In an environment where information exposure and behavioral nudging are integral to care delivery, advertising becomes more than messaging, it becomes infrastructure.
A landmark study from Cambridge and INSEAD, analyzing over 10 million people across 11 years, found that continuity of care significantly reduces system burden and improves outcomes. Patients who consistently saw the same provider had approximately 5% fewer consultations overall, with the strongest effects among those managing chronic disease, mental health conditions, and geriatric complexity (The Guardian).
For those focused on scale, defensibility, and measurable outcomes, this insight reframes a widely undervalued lever: targeted engagement, when executed with precision and regulatory awareness, can drive real-world health value.
BranchLab’s AI Platform: Turning Non-Health Data into Health Outcomes
BranchLab is an applied AI company built to surface clinical insight from non-health data. The core idea is to deploy, deep learning models, trained on health outcomes data, into non-health environments. The goal is to identify risk patterns that predict downstream clinical events.
These models operate within clients’ non-sensitive data stacks. Without needing PHI, to surface predictive signals from non-health data that are abundant, often real-time, and historically ignored in health decision-making.
Advertising is one of the most obvious applications. It’s scalable, measurable, and already embedded in the consumer journey. By modeling responsiveness, risk thresholds, and latent intent, our platform enables timely, high-ROI interventions that improve adherence, access, and care continuity.
This is not theoretical. Deployments across connected TV (CTV), programmatic media, and offline CRM platforms are demonstrating clinical relevance. This new application of AI is performed without the compliance, privacy, or legal exposure that plagues legacy targeting methods. Increasingly important as some traditional tactics likely are in violation of state-level privacy laws. (Harvard Law)
Advertising as a Scalable Intervention Layer
Healthcare advertising often seems trivial. But as systems evolve to manage patients dynamically, re-engagement, reminders, and nudges become system-critical. Advertising, when informed by predictive AI, becomes not just marketing, but a population health tool.
We are not saving lives…
We are building a bridge between undervalued non-health data and health outcomes, without deploying protected medical data and without waiting for all state regulation to catch up.
We are not saving lives, true, but the data proposes we are building the infrastructure and enabling the interactions that can.