Jared Goodner on Digitizing the Social Safety Net — Akido Labs | VIVE 2026

Key Takeaways

• Social determinants influence up to 80% of health outcomes
• Akido Labs links emergency, health, and social service data
• Unified SDOH layer enables predictive, upstream care interventions
• Value‑based models gain financial upside by addressing hidden risks
• Socio‑economic data, not genomics, is next health frontier

Pulse Analysis

The rise of value‑based reimbursement has exposed a glaring blind spot in traditional electronic health records: they were built for billing, not for capturing the socioeconomic forces that shape health. Studies from the Robert Wood Johnson Foundation show that factors such as housing stability, food security, and local pollution account for the majority of patient outcomes, yet most EHRs lack fields to record this "dark matter." As payers penalize readmissions and reward preventive care, health systems are forced to look beyond clinical metrics to avoid financial penalties and improve population health.

Akido Labs tackles this gap by aggregating fragmented public datasets—emergency response logs, public health surveillance, and social service enrollment—into a single, actionable intelligence layer. Advanced geospatial mapping aligns zip‑code level SDOH indicators with patient records, enabling predictive algorithms to flag neighborhoods at risk of spikes in conditions like asthma or diabetes. Care teams can then deploy social workers, housing assistance, or nutrition programs before patients present to the emergency department. This proactive approach not only reduces costly acute care episodes but also aligns with the broader goal of health equity, turning data into targeted community interventions.

The market implications are significant. Investors are pouring capital into health‑tech firms that can operationalize SDOH, and policymakers are encouraging data sharing through initiatives like the Health Information Exchange. Akido Labs’ model demonstrates a scalable path for health systems to meet both regulatory expectations and financial incentives. However, challenges remain around data privacy, interoperability standards, and the need for robust analytics talent. As socioeconomic data becomes the new frontier, firms that master its digitization will likely dictate the next wave of preventive medicine and redefine the economics of care delivery.