Zero-burden Risk Assessment (ZeBRA) Platform for Point-in-care Universal Screening of Complex Disorders
SUMMARY
ZeBRA is a software-based platform for universal, point-of-care risk screening that uses existing EHR data to identify patients at elevated risk for complex disorders such as Alzheimer’s disease and related dementias.
The Unmet Need: Current early-detection pathways for complex disorders such as Alzheimer’s disease are too invasive, expensive, or operationally burdensome to support broad population screening
- Alzheimer’s disease and related dementias are typically identified late, often after meaningful cognitive decline has already occurred. Earlier intervention is increasingly important as treatment development shifts toward prodromal and presymptomatic stages. However, current approaches to early detection often rely on biomarker assays, imaging, or structured cognitive testing that are difficult to deploy universally. Similar barriers exist for other complex disorders that lack simple, scalable screening tools. At the same time, healthcare systems already collect large volumes of longitudinal data through routine medical encounters. Those records contain diagnostic, prescription, and procedure histories that may encode latent risk patterns years before formal diagnosis. Most health systems do not currently use that data in a practical, point-of-care way for universal screening.
The Proposed Solution: ZeBRA is an AI-driven software platform that analyzes routine longitudinal EHR data to generate explainable, zero-burden risk scores for complex disorders years before conventional diagnosis
- The faculty inventor developed ZeBRA, a software-based clinical risk screening platform designed to identify patients at elevated risk for complex, hard-to-diagnose diseases using only data already present in the electronic health record (EHR). The core idea is to convert routine healthcare data- diagnoses, prescriptions, procedures, and other structured clinical history- into an actionable risk signal without requiring additional tests, patient questionnaires, imaging, biospecimen collection, or other burdensome screening steps. In that sense, the platform is “zero-burden”: it does not ask the patient or provider to do anything new at the point of initial risk assessment beyond using information already collected during standard care.
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Unlike conventional screening approaches that depend on disease-specific biomarkers or specialty workflows, ZeBRA is built to function as a front-end population screening and triage layer. It is intended for conditions where early detection is clinically valuable but difficult because confirmatory diagnostics are invasive, expensive, capacity-constrained, or not routinely ordered until symptoms have progressed. The platform is therefore especially suited to disorders such as Alzheimer’s disease and related dementias (ADRD), idiopathic pulmonary fibrosis (IPF), post-traumatic stress disorder (PTSD), and other complex conditions in which subtle longitudinal patterns may appear in the medical record well before definitive diagnosis.
ADVANTAGES
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No new burden on patients or clinicians at the point of data collection
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Software-only deployment model
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Compatible with routine EHR workflows
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Potentially useful for population screening, referral triage, and trial enrichment
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Modular platform design for expansion across multiple disease states
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Explainable output through physician-facing risk interpretation tools
APPLICATIONS
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Primary care screening for ADRD risk
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Identification of candidates for specialist referral
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Trial enrichment for neurodegenerative and other complex disorders
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Payer population health analytics
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Expansion to additional disease-specific risk modules such as IPF and PTSD