Atlas connects six federal and international data systems into one analytical surface. Financial, clinical, regulatory, governance, forensic, and network intelligence across every organ procurement organization, transplant center, and donor hospital in the United States — benchmarked against 93 countries worldwide.
Enter Atlas →45M+
Data Points
9,034
Entities
27,787
Connections
93
Countries Benchmarked
Capabilities
Beneish M-Score, Benford’s Law, Mahalanobis distance, and ratio stability analysis adapted from corporate finance to non-profit healthcare cost reports. Cross-referenced against IRS 990 filings with automated discrepancy detection.
Cost per donor, cost per organ transplanted, organs per million population, donor yield, and referral conversion rates. Every OPO ranked against national benchmarks with CMS CALC-derived donation rates.
Automated quality checks across CMS cost reports, IRS filings, OPTN donor data, and SRTR clinical outcomes. 55 validation rules flag inconsistencies. Direction-aware gap analysis at hospital and OPO scale.
27,787 edges connecting OPOs, hospitals, transplant centers, and vendors across five relationship types. Shared vendor detection, related-party transaction tracing, and cross-OPO linkage suspicion scoring.
48,718 hospital survey citations. 1,019 transplant center deficiencies. 505 OPO citations. Congressional investigation findings. FDA tissue adverse events. Misconduct registry spanning two decades.
Donation rates and transplant volumes for 93 countries across six WHO regions. Compare U.S. OPO performance against Spain, the UK, Eurotransplant, and the global frontier.
Longitudinal panel tracking every OPO across six fiscal years. Cost structure decomposition, year-over-year growth rates, change point detection, and trajectory clustering for performance trending.
Five specialized agents collaborate on natural language queries. Financial forensics, regulatory compliance, clinical outcomes, network analysis, and investigative synthesis. Ask a question, get an evidence-chained answer.
Unsupervised Discovery
Isolation Forest, Local Outlier Factor, PCA, and UMAP run across every entity in the system. No pre-defined hypotheses. Anomalies surface from the convergence of financial, regulatory, clinical, and network signals simultaneously.
43
Features per entity
6
Consensus anomalies detected
55
Automated quality checks
Data sources
SHA-256 provenance chain on 45 million rows. 5 GB of archived source documents. No derived metric exists without a path back to its origin.
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