Signal Corps Informatics transforms fragmented healthcare data into decision-grade intelligence.
By harmonizing and integrating real-world evidence, claims, EHR with market insights, we help organizations quantify opportunity, prioritize investments, and build strategies grounded in clinical and economic reality.
Product Lifecycle & Portfolio Management
Organization Strategy
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Enterprise growth strategy & portfolio prioritization
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Operating model design across commercial, medical, and data functions
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Capability assessment & build roadmap (people, process, technology)
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Strategic planning cadence (annual, LRP, and scenario modeling)
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Cross-functional alignment & governance frameworks
Market Definition, Segmentation & Sizing
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Epidemiology and claims-based market sizing models
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Advanced segmentation (needs, behavior, and value-based)
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Target account & NPI-level opportunity modeling
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Patient journey and treatment flow mapping
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Demand forecasting & scenario-based market evolution
Insights & Data Generation
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Primary research (quant/qual/pricing)
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Real-world data integration (claims, EHR, registries)
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Message testing, positioning, and driver diagnostics
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Competitive intelligence & benchmarking
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Insight synthesis into decision-grade narratives
Product Development & Regulatory Enablement
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Target Product Profile (TPP) definition & refinement
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Clinical and evidence generation strategy (HEOR, endpoints)
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Regulatory pathway planning (FDA, CE, CLIA, etc.)
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Payer evidence requirements & value dossier development
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KOL engagement & advisory board strategy
Commercialization & Launch Support
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Target Product Profile (TPP) definition & refinement
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Clinical and evidence generation strategy (HEOR, endpoints)
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Regulatory pathway planning (FDA, CE, CLIA, etc.)
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Payer evidence requirements & value dossier development
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KOL engagement & advisory board strategy
Data Strategy & Informatics
Data Inventory &
Catalog
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Systematic discovery and documentation of enterprise data assets across systems and sources
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Metadata tagging, data dictionaries, and lineage tracking for full asset transparency
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Gap analysis to identify missing, duplicate, or underutilized data across the organization
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Augmentation of raw records with third-party clinical, claims, and reference datasets
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Terminology linkages (e.g., SNOMED CT / ICD, RxNorm / NDC, CPT / HCPCS) to data sets for interoperability and analytics)
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Context layering to transform transactional data into decision-ready intelligence
Data Enrichment
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Implementation guidance for standard terminologies including SNOMED CT, LOINC, ICD-10, and RxNorm
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Ontology design and hierarchy management aligned to clinical and commercial use cases
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Cross-system concept mapping to resolve terminology conflicts and enable interoperability
Terminology &
Classification
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Current-state assessment of data maturity across people, process, and technology dimensions
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Phased roadmap development aligned to organizational priorities and investment constraints
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HL7 FHIR, OMOP CDM, and interoperability standard adoption planning
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KPI framework and milestone governance to track and sustain data program progress
Data Roadmap
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Packaging governed, standardized data assets for internal consumption and external commercialization
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Monetization strategy for proprietary data through licensing, partnerships, and API-based distribution
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Value measurement frameworks linking data product usage to business and clinical outcomes