Led by Brian Alper, MD

Clinical Informatics, Evidence Infrastructure, Data Standards, and Program Interoperability

The NSMS National Clinical Informatics Center (aData™) is an advanced clinical informatics and biomedical data infrastructure program integrating evidence, clinical data standards, interoperable health information systems, common data elements (CDEs), FHIR-based exchange, data quality, and computable knowledge to support next-generation translational research and precision medicine.

Led by Brian Alper, MD, aData™ develops the informatics infrastructure required to transform heterogeneous clinical, research, physiologic, laboratory, imaging, and patient-generated data into standardized, interoperable, analysis-ready, and clinically actionable information.

aData™ bridges:

• Clinical Informatics

• Evidence and Knowledge Systems

• Common Data Elements (CDEs)

• FHIR / HL7 Interoperability

• Biomedical Data Standards

• Clinical Research Informatics

• Data Quality and Provenance

• Real-World Data and Evidence

• AI-Ready Clinical Data

• Program and Ecosystem Interoperability

Mission

To build a trusted national clinical informatics infrastructure that transforms biomedical data and evidence into standardized, interoperable, computable, and clinically actionable knowledge across research, healthcare, and home environments.

Core Clinical Informatics Programs

Clinical Informatics & Interoperability

Development of interoperable clinical and research information systems supporting:

• FHIR / HL7-based data exchange

• Common Data Elements (CDEs)

• Standardized clinical terminology

• Cross-platform semantic interoperability

• Clinical and research data harmonization

• API-based data exchange

• Electronic health record integration

• Patient-generated health data

• Device and sensor interoperability

• Longitudinal clinical data integration

These capabilities provide the digital foundation connecting patients, clinicians, researchers, devices, AI systems, laboratories, and healthcare institutions.

Evidence & Computable Knowledge

aData™ develops infrastructure for transforming scientific and clinical evidence into structured, computable knowledge capable of supporting research and clinical decision-making.

Core capabilities include:

• Evidence synthesis

• Evidence-to-data translation

• Structured clinical knowledge

• Computable evidence models

• Clinical guideline representation

• Knowledge provenance

• Evidence grading

• Machine-readable clinical recommendations

• Decision-support integration

• Continuous evidence updating

The objective is to create a traceable pathway from evidence → data → knowledge → decision → outcome.

Common Data Elements & Data Standards

aData™ establishes standardized information models that enable consistent data collection, interpretation, exchange, and analysis across programs and institutions.

Key activities include:

• CDE development and implementation

• Data dictionaries

• Metadata standards

• Terminology mapping

• Ontology alignment

• Phenotype definitions

• Endpoint harmonization

• Measurement standardization

• Dataset specification

• Cross-study data harmonization

These standards enable data generated by different investigators, clinical sites, devices, and computational platforms to remain interpretable and reusable across the full research lifecycle.

Data Quality, Provenance & Governance

aData™ develops rigorous frameworks for ensuring that clinical and research data are trustworthy, reproducible, and fit for their intended use.

Capabilities include:

• Data-quality assessment

• Automated validation

• Source traceability

• Data lineage and provenance

• Missingness and anomaly detection

• Version control

• Dataset validation

• Auditability

• Governance frameworks

• Reproducible data pipelines

These capabilities establish a trusted data foundation for clinical research, regulatory evidence generation, and AI-enabled medicine.

Program Interoperability

aData™ provides the interoperability architecture connecting NSMS programs, external collaborators, clinical research networks, healthcare systems, devices, and computational platforms.

The program supports:

• Cross-program data architecture

• Interface specifications

• FHIR APIs

• CDE implementation

• Shared information models

• Research-system interoperability

• Device-to-cloud integration

• Clinical-to-research data exchange

• Multisite data harmonization

• Federated and distributed research environments

This architecture allows independently developed technologies to participate within a common clinical and translational data ecosystem.

Clinical Technology Platforms

aData™: Clinical informatics, data standards, interoperability, and evidence infrastructure

aEvidence™: Computable evidence and knowledge translation

aCDE™: Common Data Elements and standardized information models

aFHIR™: FHIR-based clinical, research, device, and program interoperability

aQuality™: Data quality, provenance, validation, and governance

aKnowledge™: Computable biomedical knowledge and clinical decision infrastructure

aExchange™: Secure cross-institutional clinical and research data exchange

AI-Ready Data Infrastructure: Standardized, provenance-aware data pipelines supporting machine learning, digital twins, autonomous clinical systems, and precision medicine

R&D / Clinical Domains

• Clinical Informatics

• Biomedical Informatics

• Health Data Interoperability

• Evidence-Based Medicine

• Common Data Elements

• FHIR / HL7

• Clinical Research Informatics

• Real-World Data and Evidence

• Data Quality and Provenance

• Biomedical Knowledge Representation

• Clinical Decision Support

• Digital Health

• AI-Ready Clinical Data

• Multisite Research Infrastructure

• Precision Medicine

• Translational Informatics

Integrated NSMS Digital Ecosystem

aData™ serves as the clinical information and interoperability backbone connecting NSMS technology and translational platforms.

aSensors™ → aData™
Continuous physiologic and device-generated data

aEyes™ → aData™
Multiscale imaging and diagnostic information

aLab™ → aData™
Laboratory, molecular, and experimental data

aTwins™ ↔ aData™
Longitudinal patient data and digital twin models

DrRobots™ ↔ aData™
Autonomous clinical systems, observations, decisions, and intervention data

aData™ → Clinical & Research Ecosystems
Standardized evidence, CDEs, FHIR resources, interoperable datasets, and computable knowledge

Together, these platforms establish an integrated pathway:

Sense → Standardize → Integrate → Understand → Generate Evidence → Decide → Intervene → Learn

Leadership

Brian Alper, MD
Director, NSMS National Clinical Informatics (aData™)
Clinical Informatics & Program Interoperability Lead

Brian Alper, MD, leads NSMS clinical informatics, evidence infrastructure, data standards, and interoperability initiatives. His work focuses on connecting clinical evidence, standardized data, computable knowledge, and interoperable information systems to enable rigorous translational research and next-generation clinical medicine.

Under his leadership, aData™ provides the standards and information architecture needed to connect clinical care, research, sensing technologies, AI systems, digital twins, autonomous laboratories, and robotic healthcare platforms within a unified, evidence-centered ecosystem.