xBxBio Data Architecture & Data Framework Policy
Effective Date: April 2, 2024
Last Updated: October 5, 2026
1. Purpose and Public Assurance
This policy establishes xBxBio's public-facing principles for data architecture, data governance, interoperability, quality, provenance, lifecycle management, clinical and laboratory data stewardship, responsible analytics, geographic and facility context, artificial intelligence data governance, and associated controls across the xBxBio ecosystem.
Its purpose is to provide patients, clinicians, caregivers, healthcare organizations, laboratories, research organizations, customers, partners, regulators, public-health stakeholders, and other authorized parties with assurance that xBxBio approaches information as a governed lifecycle rather than as an undifferentiated collection of records.
xBxBio seeks to preserve the relationship among patient identity, source evidence, time, clinical context, provenance, quality, uncertainty, authorized interpretation, and subsequent patient outcomes while supporting responsible clinical action.
2. Public Disclosure Boundary
This is a governance and assurance policy, not an engineering specification. Public disclosure is intentionally limited to functional, scientific, clinical, quality, interoperability, regulatory, and governance principles.
Detailed technical specifications and implementation documentation are maintained separately under appropriate internal controls.
Source code or object code;
Proprietary algorithms, scoring logic, model weights, prompts, formulas, thresholds, calibration methods, or state-transition logic;
Internal database schemas, proprietary mappings, internal ontologies, knowledge-graph topology, routing rules, or interface specifications;
Internal API endpoints, credentials, keys, secrets, network topology, security architecture, vulnerability information, or penetration-test details;
Proprietary Virtual Heart mathematical methods, solver implementation, parameterization, or reconstruction methods;
Customer-specific or tenant-specific configurations, nonpublic datasets, confidential partner information, or trade-secret implementation details.
3. Scope and Future-Capability Rule
This policy applies, as relevant, to current and future xBxBio modules, submodules, functions, subfunctions, data sources, interfaces, devices, models, facilities, geographic contexts, user roles, deployment environments, and authorized workflows whether or not every item is individually named in this document.
The absence of a particular technology, vendor, clinical condition, country, public-health authority, facility type, interface, device, or data source from an illustrative list does not by itself exclude that item when it falls within the defined scope.
4. Global Minimum Baseline
xBxBio establishes a jurisdiction-independent minimum baseline for patient protection, clinical-data integrity, confidentiality, authorized access, provenance, quality, security, resilience, responsible use, and lifecycle governance.
Geographic location alone is not intended to reduce that baseline. Applicable local law, regulation, contract, clinical context, data classification, or risk may require additional controls.
5. Jurisdictional Applicability and Local-Law Control
Before relevant processing, integration, research, clinical functionality, commercialization, or deployment occurs within or affects a jurisdiction, xBxBio is intended to evaluate the applicable international, supranational, national, federal, state, provincial, territorial, regional, county, district, municipal, city, local-health-authority, healthcare-system, facility, laboratory, professional, and site-specific requirements.
Where an applicable jurisdiction imposes greater or additional protection, the relevant requirement supplements the xBxBio baseline. Material conflicts are escalated for appropriate legal, regulatory, privacy, security, quality, clinical, laboratory, data-governance, and technical review before affected processing proceeds.
6. Jurisdictional Deployment Gate
Technical availability does not, by itself, authorize deployment. xBxBio may restrict, localize, segregate, reconfigure, delay, suspend, or decline processing or functionality when applicable requirements cannot be appropriately satisfied.
Privacy and health-data rules;
Cybersecurity and breach-notification requirements;
Medical-device and software-as-a-medical-device requirements;
Artificial-intelligence requirements;
Clinical-research and human-subject requirements;
Genetic, genomic, biometric, and precise-geolocation restrictions;
Data residency, localization, and cross-border-transfer rules;
Laboratory, diagnostic, and professional-practice requirements;
Electronic-record, electronic-signature, retention, and audit requirements;
Customer contracts, payer requirements, and third-party obligations.
7. Representative Jurisdictional Frameworks
xBxBio may need to evaluate, as applicable, legal and regulatory frameworks such as U.S. federal and state health/privacy requirements; European Union and EEA data-protection, health-data, AI, and medical-device regimes; United Kingdom requirements; Swiss requirements; Canadian federal and provincial requirements; Australian federal and state/territory requirements; New Zealand health-information requirements; and applicable regimes across Latin America, Asia-Pacific, the Middle East, and Africa.
This list is illustrative rather than exhaustive. Country-specific controls are maintained through jurisdictional applicability review so that the public policy does not become obsolete when laws change.
8. Geographic and Public-Health Hierarchy
xBxBio may associate authorized patient, facility, clinical, operational, and population information with context at multiple nested geographic levels while maintaining appropriate distinctions between population context and individual patient evidence.
Global and international health context;
Multinational or regional health context;
Country and national health context;
State, province, territory, prefecture, canton, or comparable regional context;
County, district, borough, parish, or comparable local-health context;
City, town, village, municipality, or local-government context;
Health-system and network context;
Facility, campus, site, department, service-line, unit, room, bed, device, encounter, and patient context.
9. World, National, Regional, and Local Health Context
Where lawful, relevant, appropriately sourced, and authorized, xBxBio may incorporate broader health context to support interpretation, planning, resource awareness, research, epidemiology, and population-level understanding. Population information must remain distinguishable from patient-specific clinical evidence.
World and international health indicators;
National public-health indicators and ministry or department of health information;
State, provincial, territorial, and regional health information;
County, district, city, town, and municipal health indicators;
Disease prevalence, morbidity, mortality, hospitalization, and registry data;
Environmental and geographic health context;
Healthcare-resource availability, service access, and population-health trends;
Authorized real-world evidence and public-health alerts.
10. Healthcare Organization, Facility, and Site Architecture
xBxBio may represent organizational relationships needed to establish where information originated, who is responsible for it, which local rules apply, and how data should be interpreted.
Enterprise and parent organization;
Health system and hospital network;
Hospital, academic medical center, community hospital, clinic, ambulatory center, urgent-care center, and emergency department;
Cardiology center, imaging center, diagnostic center, clinical laboratory, reference laboratory, genomic laboratory, pharmacy, rehabilitation facility, telehealth environment, home-health environment, research institution, and clinical-trial site;
Campus, site, department, service line, clinical unit, room, bed, device, workstation, and authorized user relationships.
11. Site-Specific Governance
A single organization may contain environments with different clinical responsibilities, equipment, interfaces, local terminology, licensing conditions, data flows, escalation paths, and operational procedures. Site-specific configuration should therefore remain subordinate to xBxBio global governance while allowing appropriately controlled local requirements.
12. Patient-Centered Architecture
The patient is the central clinical context for authorized longitudinal information. xBxBio architecture is intended to help preserve the relationship among historical and current evidence, clinical events, treatment, monitoring, outcomes, and subsequent evidence without implying that every data category is present for every patient.
13. Clinician and Caregiver Alignment
xBxBio Connected Cardiovascular Intelligence is intended to assist appropriately authorized clinicians, care teams, and permitted caregivers by organizing relevant cardiovascular information in longitudinal and multimodal context.
Access by clinicians, healthcare personnel, family caregivers, patient-designated caregivers, or other persons depends on role, authorization, legal authority, consent, applicable privacy requirements, and the functionality made available to them.
14. Patient-Clinician-Model Relationship
xBxBio data architecture is intended to preserve a clear relationship among patient evidence, computational representation, analytical interpretation, clinician review, patient-specific recommendation or action, and subsequent patient evidence.
Computational outputs are not intended to erase the distinction between source evidence and professional clinical judgment.
15. Epistemic Status of Information
xBxBio is designed to preserve material distinctions among different evidentiary states so that computational or inferred information is not silently represented as direct patient observation.
Directly observed;
Patient-reported;
Measured;
Normalized;
Derived;
Calculated;
Estimated;
Imputed;
Reconstructed;
AI-generated;
Simulated;
Predicted;
Hypothetical;
Clinician-authored or clinician-verified.
16. Longitudinal Patient-State Representation
Authorized information may be organized over time to support a coherent view of changing patient state, disease progression, treatment, monitoring, and outcomes. Earlier evidence and interpretations should remain appropriately distinguishable from later evidence and reinterpretations.
17. Temporal Architecture
Time is a first-class element of clinical interpretation. xBxBio may preserve multiple relevant timestamps rather than collapsing them into a single generic date.
Event time;
Acquisition or measurement time;
Observation time;
Order time;
Specimen-collection time;
Result time;
Procedure time;
Documentation time;
Effective time;
Transmission and ingestion time;
Processing time;
Model or simulation execution time;
Review and approval time;
Modification time;
Time-zone context where relevant.
18. Patient Identity Management
Patient identity controls are intended to reduce duplicate records, wrong-patient associations, incorrect merges, cross-patient contamination, and loss of source identity. Uncertain matches should remain distinguishable from confirmed relationships.
Patient lookup and registration;
Source-system identifier preservation;
Enterprise or federated identifiers where applicable;
Duplicate detection and review;
Merge and unmerge control where supported;
Identity reconciliation;
Demographic comparison;
Confidence assessment;
Manual review and identity audit history.
19. Clinical Timeline Module
The longitudinal timeline may organize authorized multimodal events to support comparison and clinical context.
Chronological and episode-based views;
Date-range and modality filtering;
Medication changes, procedures, imaging, ECG, laboratory, device, telemedicine, model, and Virtual Heart events;
Annotations, historical comparisons, outcome markers, and authorized summaries.
20. Cardiovascular Clinical Domain Coverage
xBxBio architecture is intended to accommodate recognized, emerging, rare, inherited, acquired, acute, chronic, structural, electrical, mechanical, vascular, hemodynamic, inflammatory, metabolic, and treatment-related cardiovascular conditions when relevant to the intended use and available evidence.
Inclusion within architectural scope does not mean that xBxBio independently diagnoses, validates, or is authorized for every condition.
Coronary and ischemic heart disease, acute coronary syndromes, and myocardial infarction;
Arrhythmias, conduction disorders, atrial and ventricular rhythm disorders, and sudden-cardiac-death risk;
Heart failure and cardiomyopathies;
Valvular, structural, congenital, aortic, peripheral vascular, and pulmonary vascular disease;
Hypertension and cardio-renal/cardio-metabolic relationships;
Myocarditis, pericardial, inflammatory, infectious, inherited/genetic, cardio-oncology, pregnancy-associated, pediatric, adult congenital, transplant, device-related, post-procedural, and other clinically relevant cardiovascular states.
21. ECG Module
ECG architecture may support static, live, historical, and comparative electrocardiographic information while preserving source waveform and acquisition context.
Waveforms and leads;
Sampling and acquisition metadata;
Device metadata;
Intervals, rates, rhythm, morphology, and measurements;
Annotations and interpretations;
Current-versus-prior comparison, longitudinal change, and event markers;
Quality indicators, provenance, export, and authorized review.
22. Live Physiological Signal Functions
Where live or near-real-time data are supported, the framework may govern streaming, buffering, timestamping, source-device identity, signal quality, synchronization, recording, event marking, loss detection, and connection status.
23. Echocardiography Module
Echocardiography data may include study identity, cine loops, DICOM metadata, measurements, chamber dimensions, ventricular function, valvular findings, Doppler, strain information where available, structured reports, quantitative results, comparison, interpretation, and provenance.
24. Stress Testing and Exercise Physiology
Stress-test information may include protocol, baseline state, exercise or pharmacologic stages, heart rate, blood pressure, ECG, symptoms, workload, exercise capacity, recovery, imaging relationships, abnormal events, interpretation, timing, and historical comparison.
25. Medical Imaging Module
Imaging architecture may support source images and derived information while preserving the distinction between the original clinical study and downstream analytical products.
DICOM studies, series, instances, and metadata;
Cardiac CT, CCTA, cardiac MR, nuclear imaging, echocardiography, angiography, and other authorized modalities;
Structured reports, segmentation, contours, registration, reconstruction, anatomical labels, quantitative measurements, functional analysis, and longitudinal comparison.
26. Electrophysiology Module
Electrophysiology data may include rhythm studies, intracardiac recordings, mapping information, ablation-related data, procedural events, device information, timing, annotations, findings, and source provenance where available and authorized.
27. Catheterization and Hemodynamics
Cardiac catheterization and hemodynamic information may include procedure context, pressures, gradients, flows, measurements, angiographic relationships, devices, interventions, medication context, source systems, timestamps, reports, and clinical interpretation.
28. Clinical Laboratory and Diagnostic Data Framework
Laboratory information may originate from hospital laboratories, clinical laboratories, reference laboratories, point-of-care systems, research laboratories, genomic laboratories, or other authorized sources. The framework is intended to preserve sufficient analytical and provenance context for appropriate interpretation.
Order, patient, specimen, collection, accession, analytical method, result, unit, reference interval, abnormal or critical status, laboratory, verification, correction, and longitudinal comparison;
Clinical chemistry, hematology, coagulation, cardiac biomarkers, lipids, renal function, electrolytes, endocrine/metabolic measures, inflammatory markers, immunology, molecular diagnostics, genetics, genomics, NGS, pharmacogenomics, toxicology, and point-of-care testing where relevant.
29. Laboratory Result Integrity
Normalized laboratory information should not silently erase the original result, unit, reference range, or correction status. Where available and relevant, source laboratory, specimen, method, timestamps, abnormal/critical flags, terminology, version history, and provenance should remain associated.
30. Laboratory Regulatory and Quality Context
Laboratory functionality is subject to applicable national and local rules governing clinical laboratories, laboratory-developed testing, accreditation, diagnostics, specimen handling, genetic testing, research testing, quality systems, reporting, and professional oversight. xBxBio does not represent that every laboratory or xBxBio environment holds the same accreditation.
31. Genomics, Genetics, and NGS
Genetic and genomic information may require enhanced controls because of sensitivity, familial implications, long-term relevance, and re-identification risk.
Specimen and sequencing context;
Gene and variant information;
Genome build, transcript, annotation, pipeline and report versions;
Pathogenicity or interpretive classification;
Family-history and phenotype relationships;
Quality metrics, laboratory source, consent restrictions where applicable, longitudinal reinterpretation, and provenance.
32. Medication and Pharmacology Data
Medication architecture may distinguish ordered, prescribed, dispensed, administered, patient-reported, active, discontinued, and historical medication states and preserve dose, route, frequency, dates, source, and terminology.
33. Drug-Drug Interaction and Drug Information
Drug-interaction and drug-information functions may support medication-pair review, evidence source, severity, mechanism, duplicate therapy, warnings, contraindications, dosing context, administration information, monitoring considerations, regulatory labeling references, and clinician review. Such information is intended to assist and does not independently determine treatment.
34. Telemedicine and Remote Care
Telemedicine architecture may support encounter relationships, patient and clinician identity, session metadata, documentation, patient-submitted information, remote measurements, device data, consent, communications, attachments, follow-up, and auditability.
35. Wearables and Remote Patient Monitoring
Wearables and remote-monitoring sources may differ materially from regulated clinical devices. Source type, sampling characteristics, algorithmic derivation, device identity, quality, timing, and intended use should remain identifiable where relevant.
36. Insurance, Eligibility, Authorization, and Billing
Administrative and financial data may include payer, plan, coverage, eligibility, authorization, claim, coding, remittance, adjustment, patient responsibility, status, dates, provider, encounter, and transaction history, subject to contractual and jurisdictional requirements.
37. Business Intelligence and Reporting
Authorized business-intelligence functions may support operational, clinical, quality, utilization, service, cohort, longitudinal, and administrative reporting with role-based access, filtering, drill-down, provenance, and appropriate aggregation.
38. Communications and Email-Related Data
Authorized communications may include clinical notifications, administrative notifications, workflow messages, alerts, report delivery, invitations, status updates, and escalation. Sensitive information should be handled under applicable privacy, security, and contractual requirements.
39. Knowledge Graph Data Governance
Where knowledge-graph capabilities are used, xBxBio may govern relationships among patients, events, diseases, phenotypes, measurements, imaging, ECG, laboratory results, genes, variants, medications, procedures, devices, models, evidence, literature, clinicians, organizations, terminology, and time. Public policy does not disclose proprietary graph structures or implementation.
40. Medical Advisor Data Governance
Where enabled, clinician-facing advisory functions may organize source-linked, patient-specific, longitudinal information, evidence, uncertainty, and explanatory context. Such functionality is intended to support rather than replace qualified professional judgment.
41. Geospatial and Location-Aware Data
Where enabled, authorized, proportionate, and legally permitted, location-aware functions may support facility proximity, healthcare-resource discovery, service availability, logistics, jurisdiction determination, regional health context, emergency context, and other approved geospatial uses.
Technical availability of location information is not, by itself, authorization to collect or use it.
Purpose limitation and data minimization;
Consent or other lawful authority where required;
Appropriate precision rather than unnecessary precision;
Role-based access and retention controls;
Protection against inappropriate inference of sensitive characteristics;
Jurisdiction-specific treatment of precise geolocation as sensitive data where applicable.
42. P6-Oriented Data Framework
xBxBio may organize authorized information around Predictive, Preventive, Personalized, Participatory, Precision, and Patient-Pathway concepts. The framework is intended to support patient-specific context and clinician review rather than autonomous treatment determination.
43. Longitudinal 1-Year, 3-Year, and 5-Year Views
Where enabled, xBxBio may present historical or modeled views over different time horizons. Observed history, modeled trajectories, forecasts, risk estimates, and uncertainty should remain distinguishable.
44. Multilingual Text and Speech
The framework may support multilingual display, text input, speech input, text-to-speech, translation, bidirectional communication, and language preferences. Source language and translated content should remain appropriately distinguishable where meaning could be clinically significant.
45. Virtual Heart Data Governance
Where Virtual Heart functionality is applicable, the data framework may govern patient-specific source evidence, model-input classifications, model-generated information, simulation outputs, uncertainty information, provenance, versions, validation status, and relationships between observed and computational information.
This public policy does not describe the proprietary mathematical, computational, reconstruction, solver, calibration, or parameter-estimation methods used to implement Virtual Heart functionality.
46. Virtual Heart Source and Derived Data Classes
Virtual Heart information may include imaging-derived anatomy, geometry, tissue or scar representations, electrophysiological, mechanical, hemodynamic, physiological, boundary-condition, observation, simulation, forecast, uncertainty, historical-comparison, and validation information where applicable. Source evidence and model-generated outputs should remain distinguishable.
47. Historical Reconstruction and Reinterpretation
xBxBio may support retrospective reconstruction of prior patient states using available historical evidence. Reconstructed states should remain distinguishable from directly observed historical facts. New evidence or improved methods may support later reinterpretation without silently erasing prior context.
48. Artificial Intelligence and Machine-Learning Data Governance
AI/ML governance may address source data, training, validation and test datasets, labels, features, input, output, model version, dataset version, provenance, representativeness, bias, leakage prevention, uncertainty, access, retention, and human review.
Public policy does not disclose proprietary models, weights, prompts, feature engineering, scoring logic, or implementation details.
49. AI Output Provenance and Human Oversight
AI-generated information should remain identifiable as model-generated where appropriate. Relevant metadata may include model identity, version, execution time, input context, output, confidence or uncertainty, review status, modification, and final disposition.
Where outputs may affect clinical interpretation, appropriate human oversight should be maintained according to intended use, risk, and applicable requirements.
50. Bias, Representativeness, and Population Limitations
Where relevant, xBxBio may evaluate datasets and models for limitations associated with population, demographics, geography, device type, institution, disease severity, modality, missingness, sampling, and distribution shift. Identified limitations should inform interpretation and governance.
51. Interface and Integration Governance
All authorized interfaces should be governed for identity, provenance, validation, security, versioning, error handling, and controlled change. A mature interface framework addresses failure conditions as well as successful transfer.
Authentication and authorization;
Source and destination identity;
Schema and version;
Patient and facility identity;
Terminology and units;
Timestamps and temporal context;
Duplicate detection, missing data, malformed messages, unexpected values, latency, outage, retransmission, quarantine, retry, and reconciliation;
Audit, security, privacy, retention, and recovery.
52. Healthcare Interoperability Interfaces
xBxBio may support authorized standards and exchange mechanisms such as HL7 FHIR, HL7 v2.x, DICOM, DICOMweb, SMART on FHIR, REST APIs, OAuth-based authorization, OpenID Connect, document exchange, terminology services, event streams, secure file transfer, and other appropriate mechanisms.
Reference to a standard does not mean that every xBxBio interface supports every feature or profile of that standard.
53. EHR and EMR Interfaces
Electronic health-record interfaces may support patient, encounter, diagnosis, medication, observation, order, laboratory, procedure, document, scheduling, provider, and clinical-context information. Vendor references are illustrative and do not imply certification, endorsement, or partnership.
54. Cardiovascular System Interfaces
Authorized cardiovascular integrations may include CVIS, PACS, ECG-management, Holter, telemetry, electrophysiology, EP mapping, catheterization, hemodynamics, stress testing, CPET, echocardiography, cardiac CT, CMR, PET, SPECT, angiography, IVUS, OCT, imaging workstations, and related systems.
55. Laboratory and Diagnostic Interfaces
Laboratory integration may include LIS, LIMS, point-of-care systems, molecular diagnostics, genomics and NGS systems, genetic laboratories, reference laboratories, and other authorized diagnostic sources.
56. Pharmacy, Payer, Administrative, and Enterprise Interfaces
Interfaces may include pharmacy, medication administration, formulary, dispensing, medication reconciliation, payer, eligibility, authorization, claims, billing, remittance, identity provider, SSO, MFA, directory, collaboration, document-management, quality, regulatory, and enterprise reporting systems.
57. Device and Sensor Interfaces
Authorized device interfaces may include ECG devices, implantable cardiac devices, pacemakers, ICDs, CRT systems, monitors, wearables, remote patient monitoring, blood-pressure devices, pulse oximetry, physiological sensors, connected diagnostic equipment, and future authorized devices.
58. Research, Registry, and Public-Health Interfaces
Interfaces may support research EDC, CTMS, registries, biobanks where applicable, real-world-data systems, public-health reporting, surveillance, emergency-health information, national or regional registries, and authorized evidence repositories.
59. Data Ingestion Framework
Data ingestion may include messaging, APIs, streaming, secure file transfer, batch import, clinical interfaces, imaging ingestion, device ingestion, customer upload, database integration, and research-data import.
Source authentication and validation;
Parsing and schema validation;
Terminology, unit, and timestamp handling;
Patient and facility association;
Duplicate identification;
Quality checking;
Provenance capture;
Routing;
Error handling, quarantine, retry, reconciliation, and alerting.
60. Data Normalization and Harmonization
Normalization may address terminology, units, identifiers, dates, times, demographics, devices, laboratory tests, medications, diagnoses, procedures, and imaging metadata. Original values should remain recoverable where appropriate.
61. Semantic Interoperability and Terminology
xBxBio may use or map to recognized terminology systems where licensed and appropriate, including SNOMED CT, LOINC, RxNorm, ICD, CPT, HCPCS, UCUM, UMLS, NDC, device nomenclature, and jurisdiction-specific code systems.
Terminology mapping should preserve source concept, target concept, mapping method, version, confidence, ambiguity, review status, and exception handling where material.
62. Clinical Context Preservation
Clinical values should not be treated as equivalent solely because they have similar names. Interpretation may depend on patient, encounter, indication, anatomy, physiological state, acquisition protocol, device, measurement method, units, reference interval, source, operator, time, medication state, and clinical setting.
63. Metadata Framework
Metadata may describe meaning, source, owner, steward, data type, format, units, classification, terminology, lineage, quality, retention, access restrictions, schema, version, creation date, modification date, and regulatory relevance.
64. Data Dictionary and Catalog
Controlled data dictionaries and catalogs may support field definitions, business and technical meaning, clinical meaning, data type, units, formats, allowed values, null semantics, source, mappings, relationships, quality rules, ownership, lineage, classification, and discoverability.
65. Data Lineage
Lineage should support understanding of how information moves from source to destination through interfaces, transformations, normalizations, calculations, mappings, intermediate stores, analytics, models, and outputs.
66. Data Provenance
Provenance should identify origin and material transformation history where relevant, including source, creator, organization, device, application, model, time, transformation, version, reviewer, and relationship to derived information.
67. Data Integrity and ALCOA+ Principles
xBxBio seeks to protect information against unauthorized or unintended alteration. Where relevant to regulated or quality records, data-integrity practices may be consistent with ALCOA+ concepts: Attributable, Legible, Contemporaneous, Original, Accurate, Complete, Consistent, Enduring, and Available.
68. Data Quality Framework
Data quality is evaluated in relation to intended use rather than by a single universal score.
Accuracy;
Completeness;
Consistency;
Validity;
Timeliness;
Uniqueness;
Conformity;
Referential integrity;
Provenance;
Reliability;
Fitness for purpose.
69. Clinical Plausibility and Quality Rules
Where appropriate, quality controls may evaluate physiological ranges, unit consistency, chronology, patient consistency, modality consistency, terminology, medication logic, laboratory relationships, duplicate events, cross-source discrepancy, required fields, and referential integrity. Automated checks do not replace professional review.
70. Missing Data and Null Semantics
Missing information should not automatically be treated as zero, normal, negative, clinically insignificant, or not applicable. Where material, the architecture should distinguish unknown, unavailable, not collected, not applicable, withheld, pending, and explicitly absent states.
71. Data Reconciliation and Duplicate Control
Reconciliation may compare records received, processed, rejected, stored, transmitted, duplicated, and expected. Duplicate detection may consider patient, source, identifier, event type, time, value, modality, message ID, and other context.
72. Original, Corrected, and Versioned Data
Corrections should not obscure original regulated or clinically relevant information where preservation is required. Changes may require user, timestamp, reason, prior value, new value, approval, and audit trail.
73. Master and Reference Data Management
xBxBio may govern master and reference entities such as patient, provider, organization, facility, device, product, terminology, location, countries, regions, languages, time zones, units, classifications, statuses, and enumerations.
74. Schema and Data-Contract Evolution
Changes to schemas and data contracts should be controlled to address version identification, compatibility, migration, validation, customer impact, deprecation, rollback, and producer-consumer expectations.
75. Operational, Warehouse, Lake, and Analytical Data Stores
Data architecture may include operational databases, warehouses, marts, lakes, lakehouses, analytical stores, semantic layers, and feature stores. Each should be governed for source zones, curated data, derived data, metadata, access, quality, lineage, retention, security, and recovery appropriate to use.
76. Multitenancy and Customer Data Separation
Multitenant architecture should maintain appropriate logical or physical separation of customer information. Customer data should not be exposed to another customer without authorization.
Tenant identity and tenant-aware access control;
Tenant-scoped APIs and permissions;
Configuration isolation;
Audit logging;
Isolation testing;
Contract-based module and function provisioning.
77. Super Administrator and Provisioning Governance
Authorized Super Administrator capabilities may include customer and tenant provisioning, user and role administration, contracted-module enablement, access configuration, support access control, deactivation, audit oversight, and administrative reporting. Detailed provisioning logic and security implementation are confidential.
78. Data Classification
Information may be classified as Public, Internal, Confidential, or Restricted/Highly Sensitive, with enhanced controls for health, genetic, genomic, biometric, precise-geolocation, authentication, financial, insurance, proprietary, research, security, and regulated information as applicable.
79. Privacy by Design and Data Minimization
Data architecture should incorporate purpose limitation, minimization, access limitation, retention control, security, de-identification, pseudonymization, rights management, consent or authorization where applicable, transparency, and accountability.
80. Access Governance
Access should be based on role, authorization, legitimate need, purpose, data classification, contract, jurisdiction, clinical context, and regulatory requirements. Ownership does not automatically imply unrestricted access.
81. Security-by-Design Relationship
This policy should be read together with the xBxBio IT & Security Policy. Data architecture should support appropriate authentication, authorization, encryption, secure transmission, logging, auditability, vulnerability management, backup, recovery, and incident response without publicly disclosing implementation-sensitive security details.
82. Robustness, Reliability, and Resilience
xBxBio systems should be designed and evaluated for robustness appropriate to intended function and risk. Robustness includes the ability of data, interfaces, analytics, models, and workflows to behave predictably when confronted with reasonably foreseeable abnormal conditions.
Incomplete, delayed, conflicting, duplicated, or malformed data;
Unexpected values and missing modalities;
Network, device, interface, or source-system failure;
Terminology, schema, version, or configuration change;
Cybersecurity events, component failure, high computational load, model uncertainty, distribution shift, and unusual user behavior.
83. Degraded-Mode and Fail-Safe Behavior
Where sufficient, valid, timely, or trustworthy information is unavailable, the system should, where appropriate, identify the limitation, preserve available evidence, avoid silently manufacturing missing information, expose relevant uncertainty, restrict affected functionality, notify the authorized user, and support controlled recovery.
84. Computational Robustness
AI, analytical, predictive, and Virtual Heart functions may be evaluated for sensitivity to missing inputs, measurement noise, source variation, parameter variation, assumptions, population differences, device differences, temporal variation, uncertainty, numerical stability, edge cases, and abnormal input conditions. Material sensitivity should not be intentionally concealed from interpretation.
85. Quality Management Integration
Quality is intended to be embedded into the lifecycle of data rather than inspected into it only after processing. Data architecture may support requirements traceability, verification, validation, risk assessment, change control, configuration management, issue management, CAPA where applicable, supplier controls, auditability, evidence preservation, controlled documentation, training, and periodic review.
86. Six Sigma and Process-Quality Principles
xBxBio may apply statistical process-improvement concepts associated with Six Sigma and related quality methodologies where useful for reducing variation, identifying defects, improving process capability, and increasing reproducibility. Use of Six Sigma concepts does not itself represent third-party certification.
DMAIC: Define, Measure, Analyze, Improve, Control;
DMADV: Define, Measure, Analyze, Design, Verify, where appropriate;
Potential applications include ingestion reliability, interface error rates, patient-identity matching, laboratory normalization, missing-data and duplicate rates, processing failures, validation, software quality, defect management, reconciliation, turnaround time, and other measurable characteristics.
87. GxP, GAMP, and Regulated Electronic Records
Where xBxBio technology is used in regulated GxP environments, data architecture may support risk-based validation, lifecycle governance, change control, configuration management, supplier management, data integrity, record retention, audit trails, and GAMP 5 concepts. Where 21 CFR Part 11 or analogous electronic-record requirements apply, relevant controls may be incorporated. Reference does not mean every xBxBio system is a Part 11 system.
88. Research Data Governance
Research information should be governed according to applicable protocol, contract, institutional requirements, ethics requirements, consent, privacy rules, data-use agreements, study design, provenance, versioning, retention, and regulatory obligations.
89. Clinical Trial, Registry, and Real-World Evidence Data
Where applicable, the framework may support study identifiers, subject identifiers, consent, cohorts, observations, endpoints, source evidence, analysis versions, registry data, real-world evidence, publication relationships, and archival while preserving distinctions between research and routine clinical use.
90. Population and Public-Health Data Governance
Population and public-health information may support epidemiology, service planning, surveillance, resource awareness, and research when lawful and authorized. Aggregated or regional information must remain distinguishable from individual-patient evidence and should be used according to appropriate privacy, statistical, and ethical controls.
91. Patient and Data-Subject Rights
Where applicable, architecture may support access, correction, deletion, restriction, objection, portability, consent withdrawal, transparency, and other jurisdiction-specific rights, subject to clinical-record integrity, legal holds, research obligations, retention requirements, and other lawful limitations.
92. Consent, Authorization, and Restrictions
Where relevant, xBxBio may support recording of consent, authorization, withdrawal, restriction, effective date, scope, purpose, and jurisdiction. The existence of a technical field does not determine whether a particular legal basis is valid.
93. Data Localization and Sovereignty
Some jurisdictions or contracts may require country-specific or regional storage and processing. Architecture may therefore support regional hosting, restricted replication, controlled administrative access, data segregation, regional backup, regional disaster recovery, and geographic restrictions.
94. Cross-Border Data Transfer Governance
Information should not be transferred between jurisdictions merely because a technical connection exists. Transfer may require assessment of source and destination jurisdictions, data class, patient information, lawful basis, contractual safeguards, transfer mechanisms, encryption, access restrictions, government-access risk, localization requirements, subprocessor location, and customer requirements.
95. Data Retention, Archival, and Secure Disposal
Retention may depend on data type, intended use, clinical need, contract, law, regulation, research, quality, litigation hold, intellectual-property protection, and business need. Eligible information should be archived or disposed of using controlled methods appropriate to sensitivity and legal obligations.
96. Backup, Recovery, and Data Resilience
Backup and recovery controls may address scheduled backup, integrity, encryption, access, retention, geographic separation where appropriate, restoration testing, recovery priorities, metadata, relationships, audit history, and required processing capability.
97. Data Incident Management
Material data incidents may include wrong-patient association, corruption, loss, duplication, unauthorized access, disclosure, invalid transformation, terminology failure, identity failure, cross-tenant exposure, model-data contamination, provenance loss, or significant quality failure.
Detection and containment;
Investigation and classification;
Correction and recovery;
Notification where required;
Root-cause analysis;
Preventive action and documentation.
98. Third-Party and Vendor Data Governance
External data, systems, vendors, subprocessors, cloud providers, and technology partners should be evaluated according to data sensitivity, rights, provenance, service criticality, security, privacy, quality, business continuity, subprocessing, data location, contractual obligations, and applicable regulatory requirements.
99. Data Sharing and Secondary Use
Data sharing and secondary use should be evaluated for authorized purpose, recipient, minimum necessary scope, classification, contract, consent or other lawful authority, security, jurisdiction, retention, transfer mechanism, and restrictions on reuse.
100. Data Portability and Avoidance of Unnecessary Lock-In
Where legally and contractually appropriate, xBxBio may support authorized export using suitable formats and recognized standards. Proprietary functionality may be used where it provides legitimate value, but portability and source provenance should be considered in architecture decisions.
101. Data Ethics and Responsible Use
Use of information should consider patient welfare, proportionality, privacy, fairness, potential harm, bias, transparency, appropriate access, human oversight, scientific integrity, and responsible innovation.
102. Human Oversight and Clinical Responsibility
Where data transformations, analytics, AI, predictions, or simulations may materially affect interpretation, appropriate human review should be maintained according to intended use, risk, regulation, and clinical context. xBxBio technology is intended to assist rather than eliminate professional responsibility for clinical judgment.
103. Data Risk Assessment
Data-related risks may include incorrect patient association, missing or corrupted information, incorrect terminology or units, invalid transformation, temporal misalignment, unauthorized access, privacy violation, cross-tenant exposure, model-data leakage, provenance loss, inconsistent versions, inappropriate secondary use, and misleading presentation of modeled information as observed fact.
104. Change Management and Architectural Review
Material architectural changes should be subject to appropriate impact assessment, documentation, review, testing, validation, approval, migration planning, rollback planning, privacy review, security review, clinical review, quality review, and regulatory review where applicable.
105. Architecture Documentation
Controlled internal documentation may include conceptual, logical, and physical models; entity relationships; data flows; interface diagrams; data dictionaries; lineage; metadata; classifications; retention rules; terminology mappings; validation evidence; and change history. Sensitive implementation details remain nonpublic.
106. Scalability and Performance
Data architecture should support expected growth in patients, studies, images, signals, measurements, devices, clinical events, simulations, AI features, model outputs, customers, interfaces, and jurisdictions. Performance optimization should not compromise data integrity, provenance, security, or governance.
107. Observability of Data Pipelines
Data pipelines may be monitored for failure, delay, unexpected schema change, quality degradation, duplicate ingestion, missing data, transformation error, interface outage, reconciliation variance, and processing status.
108. Customer Configuration and Shared Responsibility
Customer configuration may affect roles, user provisioning, local identity management, integrations, local network and endpoint security, workflow, data accuracy, retention, and customer-specific obligations. Configuration should not intentionally bypass core integrity, security, or governance controls.
109. Pre-Commercial and Research-Stage Capabilities
Some xBxBio capabilities may be research-stage, development-stage, prototype, demonstration, validation-stage, or pre-commercial. Inclusion in this policy does not mean that a capability is commercially available, clinically validated, regulatorily authorized, certified, or approved for every intended use or jurisdiction.
110. No Universal Implementation Claim
Not every module, submodule, function, interface, control, standard, or data category described in this policy is necessarily enabled in every product, customer environment, jurisdiction, research project, or stage of development.
111. No Universal Compliance Claim
No public policy can establish regulatory conformity in every jurisdiction merely by statement. Actual obligations depend on country, region, legal role, intended use, clinical use, data type, customer relationship, regulatory classification, product claims, deployment, development stage, and applicable law.
112. Relationship to Other xBxBio Governance Materials
This policy should be read together with applicable xBxBio materials, including the Privacy Policy, IT & Security Policy, Compliance & Regulatory Statement, Quality Statement, product-specific documentation, data-processing agreements, business-associate agreements where applicable, customer contracts, research protocols, and controlled internal requirements.
113. Standards and Frameworks
xBxBio may use concepts from recognized standards and frameworks where appropriate, including HL7, FHIR, DICOM, DICOMweb, SNOMED CT, LOINC, RxNorm, UCUM, NIST frameworks, ISO/IEC metadata and data-quality concepts, FAIR principles, ALCOA+, GAMP 5, quality-management and medical-device standards, laboratory standards, and other appropriate guidance. Reference does not represent certification or complete implementation.
114. Global Requirements Register
Behind this public policy, xBxBio should maintain controlled jurisdictional and operational records that identify applicable requirements for countries and subnational jurisdictions in which relevant activities occur. Such internal records may contain legal analyses, hosting restrictions, transfer mechanisms, retention rules, responsible owners, deployment restrictions, and approval status and are not required to be publicly disclosed.
115. Continuous Improvement
xBxBio may update its data architecture and governance framework in response to scientific developments, clinical requirements, patient needs, customer needs, interoperability developments, regulatory change, security developments, privacy requirements, AI developments, quality findings, new devices, new modalities, new markets, incidents, and technology evolution.
116. Policy Review
This policy may be reviewed following major architectural change, new modules, new data categories, significant new integrations, new jurisdictions, material regulatory change, significant data incidents, major AI changes, clinical expansion, commercialization milestones, or periodic governance review.
117. Important Data Architecture Disclaimer
This policy describes xBxBio's general public-facing approach to data architecture, data governance, interoperability, longitudinal and multimodal information, provenance, quality, patient-centered architecture, clinician-guided workflows, clinical and laboratory data, geographic and facility context, artificial intelligence data governance, Virtual Heart data governance, and lifecycle management.
It is not a representation that every capability, module, submodule, function, integration, standard, jurisdictional control, or architectural component described here is deployed identically across every xBxBio system, customer environment, research environment, geographic jurisdiction, or third-party service.
It does not constitute legal advice, medical advice, clinical validation, regulatory approval, medical-device authorization, cybersecurity certification, ISO certification, SOC 2 attestation, HIPAA certification, independent assurance, a guarantee of data accuracy, a guarantee of data completeness, a guarantee of interoperability, a guarantee of model or prediction accuracy, or a guarantee of availability.
No public statement contained in this policy supersedes applicable law, regulation, contractual obligation, approved product labeling, regulatory authorization, controlled quality documentation, executed agreement, or confidential xBxBio technical specification. Where an inconsistency exists, the applicable controlling authority or controlled document governs within its proper scope.
118. Global Protection Statement
No country, territory, customer configuration, deployment model, facility, technical environment, interface, or contractual arrangement is intended to eliminate xBxBio's fundamental requirements for patient protection, authorized access, information integrity, provenance, quality, responsible data use, security, and appropriate governance.
A country or territory does not need to be individually named in this public policy for the global baseline to apply where xBxBio lawfully conducts relevant activities.
END OF xBxBio DATA ARCHITECTURE & DATA FRAMEWORK POLICY