Data Strategy Fiscal Years 2026-2030

Guide the Defense Health Agency's use of data as a trusted, mission-enabling strategic asset supporting combat support, healthcare delivery, and enterprise efficiency.
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Submitter's Note: This StratML rendition was compiled from the source by ChatGPT and lightly edited in the form at https://stratml.us/forms/Claude/Part1.html

🏢Defense Health Agency

DHA

Administer the data strategy for the Military Health System in alignment with Department of Defense and Military Health System digital transformation priorities.

Stakeholders:
🏢Military Health System: Benefit from improved readiness, healthcare delivery, interoperability, analytics, and enterprise performance enabled by trustworthy data.
🏢Department of Defense: Provide department-wide data strategy, policy, and governance context for DHA implementation.
👥Defense Health Networks Directors: Help implement governance, stewardship, and data product practices across operational domains.
👥Military Medical and Dental Treatment Facilities: Use, manage, and improve mission-ready data supporting care delivery and operational performance.

Source & Submitter

Source:https://dha.mil/Reference-Library/d/e/f/Defense-Health-Ag...

Period: to

Published:

👤

Given name:Owen

Surname:Ambur

Email:Owen.Ambur@verizon.net

Vision

Enable a Military Health System in which trusted data strengthens combat support, enhances healthcare delivery, and improves operational efficiency.

Mission

To transform DHA data into a trusted, mission-enabling strategic asset through aligned governance, modern practices, and a digitally competent workforce.

Values

Mission Readiness: Prioritize data initiatives that directly support combat support, healthcare delivery, and operational efficiency.
Federated Governance: Apply centralized standards and policies while empowering domain teams to execute data responsibilities.
Data Stewardship: Hold every team member accountable for the value, quality, protection, and responsible use of enterprise data.
Data Products: Treat data products as managed enterprise assets with clear ownership, governance, versioning, and value measurement.
Trusted Sources: Anchor trust in authoritative data sources, verifiable lineage, auditability, and transparency.
Metadata: Govern, validate, and publish metadata so data remains discoverable, understandable, and contextually relevant.
Security and Privacy: Embed security controls, access management, data marking, classification, and privacy protection into all data products from the start.

Goal 1: Roles🔗

Strengthen data roles and responsibilities across the enterprise so personnel understand and fulfill their responsibilities for trustworthy, mission-ready data.
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Line of Effort 1: Strengthen Data Roles and Responsibilities.

Objective 1.1: Governance🔗

Define, document, publish, and operationalize a federated governance model with clear roles, responsibilities, escalation paths, and operating procedures.
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Action 1: Operationalize a Federated Governance Model.

Objective 1.2: Assignments🔗

Identify, designate, and track Data Domain Owners and Data Domain Stewards for critical data domains.
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Action 2: Identify and Assign Key Roles.

Objective 1.3: Awareness🔗

Deploy a targeted stewardship campaign to reinforce enterprise-wide accountability for data stewardship.
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Action 3: Launch a Targeted Stewardship Campaign.

Objective 1.4: Training🔗

Expand role-based governance and data literacy training covering ethics, quality standards, and security requirements.
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Action 4: Expand Data Governance Role-Based Training.

Goal 2: Sources🔗

Maximize the use of authoritative data sources so data products originate from verified sources of truth whenever feasible.
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Line of Effort 2: Maximize Use of ADS.

Objective 2.1: Criteria🔗

Establish authoritative data source vetting and designation criteria based on ownership, quality, metadata, and mission relevance.
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Action 1: Establish ADS Vetting and Designation Criteria.

Objective 2.2: Registry🔗

Implement an enterprise registry of authoritative data sources integrated with the DHA Enterprise Data Catalog.
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Action 2: Implement an Enterprise ADS Registry.

Objective 2.3: Priorities🔗

Prioritize designation of authoritative data sources that directly support combat support and healthcare delivery missions.
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Action 3: Prioritize High-Impact ADS.

Objective 2.4: Consolidation🔗

Execute a phased data consolidation strategy that reduces redundancy and retires systems as authoritative sources are designated.
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Action 4: Execute a Data Consolidation Strategy.

Goal 3: Products🔗

Operationalize data as a product so reusable, mission-focused data products support readiness, care delivery, and enterprise operations.
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Line of Effort 3: Operationalize DaaP.

Objective 3.1: Lifecycle🔗

Define and implement the end-to-end data product lifecycle from discovery through retirement with governance and technical requirements for each phase.
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Action 1: Standardize the DaaP Lifecycle.

Objective 3.2: Specifications🔗

Establish a data product framework specifying lineage, security, metadata, quality, interoperability, and service level expectations.
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Action 2: Establish a Data Product Specification.

Objective 3.3: Portfolio🔗

Identify, scope, and prioritize an initial portfolio of foundational data products essential to strategic mission performance.
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Action 3: Prioritize the Initial Product Portfolio.

Objective 3.4: Value🔗

Establish governance mechanisms to measure adoption, health, and value of data products.
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Action 4: Govern Product Value and Health.

Objective 3.5: Requests🔗

Implement a single streamlined data request process aligned with governance policies and efficient delivery practices.
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Action 5: Enhance Data Request Processes.

Goal 4: Trust🔗

Build trust through measurable, transparent, and increasingly automated data quality management and lineage tracking.
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Line of Effort 4: Build Trust Through Data Quality and Transparency.

Objective 4.1: Scorecards🔗

Deploy an enterprise data quality scorecard measuring accuracy, completeness, timeliness, and consistency.
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Action 1: Deploy an Enterprise Data Quality Scorecard.

Objective 4.2: Lineage🔗

Automate end-to-end lineage tracking linking data products to authoritative data sources and core metadata.
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Action 2: Automate End-to-End Data Lineage.

Objective 4.3: Transparency🔗

Publish quality scorecards and lineage information in the enterprise data catalog so consumers can discover trust signals.
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Action 3: Publish Quality and Lineage Transparency.

Objective 4.4: Remediation🔗

Institutionalize a formal remediation process with clear ownership for investigating and correcting critical data quality defects.
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Action 4: Institutionalize Data Quality Remediation.

Goal 5: Catalog🔗

Maintain the enterprise data catalog as the authoritative metadata repository for data assets, governance artifacts, and data products.
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Line of Effort 5: Maintain an EDC.

Objective 5.1: Currency🔗

Keep the enterprise data catalog updated by integrating it with key data systems so metadata refreshes continuously.
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Action 1: Keep the EDC Updated.

Objective 5.2: Metadata Governance🔗

Apply metadata-first governance by requiring data dictionaries, business rules, transformation logic, and usage guidance for all data products.
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Action 2: Apply Metadata-First Governance.

Objective 5.3: Indicators🔗

Improve transparency by displaying metadata quality indicators that help users assess asset reliability.
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Action 3: Improve Transparency Through Metadata Quality.

Objective 5.4: Context🔗

Support mission use by connecting metadata to operational and analytical systems so lineage, definitions, and context are accessible where data is used.
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Action 4: Support Mission Use Through Contextual Metadata.

Objective 5.5: Learning🔗

Support workforce learning by using the enterprise data catalog and approved resources as reference tools with accessible definitions, lineage views, and examples.
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Action 5: Support Workforce Learning.