HHS Objectives, Values, and Return on Investment (ROI) with
Data
Ensuring Responsible Use and Interpretation of Open Data
Open Methods to Improve the Living HHS Open Data Plan
Everyday Leadership: Driving Open Data Transformation
Everyone Included: Valuing All Perspectives
Unified HHS for Data Sharing
Data Collection Processes for Open
Formats
Completed Projects
HHS 2025 Initiatives and Next Steps
Action Plan and Timeline (2025–2028)
Data Usage Information
Prioritizing Public Data Asset
Review
Improving Processes for Meeting Open Data
Goals
Intra-HHS Data Sharing: Be the
Change
Real-World Data for Impact
Completed RWD Projects Advancing HHS Open Data
Ongoing RWD Initiatives Advancing HHS Open Data
Public/Private Partnership with Transparency to Accelerate
Impact
Public Engagement with, by, and for We the
People
Appendix A: Acronyms, Definitions, Keywords, and
Concepts
Acronyms
Definitions, Keywords, and Concepts
Appendix B: Novel Models of Data Governance: Inspired by Tribal Data
Governance for Radical, Collective,
Self-Governance
Appendix C: HHS Partnerships with
Transparency
Appendix D: HHS Data Improvement Process – 2025
Status
Version 1.0
Updated July 22, 2025
U.S. Department of Health and Human Services (HHS), Office of the Chief Data Officer (OCDO).
This multi-year Living Plan details how HHS intends to use data in service to its mission to enhance the health and well-being of all Americans. As part of this document, HHS explains the reasons why the Living HHS Open Data Plan exists and the rules it must follow for implementation success, while sharing credit with the HHS team that worked hard to create it.
Recommended citation: HHS OCDO. 2025. Living HHS Open Data Plan, version 1.0. https://github.com/HHS/living-hhs-open-data-plan.
The Living HHS Open Data Plan responds to Office of Management and Budget (OMB) guidance on implementation of the Open, Public, Electronic, and Necessary (OPEN) Government Data Act, also known as Title II of the Foundations for Evidence-Based Policymaking Act (Evidence Act) of 20181. OMB Memorandum M-25-05, “Phase 2 Implementation of the Foundations for Evidence-Based Policymaking Act of 2018: Open Data Access and Management,” outlines a systematic approach to open data that will better facilitate data access, subject to appropriate safeguards for privacy, confidentiality, and security. This document addresses requirements in the OPEN Government Data Act related to agency data being open by default, maintenance of agency comprehensive data inventories, dissemination of agency data via the Federal Data Catalog, maintenance of agency open data plans, and agency engagement with the public2.
This work also advances HHS implementation of the Source code Harmonization And Reuse in Information Technology Act (SHARE IT Act)3 of 2024, mandating Open Source and reuse of existing code. As a 2025 pilot between HHS and the Centers for Medicare & Medicaid Services (CMS), the HHS OCDO4 and Open Source Program Office5 of the Digital Service at CMS6 jointly developed the open-source version of the Living HHS Open Data Plan7 for efficiency through technology, transparency for the public, and data-driven delivery as a unified HHS.
HHS encourages public engagement and input on the Living HHS Open Data Plan via GitHub: https://github.com/HHS/living-hhs-open-data-plan with user experience (UX) page https://hhs.github.io/lodp-UX
Alternately, for inquiries and feedback, please contact: cdo@hhs.gov
ACKNOWLEDGEMENTS
Over 50 individuals contributed as co-authors, editors, and contributors
to this Living Open Data Plan, which the HHS Data Governance Board (DGB)
approved and received concurrence from all HHS Divisions in July 2025.
Special thanks to core co-authors and contributors:
Allen, Jelena (CBHSQ/SAMHSA/HHS), Beach, Thomas (ODAR/FDA/HHS), Blase, Alec (ASTP/OS/HHS), Broussard, Cheryl (OD/CDC/HHS), Canos, Daniel (CDRH/FDA/HHS), Caponiti, Anthony (ASTP/OS/HHS), Carrazana, Dorn (CDRH/FDA/HHS), DeCausemaker, Remy (DSAC/CMS/HHS), Dillion, Christopher (NCATS/NIH/HHS), El Zarrad, M. Khair (CDER/FDA/HHS), Ezzeldin, Hussein (CBER/FDA/HHS), Forshee, Richard (CBER/FDA/HHS), German, Claire (ASTP/OS/HHS), Gleason, Amy (OD/CMS/HHS), Gregurick, Susan (OD/NIH/HHS), Honey, Kristen (ASTP/OS/HHS), Hoppe, Travis (OD/CDC/HHS), Isaacman-Beck, Jesse (ASTP/OS/HHS), Jani, Pooja (CDRH/FDA/HHS), Juluru, Krishna (CDRH/FDA/HHS), Keane, Thomas (ASTP/OS/HHS), Kleinstreuer, Nicole (OD/NIH/HHS), Kopelevich, Dinne (DSAC/CMS/HHS), Layden, Jennifer (OD/CDC/HHS), Lu, Yun (CBER/FDA/HHS), Luzuriaga, Natalia (DSAC/CMS/HHS), Mandel, Grace (OD/CDC/HHS), Milarsky, Isaac (DSAC/CMS/HHS), Minor, Clark (IOS/HHS), Morris, Christopher (OPRE/ACF/HHS), Mundkur, Mallika (OC/FDA/HHS), Ogilvie, Jessica (OD/CDC/HHS), Panayil, Sachin (DSAC/CMS/HHS), Paraoan, Dianne (CDER/FDA/HHS), Pishko, Gregory (ODAR/FDA/HHS), Posnack, Steve (ASTP/OS/HHS), Ramanathan Holiday, Tara (OD/CDC/HHS), Ritchey, Matthew (OD/CDC/HHS), Rivera, Donna (OCE/FDA/HHS), Snyder, John (HRSA/HHS), Supplee, Lauren (OPRE/ACF/HHS), Thomson, Alastair (TIO/ARPA-H/HHS), Thornbrugh, Mitchell (IHS/HHS), Trotter, Fred (OD/CMS/HHS), Van Patton, Matthew (OD/CDC/HHS), Vigneshwaran, Shanthi (ODAR/FDA/HHS), Walsh, Jeremy (OC/FDA/HHS), Ware, Deanna (HRSA/HHS)
Submitted to OMB by Kristen Honey, HHS Chief Data Officer, with HHS
concurrence including reviews by:
Peter Bowman-Davis, Chief AI Officer and ASTP Counselor (IOS/HHS)
Kenneth Callahan, HHS Senior Advisor for Policy and Implementation
(IOS/HHS)
This document is in the public domain and available, per the Federal Open Data Policy, without restriction on copying, publishing, distributing, or adapting the information for any purpose.
Note: This Living HHS Open Data Plan is not intended to be comprehensive of all data-related work being done at HHS. This information is additive to currently active work and intend to further boost HHS’s progress in leveraging data in support of its mission. Given the multi-year time frame of this Living Plan, efforts are subject to review and possible change to maintain alignment with the President’s Management Agenda, HHS Secretary Priorities, and the interagency Federal CDO Council8.
Fifteen years ago, HHS led the federal Open Data movement and launched HealthData.gov, the home of HHS Open Data. Now in 2025, HHS has renewed focus on Open Data and released the Living HHS Open Data Plan on GitHub9 with HealthData.gov refresh, including three Evidence Act milestones:
American taxpayers fund HHS data and information, making it essential that certain resources are democratized—easily discoverable, machine-readable, and freely accessible to all. All Americans have a right to their personal health data and certain information that underpins the Department’s operations, federally funded research, and broader “open” initiatives—including partnerships, citizen science, crowdsourcing, prizes, and innovation challenges fueled by HHS Open Data. With the maturation of multiple open communities, HHS is poised to link synergistic ecosystems for impact.
HHS embraces continuous improvements to increase its ability to transform raw data into actionable insights that guide decisions across all levels of the Department. To support this, the HHS Chief Data Officer (CDO), HHS Chief Technology Officer (CTO), Chief Information Officer (CIO), Chief Artificial Intelligence Officer (CAIO), and data leaders within HHS defined shared values for HHS Open Data. Common values aid in navigating change and challenges. The HHS workforce, interagency partners, and external collaborators may differ on data priorities or interpretations, yet we can all unite around values that drive progress and collaboration with a “sharing by default” culture and “open by default” data ethos, to the extent permitted by law for ethical modernization.
Core values underpin the HHS Open Data community, underlying every aspect of this plan.\
Thank you to everyone who has contributed to the HHS Open Data ecosystem—a community of solvers, collaboratively co-creating a more transparent, accountable, and responsive HHS. We have incredible opportunity to responsibly share data, eliminate silos, modernize government, and drive progress through partnerships and emerging technologies like Artificial Intelligence (AI). All are welcome—join us! People first, data always!
— Kristen Honey, PhD, PMP, HHS Chief Data Officer, HHS Office of the Chief Data Officer10
SHARED PURPOSE: Responsibly unleash the power of HHS data, deliver improved services through data, and maximize the nation’s return on its investment in data to benefit all Americans.
CORE VALUES:
HHS is trusted with personal data by all Americans, patients, and clinicians alike. HHS must honor that trust, by protecting data privacy, while delivering value and rewarding individuals for investing their data and digital stories with us. The HHS Open Data approach aims to ensure that the healthcare, public health, and research systems are fully informed with HHS data, ensuring that patients and the public benefit from downstream data marketplace and ecosystems - while balancing the need to minimize unnecessary risks to the individual, including privacy harms and confidentiality, - and embracing our responsibilities. We must ensure that data is not just available, but that it is managed, analyzed, and interpreted with care. Bad analysis can be worse than no analysis, but neither should analysis and interpretation be the sole provenance of HHS. We just need to do a good job going first.
Change will move at the speed of trust. Trust may be defined as “consistency over time,” and this Living Plan acknowledges that HHS can do more to build trust in the ecosystem. Rebuilding and strengthening the public’s trust in HHS data is paramount for HHS Open Data success, and change is here. In 2025, HHS recommits to reliably sharing high-quality data, consistently engaging with radical transparency, adopting “Open” methods (e.g., Open Science, Open Innovation, Open Source Code), and communicating with opportunities for two-way public engagements, events, and public-private partnerships.
Such transparency has tradeoffs, and necessitates the balancing of considerations of privacy, national security, and other risks to opening government information.
The success of the Living HHS Open Data Plan depends not only on making data accessible but also on ensuring it is responsibly managed, analyzed, and interpreted. To address the risks of misinterpretation and misuse, HHS is committed to incorporating insights from epidemiologists, statisticians, systems biologists, and interdisciplinary modelers with expertise in understanding the purpose, significance, and appropriate application of complex data. For years, the National Institutes of Health (NIH), Centers for Disease Control and Prevention (CDC), and HHS Divisions have rigorously developed and shared best practices in disclosure risk management1112).
Building on best practices, such as those demonstrated by HealthData.gov13 and CDC Wide-ranging ONline Data for Epidemiologic Research (WONDER)14, HHS will explore how to optimally share Open Data with guardrails to guide users in the responsible analysis and interpretation of government data. These measures will help mitigate unintended consequences and ensure that HHS data drives meaningful, evidence-based insights that serve the public good. HHS recognizes the importance of transparency and reproducibility in science, particularly for data associated with peer-reviewed publications, so that Open Data151617 efforts will also strengthen Open Science18.
As part of future iterations of the Living HHS Open Data Plan, HHS will continue to prioritize efforts to align Open Data practices with the principles of scientific rigor, ensuring that datasets accompanying publications are well-documented, reproducible, and accessible. Acknowledging that poor data analysis can be more harmful than no analysis at all, HHS is committed to fostering a culture of responsible data use, where HHS Open Data not only informs but also empowers users to derive accurate, actionable insights with transparency and reproducibility.
All HHS Divisions will continue to responsibly share data when legally permissible and when the expected benefits to society outweigh the expected risks, using risk-informed assessments to guide decisions considering dynamic technology changes, privacy safeguarding, national threats, and situational context. HHS will comply with all requirements of OMB M-25-05 and the requirements of 44 U.S.C. § 3511 when disseminating a public data asset pursuant to the Evidence Act.
This Living Plan satisfies Office of Management and Budget (OMB) requirements for the Evidence-Based Policymaking Act (Evidence Act) of 2018 Title II—also known as the Open, Public, Electronic, and Necessary (OPEN) Data Government Act19—but its purpose transcends mere box-checking. When Open Data is reduced to a compliance task, organizations lose the transformative spirit of transparency and collaboration. Impactful Open Data requires a cultural shift at every level of an organization, embracing a mindset of “share by default” and “open by default” to democratize access to information as a public good. By distributing power to the people, the future of HHS Open Data aims to empower Americans with timely, machine-readable, high-quality, freely available data from all HHS Divisions, while lifting new data governance models to give U.S. citizens, including patients, more agency and control over their own data.
This Living HHS Open Data Plan is designed to evolve with public input and feedback. It is modular, so each chapter is its own independent GitHub file for the public to submit issues and ideas, in response to a general HHS request for public input and comments. The HHS GitHub “Tell Us About Your Experience with the HHS Open Data Plan”20 is an online form with open-ended space for public response. With this agile approach, HHS aims to avoid the pitfalls of bureaucratic compliance while maintaining focus on the ultimate goal: fostering collaboration and unlocking the transformative power of data for operational efficiency, scientific discovery, innovation, and public impact.
The value of HHS Open Data is far reaching:
Achieving the goals of the Living Plan requires sustained effort and action across all levels of the HHS workforce. Leadership, managers, data stewards, and staff must integrate data into everyday decision-making. We must all foster a culture where data-guided insights drive understanding and impact. HHS Open Data transformation begins with everyday leadership, where every Federal employee can commit to lead by example and work in the open with transparency to expand trust in the agency, in science, and in the data stewarded by HHS. We should strive to all say “yes” by default and responsibly share, when legally permissible and when the expected benefits outweigh expected risks, so that historical gatekeeping norms and gatekeeping culture across HHS will be transformed into a data-driven, enabling culture without silos—while safeguarding privacy, security, and risks.
The success of the Living Plan depends on a collective effort across the entire HHS workforce—data stewards, scientists, strategists, communicators, administrators, problem solvers, and innovators—with everyone recommitting to transparency, HHS data, and following the data wherever the data and science lead. Moreover, HHS must be responsive to the American public’s needs, requests, and suggestions for improving the Living Plan, HealthData.gov resources, and Departmental initiatives.
Across all HHS bureaucracy levels in day-to-day work, employees are encouraged to enable a “yes” by default data-sharing culture with transparency to eliminate information silos. All HHS staff can aid this transformation by asking themselves the following three questions:
1. How can I responsibly publish more “open by default” data on
HealthData.gov?
It is imperative that federal data is shared with the public when
expected societal benefits/rewards outweigh expected costs/risks, and
legal requirements allow. This involves risk-informed tradeoffs and
balancing transparency, accessibility, confidentiality, privacy, and
security while ensuring quality, ethical use, and protection of priority
data assets.
2. How can I more transparently engage, listen, and respond to
citizens and public feedback?
The OPEN Government Data Act (Title II, Evidence Act) requires each
agency to embrace data sharing with an “open by default” approach for
the public. This necessitates public engagement, while maintaining a
strategic Information Resources Management Plan that, to the extent
practicable, includes an Open Data Plan. As HHS is a science agency,
implementation involves both HHS Open Data21 and Open Science22
(free public access without paywalls), and successful delivery involves
two-way public engagements with responsiveness to citizens.
3. How do I ensure, measure, and track real-world impact from my HHS
data work?
Responsible data sharing with a “yes” enabling culture is a good step
and necessary—yet insufficient—to transform raw data into
understanding and insights to guide decisions and actions. All
data-driven use cases and data projects or pilots funded by HHS should
explicitly define measurable metrics of success with an emphasis on
real-world outcomes (e.g., longevity, services efficiency, patient
outcomes) that matter to the American people. As civil servants working
on HHS data projects, we must hold ourselves accountable to these
measurable metrics of success that will vary by project, so that HHS
data directly improves service delivery with positive outcomes.
Lastly, HHS Open Data is not just about numbers; it is about the people with the human dimensions. With a holistic view of data science, HHS must prioritize the lifting of people and sharing data-driven stories. To emphasize the human impacts, the 2025 HealthData.gov refresh renamed its blog page to a stories page. HealthData.gov stories are data with a soul23 to connect our HHS data with collective purpose.
HHS GitHub — Open Data in Action
https://hhs.github.io/lodp-UX
Identify gaps or omissions in the Living HHS Open Data Plan, including emerging technologies, Open Data trends, issues, or priorities that should be addressed in future updates.
By addressing the above questions and embracing a culture of transparency, collaboration, and accountability, HHS commits to unlocking the full potential of its data to enhance the health and well-being of all Americans. Join us!
HHS must come together as one department for successful data lifecycle management that responsibly unlocks HHS Open Data for the public. The nation’s health and human services needs are complex—and public health problems are rarely solved by a single federal initiative. Although data is a critical strategic asset for advancing public health, data sharing and interoperability are critical to making people healthier.
As such, HHS embraces the opportunity to transform itself into an agile Department, responsive to the nation’s needs, by leveraging the power of the information available across its multi-agency data assets. Contributors to this Living Plan included staff from all HHS divisions, which are listed in the acronyms of Appendix A. This Living Plan will be updated in alignment with new HHS office structures, as new information becomes known about reorganizations.
HHS is committed to transforming its data collection processes to meet the highest standards of accessibility, usability, and interoperability. By adopting open formats, HHS ensures its data is machine-readable, and published using open data formats (JSON, CSV, HTML, etc.)24, fostering transparency, operational efficiency, and innovation in alignment with the OPEN Government Data Act. To maximize the value of its data, HHS has embraced the FAIR-D principles—Findable25, Accessible26, Interoperable27, Reusable28, and Delightful2930, (FAIR-D)—establishing secure, trustworthy, and open-by-default practices. Standardizing procedures and prioritizing Open Data not only increase public access but also drive innovation, economic growth, and accountability. For example, Section 508 of the Rehabilitation Act31 mandates that the federal government ensure electronic and information technology is accessible to individuals with disabilities. These accessibility features enable people with vision impairments, who may use screen readers, to interact with digital documents and websites in ways comparable to sighted individuals. At HHS, these features are implemented to serve two key groups: (1) federal employees and (2) members of the public. By adhering to Section 508 standards and embracing technology for greatest reach, HHS ensures that its Open Data is broadly available and usable to all.
HHS GitHub — Open Data in Action
https://hhs.github.io/lodp-UX
Recommend best practices for data collection, management, or usage in open formats to help HHS achieve its Open Data goals, including intra-HHS data sharing and Real-World Data (RWD) exchanges.
Open Data collection practices are on-going with continuous improvements (marked with asterisk*) to select HHS completed projects:
Building upon past achievements, the HHS CDO and data leaders across the Department expect to implement a series of Open Data initiatives in 2025 and beyond:
HHS GitHub — Open Data in Action
https://hhs.github.io/lodp-UX
Propose ideas or examples for piloting innovative data governance models with patients, industry, academia, and other sectors to improve health data governance and transparency.
Future HHS DGB iterations will benefit from increased transparency (e.g., public meetings), modernized technology (e.g., all HHS Divisions connected to file share), and expanded engagement with external experts (e.g., Special Government Employees [SGEs]). This will necessitate coordination with the Federal CDC Council and across HHS, including working with HHS legal and ethics officials, Counsel, HHS data stewards, and HHS offices with equities in the Evidence Act, SHARE IT Act, Information Quality Act, Sunshine Laws, the Federal Advisory Committee Act (FACA), Paperwork Reduction Act (PRA), and other laws that influence DGB options for engaging the public and SGEs. It will also necessitate novel approaches, as described in Appendix B - Novel Models of Data Governance: Inspired by Tribal Data Governance for Radical, Collective, Self-Governance.
In addition, today’s HHS DGB must pivot focus from government process to delivery outcomes with measurable metrics of success, while accelerating its cadence to move at today’s pace of digital change. Given limited time and resources, the HHS DGB expects to scout, lift, and co-design novel pilots of data governance with other sectors—not reinvent wheels that likely exist in other sectors—to give U.S. citizens greater agency with opt in/out controls over their own health data. Ambitious DGB changes may occur in tandem with HHS AI governance, since data and AI are inextricably linked on the frontlines of data use.
HHS has outlined a phased approach to achieve its open data objectives in the below Table 1 - HHS Open Data Action Plan.
Table 1 - HHS Open Data Action Plan
HHS Open Data Action Items: - Data Collection Processes in Open Formats to Eliminate Information Silos: Priority in progress (2025), Done with Open Metrics (2026), Done with Open Metrics (2027), Done with Open Metrics (2028)\
As part of the HealthData.gov refresh in July 2025, HHS introduced two new pages to provide greater transparency into how the public interacts with its Open Data resources. These pages offer valuable insights into data usage trends, helping both HHS and the public better understand the reach and impact of HHS Open Data.\
Both HHS tools enable the public and federal agencies to understand how the public finds, accesses, and uses HHS Open Data, online resources, and websites. Data usage information is shared in an anonymous way, as it includes only summary statistics. This reflects HHS’s unwavering commitment to protect individual privacy and ensure compliance with the Privacy Act of 1974 and other applicable federal laws, statutes, and regulations.
Protecting Privacy and Ensuring Compliance: In data usage tracking efforts, HHS maintains an unwavering commitment to protecting individual privacy and ensuring compliance with all applicable federal laws, statutes, and regulations. Data usage information is collected, de-identified for protection of individual privacy, and analyzed in aggregate form, with stringent measures in place to prevent the identification of individual users or the compromise of potentially sensitive information.
Tracking and Analytics to Inform Decision Making: Insights gleaned from HHS data usage information inform HHS policymaking and resource allocation. By understanding which websites and datasets are most frequently accessed and how they are being used, HHS can better align Open Data efforts with public needs and scientific research priorities.
Transparency and Reporting: HHS regularly publishes reports on data usage statistics and trends596061. These reports provide valuable insights to both internal stakeholders and the public, fostering a culture of openness and accountability in our data management practices.
Collaborations and Partnerships for Enhanced Insights: To extract additional understanding and value from HHS data usage information, HHS engages in strategic collaborations through the CDO Council, other federal agencies, and public-private partnerships. Such collaborations enable a more sophisticated analysis of data usage trends, many of which are available on Data.gov62 and GSA’s DAP63.
HHS communicates the usage and value of its data at public-facing engagements and events including technology sprints, innovation sprints, demo days, and other opportunities that showcase data usage information. HHS features select data usage information through the HealthData.gov/stories64, also known as the HealthData.gov blog.
Data usage information must guide the HHS Open Data Plan and future strategy, illuminating the path to maximum efficiency, economic growth, scientific discovery, and public impact. By tracking and analyzing how HHS data is accessed and utilized, we transform raw statistics into actionable insights. The HHS CDO will develop a detailed multi-year schedule (beyond Table 1 - HHS Open Data Action Plan, pages 9–10) for implementation, following the Department’s reorganization.
A component of an HHS Open Data Strategy will be to identify and publish priority public datasets that matter to citizens. This will involve identifying and prioritizing high-impact, high-ROI data resources that align with HHS priorities for greatest benefit to society.
Criteria for prioritizing datasets may include:
HHS proactively publishes its FOIA responses as Open Data in “Electronic Reading Rooms,” like the HRSA Electronic Reading Room, once a low threshold of three or more public inquiries is met through FOIA requests.
Data-driven approaches with focused criteria and standards will ensure HHS data sharing provides value to our partners in the private sector, public institutions, non-profit organizations, and beyond. By prioritizing high-impact datasets, we aim to facilitate groundbreaking research, inform policy decisions, and drive results while being responsive and agile with HHS Open Data to address the government service and healthcare issues of most importance to you.
We encourage all our partners to engage with HHS Open Data and provide feedback on their utility and impact. Together, we can leverage the power of data to address critical health challenges, enhance service delivery, and improve the well-being of all Americans.
Data is central to the HHS mission. Data is foundational to the Department, as all HHS Divisions work together to enhance the health and wellbeing of all Americans through HHS services, disease control and prevention, scientific advancements, and efficient regulation of food, drugs, medical products, and much more. As the HHS organization evolves, its data processes will change.
Per the requirements of the OPEN Government Data Act67, the HHS CDO will update this section in a future version of the Living HHS Open Data Plan, following the Department’s reorganization.
Table 2 - HHS Data Improvement Processes - Current State
Division:\
HHS data-driven delivery relies on its ability to securely, legally, and ethically share information across all its HHS Operating Divisions and Staff Divisions for the collaborative solving of pressing public health needs. To this end, HHS views its data is an enterprise resource, and not a series of collections scattered across government silos.
The HHS CTO and CIO are leading IT enterprise-wide integration and modernization, working closely with the CDO to create one umbrella as a unified Department with shared, enterprise-wide capabilities to:
The “spirit” of the Evidence Act, for which the OPEN Government Data Act is Title II, is to ask and answer questions (build evidence) to support policymaking. HHS intends to collect, use, and acquire data to apply it in ways for the betterment of the nation. This includes rigorous application of the scientific method to test scientific hypotheses, while following the data wherever the data lead. HHS, like all Federal government, should use data to maximize the impact of science, programs, and services for the common good.
Real-World Data provides a foundation for a “Learning Health System” that can rapidly adapt to changing circumstances, emergent diseases, and enable learning from the treatment of patients to inform others with the same condition.
Real-world data (RWD69) and real-world evidence (RWE70) align with HHS Open Data values and goals to drive healthcare innovation, transparency, and improved outcomes. HHS promotes open access to and interoperability of RWD, using data-sharing and access methods compliant with applicable laws, such as the Health Insurance Portability and Accountability Act of 1996 (HIPAA), which applies to certain information when it is created, received, maintained, or transmitted by, or on behalf of, health plans, health care clearinghouses, and certain health care providers.
This real-world approach enables diverse stakeholders, such as regulators and payers, to gain insights from routine clinical care—and provides a foundation for a “Learning Health System” that can rapidly adapt to changing circumstances, emergent diseases, and enable learning from the treatment of patients to inform others with the same condition. By adopting “open by default,” while safeguarding individual privacy, HHS aims to leverage high-quality RWD/RWE, clinical evidence regarding the usage—and potential benefits or risks—of a medical product derived from analysis of RWD/RWE. Such interdisciplinary analyses and results will inform regulatory decisions, evaluate treatments, and accelerate effective care delivery, supporting evidence-based policymaking and patient-centered healthcare.
At the core of the Living HHS Open Data Plan for RWD lies the concept that data is a “public utility” for good that powers scientific advancement, innovation, and progress. Public utilities exist because the community has recognized that the service or product they provide is essential to the life and health of Americans. In today’s world, the public needs access to healthcare and public health data, which allows individuals to take control of their own health and allows aggregate, anonymized, deidentified data to be leveraged for innovation.
HHS supports public and private partnerships for data utility models that increase data access for public consumers, including patients, providers, payers, state agencies, and researchers. The health utility concept is emerging today based on lessons learned from early gains by Health Information Exchanges (HIEs), and by expanding the role of HIEs into a public utility or Health Data Utilities (HDUs). HIEs have provided critical and timely patient data to aid in treatment across health care providers, but new governance models will be necessary to empower patients and ensure HHS transparency, accountability, and responsiveness to citizen prioritizes and real-world needs.
HHS GitHub — Open Data in Action
https://hhs.github.io/lodp-UX
Highlight public-private partnerships, collaborations, or cross-sector initiatives powered by HHS Open Data that deliver measurable impact and deserve inclusion in future versions of the Living Plan.
The on-going HIEs evolution into HDUs is opportunity for the HHS CDO and partners to pilot novel data governance methods and pioneer new approaches to interoperability. This progress with HIEs is informative and important, yet alone it is not sufficient to enable a nationwide learning health system. The CDO expects to pilot novel data governance models with industry, academia, non-profit organizations, and all sectors—including individuals with lived experiences, like patients and caregivers, as partners—to co-create new modes of data governance in collaboration with HHS.
In a learning health system, cancer treatment may improve as clinicians can find other patients with similar tumor characteristics, especially genomically similar tumors, and enable clinicians to learn what treatments are or are not effective, enabling better and more tailored treatment with the right interventions, earlier in the course of the disease. Similar use cases for the health public utility exist for rare disease treatment; with sufficient data, the health public utility can support much more rapid diagnosis and treatment. Beyond the learning health system, such a public utility for health data provides the foundation for improved bio-surveillance, detection and analysis of adverse events from drugs, devices and biologics, as well as for research. In some respects, more importantly, such a public utility supports radical transparency for patients, both in terms of expanding comprehensive access to their medical history and for the ability of the public to understand how their data is being used, by whom and to understand the benefits from that use of their data.
A public utility model for good and radical transparency relies on a Patient Trust Model. This model refers to the relationship between patients and their healthcare organizations regarding their health information. Providing patients influence and power over their information and data and allowing for deeper permissioning of their data through a health data utility creates the necessary components for a learning health system. Key elements of the Patient Trust Model include data security and privacy, transparency and engagement, patient empowerment, and return of results to improve healthcare, which is a goal for a learning health system. In some ways this concept is similar to Brazil’s patient data model that is governed by the Lei Geral de Proteção de Dados (LGPD)71. The LGPD grants patients access control over their data including data sharing and transparency on data use.
The health data utility model can also work to empower patients to take control of their own data, share it selectively with their clinical care team, and if willing, to opt in to specific research studies.
HHS is a federal agency with gift authority72, so the Department may accept gifts and financial resources from external sources. Public-private partnerships have emerged as a powerful mechanism for addressing complex challenges in health, science, and human services for public good—yet such partnerships must be coupled with HHS transparency, accountability, and responsiveness to citizens.
Collaborative ventures between government agencies, private sector entities, and non-profit organizations offer a unique approach to leveraging diverse expertise, resources, and perspectives to drive innovation and improve public health outcomes. In the context of health and human services, both informal collaborations and formal partnerships are valuable for their ability to expand the solution space, pool resources, grow expertise, harness big data, and promote data sharing across sectors for a more holistic approach to public health and human services.
By combining the strengths of public and private entities, partnerships like the LymeX public-private partnerships73 accelerate progress and move the needle on HHS priorities—like MAHA chronic conditions—with greater efficacy than either sector could achieve alone. For example, a partnership between a government health agency and a private healthcare technology company could result in the development of innovative telemedicine solutions that extend healthcare access to underserved rural communities. The public sector brings regulatory knowledge and population health data, while the private sector contributes technological expertise, agile development processes, and community trust because external groups are often more directly connected than HHS to local community needs. Working together creates a synergy with mutual benefits.
HHS and its partners must execute collaborative efforts within a shared framework that safeguards individual privacy, maintains confidentiality and integrity, and ensures data security while also “sharing by default” and “open by default” per the Evidence Act.
Partnerships vary by use case and context matters. No matter the context, however, HHS partnerships adhere to all applicable federal privacy laws (e.g., HIPAA), statutes and regulations—simultaneously balancing radical transparency for public visibility and accountability.
With ethical implementation and ethical modernization, HHS partnerships can strengthen community relationships and foster public trust in government to achieve shared goals, as they optimize the societal benefits through innovative partnerships fueled by HHS Open Data. Well-managed partnerships include protective measures and best practices for open government transparency, co-creation, accountability, and responsiveness to citizens so that all HHS partners harness the power of cross-sector collaboration, while maintaining the highest standards of ethical and legal compliance. All stakeholders—including the public—deserve to have full visibility into an HHS partnership’s objectives, methods, progress, and challenges to foster trust and enable continuous improvement through open feedback and scrutiny.
HHS guidelines on public-private partnerships fueled by HHS Open Data do not yet exist, yet the community identified these key measures to maximize the chances of success for public good:
HHS is redefining partnerships with transparency by moving beyond Memorandums of Understanding (MOUs) and information sharing to actively co-create open platforms with U.S. citizens, patients, and stakeholders as equal partners. This collaborative approach enables the development of data-driven projects, such as real-time tracking of milestones, public forums for strategy discussions, and mechanisms for direct citizen input into decision-making. By embracing this level of openness and implementing safeguards against regulatory capture, public-private partnerships not only enhance their effectiveness but also set new benchmarks for accountability. This ensures that the interests of all stakeholders—especially the public—remain at the forefront of these initiatives.
HHS uses numerous mechanisms to engage with the public for sharing data and information (so that the public can better access and use public data assets), to collaborate on data-related work where there are common interests, and/or to maintain an open dialogue between HHS and the public when critical perspectives and other input is needed. Department-wide “open” engagement outlets commonly used by all HHS divisions include:
Additional opportunities for public engagement include:
Web Interfaces for Data Sharing: HHS publicly shares information and data through the Open Data catalog on HealthData.gov (and other open catalogs), the HHS Data Inventory, Dashboards, Search Tools, and APIs such as the ones listed on the HHS CDO Open Data Inventories and APIs page74—and through resources like its Tribal Data Homepage75 and GitHub site76.
Feedback and Input: HHS shares with the public its agency policies and procedures related to maintenance of information quality—providing opportunities for the public to give HHS feedback and request clarity/corrections. HHS also engages with the public through mechanisms such as the Secretary’s Tribal Advisory Committee77 and other Federal Advisory Committees mandated by the U.S. Congress and managed by HHS.
Formal Collaborations and Partnerships: HHS builds cross-agency data capacity for comparative clinical effectiveness research, works with surveillance and research partners through cooperative agreements such as these at the CDC, and offers technical assistance and other resources to help others use HHS data to make the nation healthier. Such formal partnerships include legally binding relationships between HHS and external entities.
Informal Collaborations with Communities: HHS hosts events like the Health Datapalooza78 that originated out of the Department to showcase the value of Open Data for health and human services. HHS also hosts Open Data roundtables, hackathons, “healthathons79”, DataJams, Demo Days, Innovation Sprints, Tech Sprints like TOP/TOPx80, and other public engagements fueled by HHS Open Data. Other mechanisms involve listening sessions and interviews81 to monitor HHS progress and understand HHS effectiveness, given evolving community needs and wishes. These informal engagements are lightweight, flexible engagements that do not require legally binding relationships between HHS and external entities.
The HHS Open Data community embraces agile methods. Agile methods include human-centered design and qualitative research, which helps to lift the lived experiences and interdisciplinary sciences with consideration of medical ethics and ethical modernization.
Open data excellence is a shared effort that will improve with your input and iterating collaboratively with this Living Plan. HHS welcomes and values input from all the public across all sectors. Cross-sector lessons learned and insights will improve HHS efforts to responsibly unlock data, share information, and deliver mission while following the data wherever the data lead.
HHS encourages public engagement and input on the Living HHS Open Data Plan via GitHub82with a user-friendly HHS GitHub UX page83.
Alternatively, for inquiries and feedback, please contact: cdo@hhs.gov
Administration for a Healthy America (AHA, proposed)
Administration for Children and Families (ACF)
Administration for Community Living (ACL)
Administration for Strategic Preparedness and Response (ASPR)
Advanced Research Projects Agency for Health (ARPA-H)
Agency for Healthcare Research and Quality (AHRQ)
Agency for Toxic Substances and Disease Registry (ATSDR)
American Indians and Alaska Natives (AIAN)
Application Programming Interface (API)
Artificial Intelligence (AI)
Assistant Secretary for Technology Policy (ASTP) and the Office of the
National Coordinator for Health Information Technology (ONC)
(collectively, ASTP/ONC)
Authority to Operate (ATO)
Autism Spectrum Disorder (ASD)
Centers for Disease Control and Prevention (CDC)
Centers for Medicare & Medicaid Services (CMS)
Chief Artificial Intelligence Officer (CAIO)
Chief Data Officer (CDO)
Chief Information Officer (CIO)
Chief Technology Officer (CTO)
Collective Benefit, Authority to Control, Responsibility, and Ethics
(CARE)
Cooperative Research and Development Agreement (CRADA)
Coverage with Evidence Development (CED)
Data Catalog Vocabulary (DCAT) - US, version 3.0 (DCAT-US 3.0)
Data Governance Board (DGB)
Data Use Agreement (DUA)
Digital Analytics Program (DAP)
Electronic Health Records (EHRs)
Executive Order (EO)
Federal Advisory Committee Act (FACA)
Food and Drug Administration (FDA)
Foundations for Evidence-Based Policymaking Act (Evidence Act)
Health Data Utilities (HDUs)
Health Information Exchanges (HIEs)
Health Insurance Portability and Accountability Act (HIPAA)
Health Resources and Services Administration (HRSA)
Immediate Office of the Secretary (IOS)
Indian Health Service (IHS)
Information Technology (IT)
Institutional Analysis and Development (IAD) framework
Lei Geral de Proteção de Dados (LGPD); Brazil General Data
Protection Law (LGPD), Law No. 13.709/ 2018:
https://iapp.org/resources/article/brazilian-data-protection-law-lgpd-english-translation/
Memorandums of Understanding (MOUs)
National Clinical Cohort Collaborative (N3C)
National Institutes of Health (NIH)
Office for Civil Rights (OCR)
Office of Global Affairs (OGA)
Office of Inspector General (OIG)
Office of Intergovernmental and External Affairs (IEA)
Office of Management and Budget (OMB)
Office of the Assistant Secretary for Administration (ASA)
Office of the Assistant Secretary for Financial Resources (ASFR)
Office of the Assistant Secretary for Health (OASH)
Office of the Assistant Secretary for Legislation (ASL)
Office of the Assistant Secretary for Planning and Evaluation
(ASPE)
Office of the Assistant Secretary for Public Affairs (ASPA)
Office of the Chief Data Officer (OCDO)
Office of the General Counsel (OGC)
Office of the National Coordinator for Health Information Technology
(ONC)
Open, Public, Electronic, and Necessary (OPEN) Government Data Act,
also known as Title II of the Foundations for Evidence-Based
Policymaking Act (Evidence Act)
Paperwork Reduction Act (PRA)
Real-World Data (RWD)
Real-World Evidence (RWD)
Return on Investment (ROI)
Source code Harmonization And Reuse in Information Technology Act
(SHARE IT Act)
Special Government Employees (SGEs)
Subject Matter Experts (SMEs)
Substance Abuse and Mental Health Services Administration (SAMHSA)
U.S. Department of Health and Human Services (HHS)
U.S. General Services Administration (GSA)
Accuracy refers to how well data reflects reality, ensuring it’s corrected and free from errors.
Agile Methods are a set of project management and software development approaches that emphasize flexibility, collaboration and iterative development.
Availability means data is accessible when needed.
CDC’s Core Data Use Agreement (DUA) initiative focuses on enhancing data use and sharing agreements with public health jurisdictions across states, tribes, localities, and territories. On December 1, 2023, CDC adopted a new approach, introducing a “Core DUA” that unifies and enhances national data exchange. Following recommendations from the Advisory Committee to the Director (ACD) Data and Surveillance Workgroup, CDC is implementing a single agreement formalizing agency-to-agency data-sharing relationships. (https://www.cdc.gov/data-interoperability/php/use-agreement/index.html)
Completeness signifies all required information is present.
Consistency means data is uniform across different sources and systems.
Enterprise Platform refers to a standardized technology framework used by the whole Department to manage and integrate various systems and data across its HHS Divisions.
FDA Terms of Use offers some of its public data in machine-readable format through openFDA, a service located at https://open.fda.gov. Use of the data made available via openFDA is generally unrestricted (see “Data Rights and Usage”). However, the service through which FDA makes that data available is offered subject to your acceptance of the terms and conditions contained herein as well as any relevant sections of the FDA Website Policies.
HHS Data Inventory is an individual data asset (metadata catalog) generated by the HHS Data Hub, which is part OCDO’s existing authority to operate (ATO) for HHS Connect. The HHS Data Inventory will promote the reuse of existing data and eliminate the duplicate effort to produce and store the same data multiple times. The HHS Data Inventory will break down existing information silos, encourage information sharing, eliminate duplication and inefficiency, and increase the American taxpayers’ ROI on existing information technology (IT) and data investments.
HHS Open Data Plan is a document published under the authority of Title II of the Foundations for Evidence-Based Policymaking Act of 2018 (OPEN Government Data Act). This living plan is not intended to be comprehensive of all data-related work being done at HHS. This information is additive to currently active work and intended to further boost HHS’ progress in leveraging data in support of its mission.
HHS Connect Terms and Conditions (formerly HHS DUA builder) looks to simplify the way data is shared. The Terms and Conditions in HHS Connect will ask a series of questions to understand the data being shared, and by whom and by what terms and conditions. It will generate the document based on the answers provided and trigger the electronic signatures for the agreement. The terms and agreements are stored in the repository based on the type of agreement generated. The agreements are searchable in the repository.
Human-centered design (HCD) is a design philosophy and process that prioritizes the needs, desires, and limitations of the end-users throughout the entire design process.
Living Document is a document that is designed to be continually updated and revised, reflecting new information, changing circumstances, or evolving needs. It’s not meant to be static or fixed, but rather to adapt and remain relevant over time.
Open Data refers to information or content that is freely available for anyone to use, re-use, and redistribute, without restrictions. It’s data that is accessible, machine-readable, and provided in open formats, often under an open license.
Open Government is transparent, participatory, and collaborative. Transparency means sharing data and information. Participation means hearing and implementing ideas from many kinds of people and organizations. Collaboration means engaging in ongoing conversation with employees and the public and working together to solve problems. Doing these things not only increases our own accountability but also build trust with the American people.
Open Innovation a collaborative approach where government agencies actively seek ideas, expertise, and resources from outside their traditional boundaries, including citizens, businesses, and academia, to address public challenges and improve government services.
Open Science refers to the principle and practice of making research outputs and processes available to all, while prioritizing security, privacy, and fostering collaboration.
Open Source Code refers to software code that is publicly available for anyone to use, modify, and distribute, often under specific licensing terms. Open-source code fosters collaboration, transparency, and innovation across agencies and with the public.
Real-world data (RWD) are data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources. Examples of RWD include data derived from electronic health records, medical claims data, data from product or disease registries, and data gathered from other sources (such as digital health technologies) that can inform on health status.
Real-world evidence (RWE) is the clinical evidence about the usage and potential benefits or risks of a medical product derived from analysis of RWD.
Timeliness indicates data is up-to-date and relevant for its intended purpose.
Usefulness describes data’s applicability and relevance to problem-solving and decision-making.
Version (version control) is a system that tracks and manages changes to a document like the Living HHS Open Data Plan over time.
HHS expects to explore novel models of data governance, including radical, collective, self-governance models with sovereign nations, patient communities, and external sources.
The thoughtful collection, sharing, and use of Open Data to advance HHS mission requires transparency in data governance that engenders trust by design, ensuring that the right people have access to the right data at the right time. Governance of data requires a close interplay between data sharing and access policies, the technologies that enable the management and sharing of data through secure infrastructures, and—most importantly—the people with equities.
Included in these considerations for HHS are the responsible management and sharing of American Indians and Alaska Natives (AIAN) data, contributed from Federal, Tribal, and Urban Programs. As a model, Indigenous data are governed by and intrinsic to Indigenous Peoples’ capacity and capability to realize their human rights and reflect the crucial role of data in advancing Indigenous innovation and self-determination. The governance of these data has been articulated through the Collective Benefit, Authority to Control, Responsibility, and Ethics (CARE) principles84, which emphasize the need for tribal data sovereignty over access and future use, among other principles. NIH has acknowledged tribal sovereignty in policies governing sharing of scientific data85 and implemented a tribally governed data infrastructure86 that allows for federated tribal data sovereignty, giving each participating tribal community full control over the access and management of their data.
Through its Tribal Data use case87, the HHS CDO and DGB are exploring how tribal data can be owned and controlled by tribes, while enabling responsible data sharing and use. For example, the Institutional Analysis and Development (IAD)88 framework emphasizes self-governance, community trust, and nested scales of decision-making. Used in natural resource management, IAD offers implementation best practices for empowering local communities through shared governance structures and the “co-creation” of policies with government. To ethically engage local, regional, and national stakeholders, the CARE principles coupled with IAD design principles may offer novel solutions rooted in Indigenous Data Sovereignty. The future of HHS Open Data must balance collective action, respect for individual sovereignty, and the equitable sharing of resources—treating data as a strategic asset and resource—while empowering communities to manage their data with agency, aligned to their unique needs and values.
In the spirit of radical transparency and co-creating the future with the public, HHS welcomes general feedback from the public on this preliminary vision to guide future public-private partnerships.
HHS encourages public engagement and input on the Living HHS Open Data Plan on GitHub89 with a user-friendly HHS GitHub UX page90.
For inquiries or feedback you prefer not to make public on GitHub, please contact: cdo@hhs.gov
2025: Establish clear policy and procedure on approaches to build strategic partnerships to revolutionize healthcare by harnessing cutting-edge technologies and fostering collaboration between government, industry, and academia. Host HHS public-private partnerships engagement to co-design new approaches, including partnership models like Cooperative Research and Development Agreements (CRADAs). Novel CRADA-like partnership opportunities with HHS may drive additional value and innovation.
2026: ARPA-H together with FDA/CDRH are exploring market-based approaches to making medical imaging data more available to research, product development, and regulatory testing purposes via an Apple App Store model using a trusted third-party broker. Develop readiness checklist and framework to accelerate the development and deployment of innovative solutions that address critical health challenges, improve data accessibility and analysis, and pave the way for advancements in personalized medicine, predictive health analytics, and remote patient care.
2027: Establish an Open Data engagement platform pilot program made up of a dozen key innovation industry partnership to leverage complementary strengths to accelerate innovative solutions for complex healthcare challenges, enhancing efficiency and expanding access beyond what either sector could achieve independently through.
2028: Establish an Open Data engagement platform Phase 1 made up of a dozen key innovation industry partnership to leverage complementary strengths to accelerate innovative solutions for complex healthcare challenges, enhancing efficiency and expanding access beyond what either sector could achieve independently through the steps of:\
Table 3 - HHS Data Improvement Processes - 2025 Status
Division:\
Per the requirements of the OPEN Government Data Act91, the HHS CDO will update this table and still to-be-determined information in a future version of the Living HHS Open Data Plan, following the Department’s reorganization.
HHS encourages public engagement and input on the Living HHS Open Data Plan via GitHub: https://github.com/HHS/living-hhs-open-data-plan
Alternately, for inquiries and feedback, please contact: cdo@hhs.gov
Foundations for Evidence-Based Policymaking Act of 2018. Public Law No: 115-435. https://www.congress.gov/bill/115th-congress/house-bill/4174 ↩
https://www.cdo.gov/phase-2-of-foundations-for-evidence-based-policymaking-act ↩
https://www.congress.gov/bill/118th-congress/house-bill/9566 ↩
https://www.cms.gov/digital-service/open-source-program-office ↩
SOS NSTC. 2019. Open Science Disclosure Risk Management: A Workshop Report and Corresponding Recommendations for the Federal Research Community. A Working Group Report to the SUBCOMMITEE on Open Science, NSTC Committee on Science of the National Science & Technology Council (NSTC). December 2019. 31pp. ↩
https://sharing.nih.gov/data-management-and-sharing-policy/about-data-management-and-sharing-policies/data-management-and-sharing-policy-overview#after ↩
https://www.congress.gov/bill/115th-congress/house-bill/4174 ↩
Office of Management and Budget, Executive Office of the President. (2023). Delivering a Digital-First Public Experience. (OMB M23-22). Office of Management and Budget. Executive Office of the President. https://www.whitehouse.gov/wp-content/uploads/2023/09/M-23-22-Delivering-a-Digital-First-Public-Experience.pdf ↩
Office of Management and Budget, Executive Office of the President. (2019). Phase I Implementation of the Foundations for Evidence-Based Policymaking Act of 2018. Learning Agendas, Personnel, and Planning Guidance. Office of Management and Budget, Executive Office of the President. https://www.whitehouse.gov/wp-content/uploads/2019/07/M-19-23.pdf ↩
Executive Order 14243. (2025). Stopping Waste, Fraud, and Abuse by Eliminating Information Silos. https://www.whitehouse.gov/presidential-actions/2025/03/stopping-waste-fraud-and-abuse-by-eliminating-information-silos/ ↩
Office of Management and Budget, Executive Office of the President. (2019). Phase I Implementation of the Foundations for Evidence-Based Policymaking Act of 2018. Learning Agendas, Personnel, and Planning Guidance. Office of Management and Budget, Executive Office of the President. https://www.whitehouse.gov/wp-content/uploads/2019/07/M-19-23.pdf ↩
Office of Management and Budget, Executive Office of the President. (2023). Delivering a Digital-First Public Experience. (OMB M23-22). Office of Management and Budget. Executive Office of the President. https://www.whitehouse.gov/wp-content/uploads/2023/09/M-23-22-Delivering-a-Digital-First-Public-Experience.pdf ↩
Parasuraman, A., Ball, J., Aksoy, L., Keiningham, T.L. and Zaki, M. (2021), “More than a feeling? Toward a theory of customer delight”, Journal of Service Management, Vol. 32 No. 1, pp. 1-26. https://doi.org/10.1108/JOSM-03-2019-0094 ↩
29 U.S.C. § 794d(a)(1)(A) ↩
https://healthdata.gov/ (on-going effort with the HHS Office of the Chief Data Officer [OCDO]). ↩
https://www.hhs.gov/web/section-508 (on-going HHS effort with all HHS Divisions). ↩
https://open.fda.gov/ (on-going HHS effort with FDA). ↩
See Appendices B and C for responsible data-sharing (on-going HHS effort with OCDO, NIH, CDC, and all HHS Divisions). ↩
https://www.gsa.gov/system/files/NAP4-MH.pdf (on-going HHS effort through the LymeX partnership and OCDO). ↩
https://www.congress.gov/bill/113th-congress/senate-bill/994/text (on-going HHS effort with grants data). ↩
https://www.usaspending.gov/ (on-going federal effort includes HHS data shared with U.S. Department of Treasury). ↩
https://www.grants.gov/learn-grants/grant-policies/data-act-2014.html (on-going HHS effort with grants data). ↩
https://www.challenge.gov/fy23-year-in-review/ (on-going federal effort, led by GSA; HHS Open Data fuels innovation). ↩
https://www.science.gov/ (on-going federal effort; HHS Open Data fuels science). ↩
https://pubmed.ncbi.nlm.nih.gov/ (on-going HHS effort with NIH National Library of Medicine). ↩
https://pmc.ncbi.nlm.nih.gov/ (on-going effort with NIH National Library of Medicine). ↩
https://www.nih.gov/about-nih/nih-director/statements/accelerating-access-research-results-new-implementation-date-2024-nih-public-access-policy (on-going effort with HHS and NIH). ↩
https://grants.nih.gov/grants/guide/notice-files/NOT-OD-21-013.html (on-going effort with NIH). ↩
See Appendices B and C for responsible data-sharing information, while HHS actively updates data policies. ↩
https://academyhealth.org/events/2025-09/2025-health-datapalooza (on-going effort with the HHS OCDO). ↩
https://tophealth.github.io/ (2019–2002 pilot sunset in 2020, and informed the U.S. Census Bureau’s TOPx Toolkit for TOP/TOPx Tech Sprints to transform government data into digital tools for real-world impact). ↩
Stopping Waste, Fraud, and Abuse by Eliminating Information Silos–The White House ↩
Fact Sheet: President Donald J. Trump Eliminates Information Silos to Stop Waste, Fraud, and Abuse ↩
https://www.whitehouse.gov/presidential-actions/2025/02/establishing-the-presidents-make-america-healthy-again-commission/ ↩
https://www.whitehouse.gov/fact-sheets/2025/02/fact-sheet-president-donald-j-trump-establishes-the-make-america-healthy-again-commission/ ↩
https://www.hhs.gov/press-room/nih-cms-partner-to-research-root-causes-of-autism.html ↩
Data Quality Guidelines ensure transparency around the quality of official statistics (FCSM-20-04 A Framework for Data Quality) ↩
https://aspe.hhs.gov/reports/department-health-human-services-evaluation-policy ↩
https://www.congress.gov/bill/115th-congress/house-bill/4174 with OMB implementation guidance M-25-05, see pages 28-29. ↩
https://www.hhs.gov/press-room/nih-cms-partner-to-research-root-causes-of-autism.html ↩
https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence ↩
Brazil General Data Protection Law (LGPD), Law No. 13.709/2018 https://iapp.org/resources/article/brazilian-data-protection-law-lgpd-english-translation/ ↩
https://www.hhs.gov/about/agencies/iea/tribal-affairs/about-stac ↩
https://academyhealth.org/events/2025-09/2025-health-datapalooza ↩
https://health.gov/about-oash/io-programs-initiatives/innovationx/health-human-centered-design/health-long-covid ↩
https://www.cdc.gov/public-health-gateway/php/public-health-strategy/public-health-strategies-for-community-health-assessment-data-benchmarks.html ↩
Carroll, S, et al. 2020. The CARE Principles for Indigenous Data Governance. Data Science Journal, 19: XX, pp. 1–12. DOI: https://doi.org/10.5334/dsj-2020-042 ↩
https://grants.nih.gov/grants/guide/notice-files/NOT-OD-22-214 ↩
Data for Indigenous Implementations Interventions and Innovation (D4I) is an NIH-funded award to the Native BioData Consortium. https://d4itdr.org/ ↩
OMB M-25-05, pages 28-29. ↩
OMB M-25-05, pages 28-29. ↩