How Connected Data Can Improve Outcomes Across Health and Human Services
The systems that serve people in need are not, for the most part, talking to each other.
A person accessing Medicaid managed care, a state housing assistance programme, a community mental health service, and a food security programme is likely interacting with four separate data environments, governed by four different agencies, each holding information that would make the others more effective. The individual has to re-identify themselves, re-explain their situation, and re-qualify for services at each point of contact.
The agencies, meanwhile, are making decisions based on partial pictures.
This is the health and human services data problem. It is structural, it is costly, and in 2026 it has become both more addressable than it has ever been and more urgent to address.
What Connected Data Means in This Context
Health and human services encompasses a broader ecosystem than clinical healthcare alone. It spans Medicaid and Medicare programme administration, public health agencies, behavioural health services, social services programmes, community health workers, housing and food security providers, and the population health functions that cut across all of them.
Each of these operates on data. And almost none of that data, historically, has flowed meaningfully between these sectors.
Connected data in this context does not mean a single giant repository. It means interoperable systems: the ability for relevant information about an individual, a programme, or a population to be accessed by the people and systems that need it, in a usable form, at the point where a decision is being made.
The OECD published a major report on health data interoperability in July 2026, drawing on data from health systems across member countries. It found that enabling health data interoperability carries a potential value equivalent to between 2.7% and 6.6% of health system expenditure. The report identified improved financial sustainability, accelerated programme efficiency, and stronger population health management as the primary drivers of that value.
The Fragmentation Problem Is Larger Than Healthcare
Healthcare has spent years addressing its internal interoperability gaps. The progress is real. The 2026 State of FHIR Report found that 80% of respondents now report that FHIR is either mandated or recommended by national policy, and 62% report active FHIR use cases in their countries. (Source: healthitanswers.net/interoperability-2026-are-we-fhired-up-yet/)
But the gains in clinical data exchange have not yet extended meaningfully into the adjacent sectors that shape whether health and human services programmes actually work.
Behavioural health is the clearest example. An April 2026 ONC data brief, drawing on data from the 2024 National Substance Use and Mental Health Services Survey, found that while the majority of behavioural health facilities use EHRs to record information, actual exchange of that data with other parts of the health system remains significantly more limited.
Similarly, only 16 to 17% of hospitals reported sending summary of care records to most or all post-acute and behavioural health providers, even as overall interoperability progress has accelerated. The healthcare system has become better at exchanging data within acute care. The broader health and human services ecosystem is still largely siloed.
This matters operationally. A Medicaid care manager who does not know that a member is also receiving housing assistance cannot coordinate those services effectively. A public health agency building population risk models on incomplete data produces incomplete models. A community health worker visiting a client without visibility into that client's prior service history is starting from scratch every time.
What Operational Improvement Looks Like
The gains from connected data in health and human services are not primarily about what happens during a single service interaction. They are about what becomes possible across the lifecycle of a programme or a population.
Administrative deduplication is the most immediate operational gain. When agencies share data in real time, individuals do not need to re-enroll in programmes they are already eligible for. Eligibility verification that currently requires manual coordination across agencies can be automated. Reporting requirements that currently consume significant staff time can be met from shared data rather than duplicated data entry.
Resource allocation improves materially when agencies can see patterns across the population they serve. Which geographies have high Medicaid utilisation and low access to behavioural health services? Where are housing instability and emergency department utilisation patterns correlated in ways that suggest a coordination intervention would be more efficient than continued reactive response? These questions can only be answered when the data that currently lives in separate systems is accessible to the analysts and programme managers who need to act on it.
Financial performance across programmes also improves with connected data. Value-based care arrangements in Medicaid, for example, require the ability to measure outcomes and attribute them to interventions. That measurement is only possible when the data from all the services an individual receives is accessible in a form that can be aggregated and analysed. Programmes that cannot demonstrate outcome performance are programmes that cannot sustain value-based payment arrangements.
Health IT Answers summarised the direction of 2026 interoperability progress accurately: the real advance is moving beyond data exchange to data usability. Systems that can share data technically have been built. What remains is building the governance and analytical infrastructure that turns shared data into operational intelligence.
The Infrastructure That Makes This Achievable
Three infrastructure elements determine whether connected data across health and human services is achievable in practice.
The first is standards adoption. FHIR-based APIs are now the foundation for clinical data exchange under CMS mandate, and their adoption is accelerating. Extending this infrastructure to the non-clinical services that intersect with health requires both the technical adoption of shared standards and the governance agreements that allow agencies to use them across jurisdictional and organisational boundaries.
The second is data governance at the programme level. Connecting data across health and human services raises legitimate questions about consent, privacy, and appropriate use that are distinct from the questions that arise in pure clinical data exchange. Individuals receiving social services have not necessarily consented to their social services data being accessible to their healthcare providers, or vice versa. Building governance frameworks that are specific to these cross-sector data flows, rather than simply extending healthcare privacy frameworks, is a prerequisite for sustainable connected data programmes.
The third is auditability. When data from one system informs a decision made in another, the accountability chain needs to be traceable. Who accessed which data, when, to inform what decision, under what authorisation? In health and human services programmes that are subject to both federal and state regulatory oversight, this auditability is not optional. It is the documentation that makes cross-sector data sharing defensible.
This is where Tamamie's infrastructure work sits. Building the data architecture, integration layers, and event tracking that allow health and human services data to flow securely and accountably across organisational and programme boundaries is what makes connected data a reality rather than an aspiration.
The Shift That Is Already Happening
The organisations that are furthest ahead on connected data are the ones that stopped treating interoperability as a compliance requirement and started treating it as an operational asset.
Carahsoft's 2026 healthcare technology analysis made this distinction clearly: organisations treating CMS interoperability mandates as checkbox compliance exercises are watching competitors turn data exchange into operational advantage. Real-time data feeds reduce prior authorisation delays. Integration platforms surface insights that drive better programme performance. Data infrastructure built for exchange rather than just storage becomes the foundation for population health management.
Health Data Management's September 2026 reporting from the field noted that interoperability has become a multidisciplinary responsibility: it requires collaboration among operational leaders, clinicians, designers, engineers, informaticists, and executives. The technical problem is largely solved. The organisational problem is what remains. (Source: healthdatamanagement.com/articles/why-healthcares-next-interoperability-challenge-is-human)
For health and human services organisations, that organisational work involves building the governance agreements, the shared data standards, and the accountability frameworks that allow data to move across programme and agency boundaries in ways that serve the people the programmes exist to help.
The infrastructure to do that is available. The organisations building it now are the ones that will be able to demonstrate programme outcomes, sustain value-based arrangements, and improve the efficiency of service delivery in ways that siloed data environments make impossible.
Tamamie connects data, workflows, and AI into secure, scalable systems that improve decision-making and operational performance across health systems, pharmaceutical organisations, and public-health environments. Learn more at tamamie.com
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