Over the past decade, many healthcare organizations have responded to new regulations, market pressures, and innovation demands by layering point solutions onto already complex environments. The result is massive data sets that are fragmented, non-standardized, semantically misaligned, duplicated, or incomplete.
Fragmented data and systems produce fragmented insights, performance gaps, and rising operational costs.
These environments are expensive to maintain and difficult to trust. As regulatory requirements evolve and data volumes grow, IT and administrative teams are forced to repeatedly reconcile, normalize, and validate data before it can be used. When source data lacks consistency and quality, analytics, automation, and AI inherit that uncertainty, undermining confidence in outcomes and slowing progress.
Healthcare cannot continue to solve the same data problems repeatedly with fragmented tools.
From Fragmented to Unified
Today, the technology, architecture, and systems-level strategy exist to shift from fragmentation towards a unified, trusted data foundation. This shift requires transforming disparate data into computable data, which is defined as data that is standardized, semantically aligned, validated, and ready to support automation and intelligence at scale.
Computable data is machine-readable, semantically aligned, high-quality (i.e. de-duplicated) and instantly usable and trusted across systems, applications and use-cases. A computable data foundation at the core of health systems, eliminates ambiguity so that every system interprets data consistently, grounded in semantically-aligned standards. This transformation layer normalizes structure, aligns terminology, resolves identity, and produces complete, de-duplicated records at enterprise scale.
Powered by a FHIR®-native architecture and shared clinical logic using Clinical Quality Language (CQL), this approach ensures data carries both context and meaning. The same high-quality data can reliably support quality measurement, prior authorization, clinical decision support, care management, analytics, and emerging AI-driven workflows. This reduces technological and administrative burden, as well as ongoing IT maintenance.
A computable foundation enables predictable behaviour across downstream workflows because the data itself is validated and continuously optimized.
Computable data is not a one-time milestone. It is the outcome of a continuously optimized data pipeline that validates, refines, and enriches data as it flows through the ecosystem. Organizations that adopt this approach shift from reactive data management to proactive and scalable intelligence.
This transformation is enabled through three strategic steps. Together, they provide healthcare organizations with a future-ready source of truth data model that reduces complexity, increases confidence, and unlocks long-term efficiency.
Step One: Unify
What this enables: A single, trusted foundation that replaces fragmented and legacy systems with enterprise-wide consistency.
Unification brings together clinical, administrative, and document-based data from across the organization into a single, standards-based FHIR repository. Once consolidated and de-duplicated, data becomes reliable, actionable, and ready to support every downstream workflow. Health organizations can:
Healthcare generates some of the largest data volumes of any industry (36% in 2025). At Smile, we call this planetary-scale data. The Smile MegaScale feature enables near-limitless horizontal scalability by connecting multiple database instances and virtualizing them as a single system. The same architecture supports large-scale document repositories (such as CDA documents converted to FHIR) optimized for storage, indexing, retrieval, and exchange.
A unified data foundation provides a secure, high-performance platform for managing and operationalizing healthcare data at near-limitless scale.
Step Two: Transform
What this enables: Consistent meaning, shared logic, advanced terminology services, and trusted intelligence across the enterprise.
Once unified, data is transformed into computable health knowledge through normalization, codification, and shared clinical logic using FHIR and CQL. This ensures that data is not only standardized in format, but structured and semantically-aligned in meaning across clinical, operational, quality, and compliance workflows. Health Organizations can:
A unified data foundation provides consistency and maintains clinical context of data, de-risking scale.
What this enables: Continuous value from a single, trusted source of truth.
When data is unified and transformed, it becomes truly computable and ready to power multiple downstream use cases without duplication of effort or reprocessing workflows. The same trusted dataset can support:
By reusing the same high-quality data across use cases, organizations reduce risk, operational burden, and manage costs, while improving performance, outcomes, and readiness for value-based care initiatives.
A unified data foundation gives healthcare something it has never fully had before: a real-time, secure, computable data engine that delivers consistent, reproducible outcomes across every workflow.
Fragmented systems and one-off integrations are no longer sustainable in healthcare. As data volumes grow and population needs rise, the future belongs to organizations that can unify once, compute continuously, and scale intelligently. Computable data is the foundation that makes this possible, allowing healthcare to move forward without repeatedly rebuilding the same solutions.