Written by Technical Team | Last updated 15.11.2025 | 10 minute read
Integrating Altera Sunrise into a broader digital health ecosystem is rarely a simple interface exercise. It is a strategic architecture decision that affects clinical workflows, patient safety, reporting, and the agility of the entire organisation. As hospitals consolidate systems, adopt new specialist solutions and expand remote care, their Sunrise deployment must communicate reliably and at scale with hundreds of internal and external applications.
In this context, middleware is no longer just “the thing that moves HL7 messages around”. It becomes the abstraction layer that stabilises a messy estate of devices, departmental systems, cloud services and data feeds into something Sunrise can consume predictably. When middleware is poorly designed, organisations end up with brittle point-to-point links, opaque data flows and integration outages that clinicians experience simply as “the EHR is down”. When it is architected well, Sunrise feels like the single coherent nervous system of the hospital, even when the underlying systems landscape is anything but.
Designing that middleware for high performance requires more than picking a broker and mapping some messages. It involves understanding how Sunrise behaves, how clinicians work, and which architectural choices will still serve the organisation well in five or ten years. The following sections explore a pragmatic, deeply technical approach to architecting high-performance middleware specifically for Altera Sunrise integration, with an emphasis on real-world constraints in UK and international health systems.
Altera Sunrise (formerly Allscripts/Eclipsys) is positioned as an enterprise-grade EHR platform for acute and community hospitals, and is deployed in both North America and a number of international markets, including some NHS organisations. Architecturally, Sunrise presents a rich clinical application layer backed by a combination of relational data stores, domain services and integration endpoints. For integration teams, what matters most is that Sunrise is not a monolith with a single “integration port”; it exposes different channels and behaviour patterns for orders, results, clinical documentation, scheduling and administrative data.
Within a typical trust or health system, Sunrise rarely exists in isolation. It must interoperate with laboratory systems, radiology and PACS, specialist departmental solutions, theatre systems, pharmacy and dispensing robots, patient flow tools, remote monitoring platforms and a variety of data warehouses and analytics stacks. Many of these systems were procured at different times, by different teams and with different integration assumptions — proprietary APIs, specific HL7 versions, batch file transfers or event-driven streams. Middleware becomes the negotiation layer between these worlds.
Historically, organisations often relied heavily on classical interface engines to connect Sunrise to the ecosystem, focusing largely on HL7 v2 messaging. While these engines remain valuable, modern environments demand more: event-driven patterns, RESTful APIs, FHIR interfaces and cloud connectivity for third-party services and AI-driven tools. Middleware should therefore be conceptualised as a broader integration platform that can speak multiple protocols, orchestrate complex workflows and provide robust observability and governance, rather than simply moving messages from one system to another.
This extended role is especially important in device and point-of-care scenarios. Middleware solutions increasingly serve as the bridge between near-patient testing devices and enterprise EHRs, automating the flow of orders and results while ensuring accurate patient and encounter association. When these pathways are architected for low latency and high reliability, clinicians experience near real-time updates in Sunrise, supporting faster decision-making and better patient outcomes.
A high-performance middleware architecture for Sunrise is not defined by a particular vendor product. Instead, it is defined by a set of architectural principles that guide system behaviour, resilience and scalability across the integration estate.
At the core is loose coupling. Middleware should treat Sunrise and each connected system as independently evolving components with clear, versioned contracts. A canonical internal model, used to normalise data from disparate sources, simplifies mappings into Sunrise and reduces the risk of breakage when upstream systems change. Where clinically appropriate, asynchronous integration should be preferred to reduce direct dependencies and improve system-level resilience.
Scalability must be considered early. High-volume interfaces — especially ADT, order/result traffic and clinical documentation updates — can generate sustained workloads punctuated by spikes during busy clinical periods. Middleware should use stateless processing nodes behind queues or brokers, allowing traffic to scale horizontally. This approach avoids bottlenecks associated with single-server interface engines and provides flexibility to grow processing capacity with demand.
Equally important is back-pressure management. Like all EHRs, Sunrise has operational thresholds governing how many inbound updates it can process without degrading performance. Middleware must absorb bursts using buffering, queueing and controlled concurrency. This lets Sunrise maintain stable performance even under extreme load and ensures consistency without overwhelming the EHR.
A set of pragmatic design tenets helps embed these ideas into everyday architecture decisions:
When these principles are consistently applied, middleware becomes not only high-performing in terms of throughput, but high-performing as an organisational asset — easier to extend, safer to modify, and more transparent for both technical and clinical stakeholders.
Once principles are set, the next step is to design Sunrise-centred data flows using proven integration patterns that align with the EHR’s internal behaviours. The goal is to create data pipelines that reflect how Sunrise models patients, encounters, orders and documentation.
Many existing Sunrise deployments rely on HL7 v2 for ADT, orders and results. This remains a robust and widely supported protocol, especially where upstream systems already rely on HL7. However, HL7 should not necessarily be treated as the middleware’s native internal format. A more modern strategy is to convert inbound messages into a canonical model inside the integration platform and then generate outbound formats — HL7, FHIR, XML, JSON or API payloads — depending on Sunrise’s requirements. This approach decouples upstream evolution from Sunrise integration and simplifies future expansion.
RESTful APIs and FHIR interfaces play a growing role in newer or strategically important integrations. These API-driven models provide clear error semantics, simpler tooling, better test automation and improved compatibility with cloud-native services. In practice, hybrid flows are common: a FHIR-based upstream system may send structured resources to middleware that must be transformed into HL7 messages for Sunrise, or vice versa. Middleware should be comfortable operating across both worlds.
Event-driven integration patterns deliver significant benefits where responsiveness and loose coupling are essential. Publishing domain events such as “OrderPlaced”, “ResultReady” or “NoteSigned” enables multiple subscribers to react independently. Analytics platforms, alerting services, operational dashboards and care-coordination tools can all consume these events without additional point-to-point integrations. Sunrise itself can benefit from event-driven updates when implemented carefully alongside its existing messaging channels.
Choosing appropriate patterns depends heavily on clinical workflow. Request–reply is ideal when a Sunrise user is actively waiting for a response from an external system. Fire-and-forget works for notification-style updates. Publish–subscribe patterns are well suited to multi-consumer scenarios. More advanced patterns such as content-based routing, message aggregation or data enrichment become relevant when consolidating complex departmental data or combining multiple upstream sources into a single coherent update before sending it to Sunrise.
Performance, observability and resilience form a tightly coupled trio in middleware design. Without visibility, performance tuning is guesswork. Without resilience patterns, high throughput simply leads to faster failure. For Sunrise integration — where problems directly affect frontline clinical activity — getting these layers right is essential.
The journey begins with a clear performance model. Identify the highest-volume and most latency-sensitive workflows: ADT, pathology results, imaging updates and clinical documentation. Establish baseline performance expectations for end-to-end latency from the upstream source to Sunrise and model peak loads associated with different care environments and times of day. These metrics inform queue sizing, thread pools, connection management and scaling policies.
Observability must be designed in, not bolted on. Middleware should expose:
Structured logging with correlation IDs and patient or encounter references (appropriately pseudonymised where needed) makes it possible to trace a single event from source system to EHR. Distributed tracing tools provide even deeper insight across microservices, brokers, APIs and transformation layers, dramatically reducing diagnosis time for intermittent integration issues.
Resilience patterns must be implemented with care. Timeouts should be tuned to prevent long waits that block processing pipelines. Retry strategies should be intelligent enough to address intermittent problems but conservative enough to avoid overwhelming Sunrise with duplicate calls. Idempotency is crucial: operations must produce the same result even when invoked multiple times, especially during replay scenarios after downtime.
Circuit breakers help isolate Sunrise from downstream failures and provide predictable behaviour when dependent services are slow or unavailable. Graceful degradation strategies ensure that non-essential integrations pause when capacity is limited, preserving bandwidth for clinically urgent pathways. Replay tooling allows batches of messages to be reprocessed safely after downtime without risking duplication or corruption.
Non-functional testing should be treated as a first-class discipline. Load testing under realistic Sunrise usage patterns, failure injection to validate retry logic, and chaos exercises to evaluate recovery capabilities collectively provide confidence that the integration platform will behave correctly during real-world operational stress.
The best middleware architecture will drift into fragility without strong governance. As clinical services procure new tools, as regulatory reporting requirements evolve and as vendors introduce new APIs, the risk of uncontrolled or duplicative interfaces grows. A structured governance model ensures consistency, maintainability and clarity across the entire Sunrise integration landscape.
A central integration architecture board, ideally with representation from clinical, operational and technical teams, can set standards for patterns, protocols, testing criteria and data modelling. A maintained integration catalogue describing every Sunrise-related flow, its purpose, ownership and technical implementation provides essential visibility. This catalogue becomes invaluable during upgrades, impact assessments and audits.
Security considerations are fundamental in healthcare integration. Middleware must enforce strong access control at every point where patient data flows. Encryption in transit and at rest should be standard. Identity and access management frameworks based on OAuth 2.0 and OpenID Connect help prevent credential sprawl and enable fine-grained privilege control. Internal access to integration consoles, logs and tooling must be carefully restricted and audited.
Future-proofing requires planning for both technical and clinical evolution. Technically, this may involve adopting FHIR where appropriate, containerising middleware services, introducing event streaming platforms, and integrating with cloud-native observability and automation tools. Clinically, it means recognising that Sunrise may be one component of a wider regional or national care ecosystem. Middleware should therefore be capable of serving as an enterprise integration fabric rather than a Sunrise-only adapter layer.
A highly effective approach is to treat middleware as an integration product with its own roadmap, ownership and service-level commitments. This promotes the creation of reusable components, shared adapters and standardised patterns rather than one-off, point-to-point integrations. It also supports incremental modernisation: new technologies can be introduced alongside existing interfaces, with flows gradually migrated as capabilities mature.
Ultimately, architecting high-performance middleware for Altera Sunrise is not solely a technical challenge. It is an organisational capability, combining engineering, clinical insight, operational discipline and strategic foresight. When executed well, it ensures that Sunrise remains a stable, trusted centre of the clinical record while the surrounding digital ecosystem continues to evolve. The result is not just faster integrations, but a safer, more coherent and more agile digital environment for clinicians and patients alike.
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