AI in healthcare isn’t about replacing clinicians – it’s about removing friction. The challenge is not the model demo; it’s the integration: getting secure, governed, reliable AI to work inside your EHR, LIS, PACS, billing, and messaging flows without adding risk or noise.
Healthcare Integrations connects artificial intelligence with the systems you already use – Epic, Cerner, Meditech, Athena, and other EHRs; Orchard, Sunquest, Soft, and NovoPath in the lab; PACS/VNA ecosystems; and revenue-cycle tooling. Our focus is pragmatic AI: we integrate and orchestrate proven AI services and models, embed them into clinical and operational workflows, and wrap everything with security, governance, and observability your team can support on day one and day one hundred.
We meet organizations where they are. If your environment is HL7 v2 heavy, we normalize to and from FHIR when helpful and keep ACK handling, ORU/OBX mapping, SIU/SCH scheduling, and ADT triggers deterministic. If you are FHIR-forward, we adopt R4 resources and events to drive AI actions. Either way, we keep data flows schema-first and traceable.
What you can enable with AI – today
- Ambient documentation & clinical note drafting – Generate structured drafts (S/O/A/P or specialty templates) from transcripts or key signals. We constrain outputs to JSON schemas so your EHR can validate and slot content into the right fields.
- AI-assisted patient communication – Safely handle routine portal messages and calls (prep instructions, refills, post-visit reminders). Escalations route to staff with full transcript context.
- Prior authorization & revenue cycle acceleration – Pre-screen documentation against payer criteria, surface missing elements, assemble cleaner packets, and summarize responses for faster rework.
- Triage and referral intake – Collect symptoms, route to appropriate service lines, and pre-populate discrete data in EHR or care management tools.
- Imaging and pathology orchestration – Ingest inference results, attach provenance, and map them to the correct accession/series so radiologists and pathologists see insights inside their native systems.
- Interoperability automation (HL7 v2 ↔ FHIR) – Normalize codes, enrich OBX segments, validate message structure, and flag anomalies before they reach downstream systems.
How we keep AI safe, compliant, and supportable
- Security by design – HIPAA-aligned controls, encryption in transit/at rest, RBAC/least privilege, and network isolation. Architectures include on-prem, private VPC, or hybrid, with “no-PHI-leaves-our-environment” options (self-hosted models or private endpoints).
- Governance & auditability – Versioned prompt templates, endpoint/model version tracking, structured outputs validated against schemas, and full prompt/response logging. Actions that affect care remain human-in-the-loop.
- Safety controls – Retrieval-augmented generation (RAG) with source linking, guardrails to approved vocabularies, and strict format constraints to minimize unsupported statements.
- Lifecycle management – Monitoring for accuracy, latency, and cost; drift detection; canary rollouts and rollback; and documentation/training so your team can own day-to-day operations.
Integration patterns that make the difference
- Event-driven orchestration – Trigger AI on the right events: a new transcription, an inbound result, a portal message, a referral order. Durable queues and idempotent processors ensure you can retry safely without duplicates.
- Schema-first contracts – Even when AI writes prose, our integrations exchange structured payloads (e.g., required fields for PA packets or clinical notes), which keeps downstream systems happy and simplifies validation and auditing.
- EHR/LIS/PACS embedding – Results appear where people work: note drafts in EHR, inline flags in LIS review screens, measurements in PACS viewers – not in a separate “AI portal.”
- End-to-end observability – Health checks, throughput/latency/failure metrics, and cost monitoring. If you already use our monitoring, we stream AI events into the same dashboards for one place to watch.
Mini-case: turning a promising pilot into a supported workflow
Setting: A multi-site specialty clinic running a modern EHR, with a backlog of portal messages and clinician burnout from documentation. The organization wanted to test ambient note drafting and automate responses to common patient questions.
Approach: We designed an event-driven pipeline: call recordings and transcripts landed in a secure bucket; an AI service produced a structured draft (S/O/A/P), citations to chart data, and a terse summary. Drafts posted back as unsigned notes with a “human-approve” step. In parallel, a message-triage skill handled routine inquiries and escalated edge cases with full context. All prompts, responses, and model versions were logged; safety filters enforced approved vocabularies; and no PHI left the client’s private VPC.
Outcomes: Clinicians consistently reported less after-hours charting; audit logs showed shorter draft-to-sign intervals; patient messages moved faster with fewer hand-offs. Because every step was observable and reversible, the pilot scaled to three additional clinics without rework. The IT team supports it like any other interface – with runbooks, dashboards, and clear SLAs.
Architecture options that match your risk posture
- On-prem only – Self-hosted inference or private endpoints inside your network, with zero-retention policies and strict egress rules. Ideal for high-sensitivity data or tight regulatory constraints.
- Private VPC – Your data stays within a dedicated cloud boundary, with service endpoints locked to your region and access via private links.
- Hybrid – Non-PHI/metadata to managed services; PHI remains on-prem/VPC. Clear data classification and transformation steps ensure nothing sensitive leaves approved boundaries.
Our delivery approach
- Discovery & use-case prioritization – We meet clinical/operational leaders, inventory systems and constraints, and rank use cases by value and risk. Output: a short, actionable roadmap.
- Architecture & security design – Hosting choice (on-prem/VPC/hybrid), data flows, guardrails, and success metrics. Monitoring is defined up-front so proving value isn’t an afterthought.
- Pilot in a safe slice – Contained rollout to one clinic, department, or lab client. We focus on user experience and change management; quick wins build momentum.
- Scale & operationalize – Expand to additional sites/lines with training, documentation, and handoff. We align SLAs with 24/7/365 realities.
- Govern & improve – Scheduled reviews, prompt/model refreshes, and tuning based on usage, errors, and policy changes.
Where AI helps first – by organization type
- Hospitals & health systems – Ambient documentation in high-burnout clinics; AI-assisted discharge instructions linked to portals; nurse-line triage; PA pre-checks; imaging AI orchestration.
- Independent & regional labs – Normalize inbound orders, generate consistent interpretive comments, detect anomalies prior to release, and send AI-backed status notifications to clients. Considering a modernization of your interface engine? See our Mirth → BridgeLink services.
- Specialty clinics & physician groups – Charting assistants tuned to your templates, routine portal response automation, and clean documentation assembly for payers – all inside the EHR.
- Digital health & health IT vendors – Add AI features without building a large integration team. We can operate white-label with your domains and documentation.
What you get with Healthcare Integrations
- Standards-based, secure integrations – HL7 v2 and FHIR mappings that pass audits and fit your policies.
- Structured outputs – JSON contracts and validation so systems downstream accept content without manual cleanup.
- Observability – Health checks, metrics (throughput, failure rates, latency), and cost telemetry from day one.
- Documentation & training – You own the deliverables and can support operations without vendor lock-in.
- White-label delivery – We can run as an extension of your brand when you need to scale services for your customers.
Readiness checklist for CIO/CMIO/IT Directors
- We’ve identified high-value use cases (e.g., notes, triage, PA, interpretive comments) and mapped where in the workflow AI adds value.
- We know which events will trigger AI (new transcript, portal message, order/result) and how to recover safely on retry.
- Data classification is documented: what can leave the network, what must stay on-prem/VPC, and how de-identification applies.
- We have a schema for outputs (note draft fields, PA packet elements, inference artifacts) and a validation plan.
- We’ve defined audit requirements: prompt/response logging, model/endpoints versioning, and retention rules.
- We’ve chosen rollout stages (pilot → canary → production), success metrics, and rollback criteria.
- Support model and SLAs are clear, with runbooks and dashboards for operations.
Call to action – explore services and book a consult
If you want AI integration that fits your workflows without adding risk, we’re ready to help Explore our integration & support services. Contact our team or book a 20-minute free consult.
Want to see related capabilities? Explore our Integration Services or learn how we modernize legacy engines with our Mirth → BridgeLink services.
