Healthcare workflow automation that does not break the next time a portal updates.
End-to-end automation of clinical admin, prior authorization, denial management, RCM, and care coordination workflows. Built with API-first integration, AI-augmented decision steps, and audit trails that pass regulatory review. Built on Azure AI, Azure OpenAI, Claude API, and n8n.
Why most healthcare workflow automation projects underperform
Healthcare operations is full of repetitive, rule-driven work that looks like it should be easy to automate. Prior auth submissions, denial appeals, intake forms, eligibility checks, referrals, status follow-ups. The reason these projects so often underdeliver is not that the work is hard to automate. It is that the integration surface is brittle, the decision steps need more judgment than rule engines provide, and the audit requirements get layered in late.
We build automation that combines API integration where it exists (most modern EHRs and payer portals expose more than teams realize), structured EDI and FHIR exchange where APIs do not, AI-augmented decision steps for the parts that genuinely need judgment, and audit trails designed in from day one. The result holds up to year three of production operation, not just the demo.
Where the ROI shows up first
Four workflow families that consistently produce measurable time and cost savings inside 6 to 9 months of go-live.
Prior authorization
Automated case assembly from the EHR record, payer-specific submission formatting, status follow-up, and AI-drafted clinical justification. Typical 40 to 60 percent reduction in touch time per case, with denial rates dropping as documentation completeness improves.
Denial appeals and RCM
Denial classification, automated appeal letter drafting from payer policy and clinical record, coding suggestion against payer rules, and prioritized worklists for the RCM team. Typical 10 to 20 percent reduction in denial rates and significant lift in appeal-overturn percentage.
Patient intake and care coordination
Intake forms with structured data capture into the EHR, eligibility verification, referral processing and status tracking, post-discharge follow-up triggering. Reduces front-desk and care management admin time without losing the patient touchpoint.
Clinical admin and operations
Order management, results follow-up, clinician inbox triage, scheduling exception handling. The cumulative tax of small-task admin gets compressed back into clinical time, which is where the real economic value sits in any clinical org.
How we deliver
Five phases, KPI-first. Every workflow ships against a measurable baseline and a target. No demo theater.
- 01
Workflow discovery and KPI baseline (2 to 3 weeks)
Map the current workflow end to end. Capture the volume, current touch time, error rate, and cost. Identify the integration surface (EHR, payer portal, EDI, internal systems). Define the KPI the automation must move and the target. Output: scoped statement of work with baseline numbers and a defensible target.
- 02
Integration architecture (3 to 4 weeks)
Design the integration approach (API where possible, EDI and FHIR where structured, AI-augmented for judgment steps, encapsulated UI automation only as last resort). Set up monitoring and alerting. Build the audit trail design. Architecture review with operations and compliance leadership.
- 03
Build and pilot (8 to 12 weeks)
Implement the workflow with full audit logging, alerting, and exception handling. Soft-launch on a defined subset (one specialty, one payer, one care line). Daily KPI tracking against baseline. Operations team trained on exception handling.
- 04
Validation and full rollout (3 to 4 weeks)
Compare pilot KPIs against baseline. Refine thresholds, alerts, and exception flows. Full rollout to all in-scope volume. Operations runbook updated, on-call rotation in place.
- 05
Operations, monitoring, and evolution
Continuous KPI monitoring, schema-change alerts, quarterly retrospective on integration health. Workflow updates as payer rules and EHR capabilities evolve. Optional managed support for organizations without an in-house automation team.
What you get
- Production workflow automation against your EHR or operational systems
- API-first integration with EDI and FHIR fallbacks where required
- AI-augmented decision steps for the judgment-heavy parts
- Defensible audit trail with structured logging for HIPAA and payer audit
- Exception handling and operations runbook
- Daily KPI dashboard tracking baseline against target
- Schema-change alerting and integration health monitoring
- Operations team training and on-call rotation setup
- Annual ROI reconciliation against the original baseline
- Optional managed support and ongoing workflow evolution
When to engage us
Your prior auth team is the bottleneck
If prior auth is delaying care or eating clinical operations time, automation pays back inside the first year. Often inside the first six months.
Your denial rate is climbing
Rising denial rates usually trace to documentation gaps and payer rule drift. Automated denial classification, appeal drafting, and rule-aware coding suggestion close the loop.
You inherited brittle RPA
If your team is supporting a fleet of UI-scrape RPA bots that break monthly, the right move is API-first replacement, not more bots. We help you migrate.
You are a healthtech building automation features
Healthcare buyers will not accept demo-grade automation. We help healthtech teams ship workflow automation with the audit, monitoring, and exception handling buyers expect.
Pitfalls we see in workflow automation projects gone sideways
- UI scraping when an API exists. Modern EHR and payer integrations have more API surface than teams realize. UI scraping should be last resort, not first instinct.
- Skipping the KPI baseline. Without baseline numbers you cannot tell if the automation worked. Capture them before kickoff.
- Ignoring exception handling. The 5 percent of cases that break the happy path are where most of the operational risk lives. Design for them up front.
- No schema-change monitoring. Portals and APIs change. Without active monitoring, the workflow fails silently and you find out from a clinician or a payer call.
- Treating automation as a headcount cut. Successful deployments redirect operations capacity rather than eliminate it. The framing affects adoption and long-term success more than the technology does.
Related reading
GenAI and AI agents in healthcare
Where agentic workflows fit. Prior auth, RCM, and care coordination patterns under clinical evaluation and governance.
HCC risk adjustment automation
The clinical NLP workflow that produces the most defensible ROI. Pre-visit surfacing for ACOs and Medicare Advantage.
ACO data platform consulting
Workflow automation runs on top of the data platform. Clean data, attribution, and FHIR foundation come first.
Frequently asked questions
What's the difference between RPA and what you build?
Traditional RPA records UI clicks and replays them. It works for stable interfaces with structured input and breaks the moment a vendor ships a UI update. What we build combines API integration where APIs exist (most modern EHRs and payer portals), structured data exchange where it does not (835/837/270/271 EDI, FHIR endpoints, PDF parsing where required), and AI-augmented decision steps for the parts that need judgment. The result is durable instead of brittle.
Where does workflow automation actually pay back fastest?
Prior authorization (40 to 60 percent reduction in touch time per case), denial appeal preparation (50 to 70 percent reduction in coder time per appeal), RCM coding suggestions (10 to 20 percent reduction in denial rates), patient intake (30 to 50 percent reduction in front-desk admin time), and clinical admin around referrals and orders. Each has measurable baseline and post-deployment KPIs you can put on a CFO scorecard.
Do you need access to our EHR to build automations?
Usually yes, but the access pattern depends on the workflow. Read-only FHIR access for ingestion is enough for most analytics-style automations. Write-back into EHR (orders, notes, charges) requires deeper integration via vendor APIs (Epic Bridges, Cerner CCL, Meditech APIs) or via HL7 interfaces, with appropriate security review. We scope the integration depth required as part of discovery.
How do you handle compliance and audit on automated workflows?
Every automated decision is logged with the input, the rule or model that produced the decision, the output, and the human reviewer where applicable. Audit trails are structured for HIPAA, payer audit, and any applicable state regulatory review. Workflows that touch billing or coding decisions are designed to be auditable from the first commit, not retrofitted.
How do you keep automations from breaking when payer or EHR portals change?
Monitor and alert. Every integration has health checks that detect schema or behavior change. When a portal changes, alerts fire before the workflow fails silently. Where APIs exist we prefer them over UI scraping. Where UI is the only option we encapsulate it in a single replaceable layer so a fix is a one-day update instead of a multi-week rewrite.
Can workflow automation work alongside our existing operations team?
Yes, and the framing matters. Automation reduces volume on repetitive work and shifts the team toward exceptions, judgment calls, and higher-leverage tasks. Successful deployments are designed with operations leadership in the room from day one and include staffing models that explicitly call out the work the team will own going forward.
Let's talk about your value-based care project.
Working on a value-based care contract, ACCESS Model application, EHR integration, or AI-enabled clinical workflow project? Book a 20-minute discovery call or email [email protected].