RPA in Healthcare: Claims & Prior Auth Automation
RPA in healthcare that gives clinical staff back the hours paperwork steals.
Healthcare staff spend a significant portion of their day on administrative tasks that deliver no clinical value. Prior authorizations submitted manually to payer portals. Patient records reconciled between systems that don't talk to each other. Insurance claims prepared, checked, and filed by hand. Compliance reports assembled from data spread across multiple systems.
We build robotic process automation systems that handle these workflows automatically, claims processing, EHR data entry, prior auth submissions, and billing reconciliation, so clinical and administrative staff focus on patient care instead of paperwork.
Claims processing and prior authorization automation for payer portals
EHR data migration and cross-system patient record reconciliation
Billing and revenue cycle automation that reduces accounts receivable days
HIPAA-aware automation architecture with full audit trails
Bring the problem, the current workflow, or the existing code. We reply with a practical next step within one business day.
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The brief
Start with what is not working.
Good software decisions begin with the constraint, not a list of features or a preferred technology.
01
Prior auth submissions taking days of staff time per week across your practice?
02
Claims rejection rate driven by manual data entry errors your team has to resubmit?
Plain answer
RPA in healthcare automates the rule-based work around care: insurance claims, prior authorization, eligibility verification, EHR data entry, and compliance reporting. RaftLabs designs automation with audit trails for every bot action, sized to one workflow at a time.
The payer portal your billing team opens forty times a day.
A billing coordinator opens the payer portal for the fortieth time today. Same patient demographics, same diagnosis and procedure codes, same clinical justification, retyped out of the EHR into a form that has not changed in years.
Now a bot pulls the demographics, the codes, and the justification from the EHR, completes the payer-specific form, submits it, and checks the status on schedule. What reaches the coordinator is the handful of cases a payer kicked back for real review.
The portal work was never clinical. It was never judgment. It was data moving from one system to another, by hand.
That is the work RPA takes off your team.
Every hour a nurse spends reconciling records is an hour not spent with patients. Every prior auth your billing team submits manually is a task that could be automated, freeing that time for the work that requires a human.
RPA doesn't replace clinical judgment. It replaces the repetitive, rule-based work that surrounds it, the data entry, the portal submissions, the status checks, the report assembly, so your staff has more time for the work that requires a human.
Healthcare administration runs on repetitive data movement: retyping demographics, codes, and justifications between systems that don't talk to each other. That work absorbs staff hours that could go to patient-facing work, and it is the work RPA takes over first. The team that scopes your automation is the team that builds it, tests it in your environment, and hands it over.
Proof
- shipping production software across healthcare, fintech, hospitality, and logistics
- Since 2015
- RaftLabs delivery record
- average client rating across delivered projects
- 4.9/5
- Clutch, verified reviews
- HIPAA architecture defined before any bot is built
- Scoped first
- Healthcare RPA engagements
RPA pays off when the work is high volume and the rules are fixed.
Everything on the left should already be true for your organization. Even one thing on the right, and the workflow needs process work or a different approach before automation fits.
A fit
A high-volume, rule-based workflow your staff runs by copying data between systems: claims, prior auth, or EHR data entry.
An EHR your team works in daily (Epic, Cerner, eClinicalWorks, NextGen, or Athenahealth) that the automation can integrate with.
Manual data entry driving claim rejections or prior auth backlogs you currently absorb with more staff hours.
Not a fit
A workflow that turns on clinical judgment rather than repetitive data movement.
A one-off task that runs a handful of times a month, not at high volume.
No documented process yet, where the steps change every time and live only in someone's head.
What we build
Healthcare processes we automate
Insurance claims processing
Automated CMS-1500 and UB-04 claims preparation, EDI 837 submission, status monitoring, and rejection management. Bots extract ICD-10 and CPT codes from your EHR and submit via your clearinghouse or direct payer EDI. Rejected claims are categorized and routed with the denial reason in plain English.
Prior authorization automation
Automated prior authorization submission across payer portals (BCBS, UnitedHealthcare, Aetna, Cigna). Bots pull demographics, diagnosis and procedure codes, and clinical justification from your EHR, then complete and submit the payer-specific form, with status checks on schedule, escalation when a payer misses its turnaround standard, and a pre-populated appeal workflow on denials.
EHR data entry and migration
Automated data entry from intake forms, referral documents, lab results, and external records into your EHR, eliminating manual transcription and its errors. HL7 and FHIR integration handles real-time exchange with labs, imaging, and pharmacy systems, OCR extraction pulls structured data from scanned documents, and patient records are reconciled across your EHR, billing, and scheduling systems to catch duplicates.
Revenue cycle automation
Automation across the full revenue cycle from patient scheduling to payment posting, where manual steps at each stage compound into extended days in AR. Eligibility verification bots run payer checks 24-48 hours before each appointment, charge capture applies CPT and modifier coding rules before claim submission, denials are routed to the correct rework protocol, and payment posting identifies underpayments against contracted rates.
Compliance and regulatory reporting
Automated assembly of compliance reports from clinical and administrative systems, so compliance staff spend less time on manual compilation and more on analysis. CMS quality measure reporting (HEDIS, STARS, MIPS) pulls clinical data from your EHR, applies measure logic, and generates the submission file, while HIPAA monitoring logs PHI access and flags anomalous patterns for the Privacy Officer. Every report is timestamped, versioned, and logged for audit.
Patient communication workflows
Automated appointment reminders, recall notifications, and follow-ups triggered by EHR events, so front desk staff spend less time on outreach calls. Reminders fire by SMS, email, or voice per patient preference, confirmations update the EHR without staff involvement, recall notices include direct scheduling links, and refill reminders fire before chronic medications lapse.
Tell us which administrative process costs your team the most time.
Process, volume, and current system. We'll design the automation and give you a fixed cost.
We have not published a healthcare RPA case study yet. The closest work we can point to is adjacent, not identical: the same discipline of high-volume document extraction and syncing clean data into an incumbent system your team already runs.
Proof
Adjacent proof: high-volume document extraction and sync
Online course software case study: a beauty education platform with protected video, translated audio, and instructor payouts
Online course software for the beauty industry: instructors publish courses, learners subscribe, and instructors get paid. DRM video on Mux, transcription and translation on ElevenLabs, and two Stripe payment modes, built with AI orchestration on a fixed price.
Gula reaches 50 Indonesian restaurants in its first month by solving multi-platform order chaos
Gula, our own Indonesian B2B platform, gives restaurants and food outlets a single web and tablet app for effortless multi-platform food delivery management.
The proposal is scoped before it is priced:
- Single-process automation
- One workflow automated end to end (e.g., claims submission to 3 payers), including bot development, testing in your environment, and deployment.
- Multi-process program
- Claims, prior auth, and EHR data entry automated together, scoped by process count, payer or system complexity, and integration requirements.
How pricing works
Scope the automation before committing to a program.
We scope every project before pricing it. Start with your highest-volume claims workflow, then add bots for adjacent processes once the first one proves its return.
We scope every project before pricing it. Most health systems start with one bot on their highest-volume workflow, then expand the automation as it proves its return.
Starting investment
The price is locked in writing before work begins, with no hourly billing and no invoice surprises.
No hourly billing
Once we scope your first bot, that price is locked in writing, so there's no hourly billing and no invoice surprises. A scope change is a priced change request, agreed before work begins.
HIPAA by design
Every bot ships with access controls that limit data exposure, encrypted credential management with no hardcoded passwords, and full audit logs of everything it does, in line with your existing HIPAA policies.
Work with us
Tell us where the work is stuck.
Bring the rough workflow, half-built product, or messy brief. We will map the smallest useful first move, then send scope, timeline, and price in plain English.
- Scope and cost agreed before work starts. No surprises. No obligation.
- Working prototype within 3 weeks of kickoff.
- Pay by milestone. You see progress before each invoice.
- 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
- All conversations are NDA-protected.
Common questions
The best RPA candidates in healthcare share three characteristics: they're high volume, rule-based, and currently done by people copying data between systems. Top candidates include: insurance claims submission and status checking (bots submit to payer portals, check status, and flag rejections), prior authorization requests (bots complete payer-specific forms using patient and clinical data), EHR data entry from intake forms or referral documents, patient scheduling and reminder workflows, pharmacy benefit verification, and compliance and regulatory reporting that requires data aggregated from multiple systems.
No software is compliant by default; compliance comes from how it is deployed and governed. Deployments in healthcare typically include a signed BAA with any vendor handling PHI, encryption in transit and at rest, unique bot identities instead of shared logins, and audit logging of every bot action. We document data flows and validate the setup against your own HIPAA policies.
We integrate with EHR systems via three approaches depending on what your system exposes: UI automation (the bot interacts with the EHR interface as a user would, useful when no API exists), API integration (where the EHR exposes a FHIR or HL7 API, we use it directly for more reliable data access), and database integration (for on-premise EHR systems where direct database access is available and appropriate). Common targets include Epic, Cerner, eClinicalWorks, NextGen, and Athenahealth. The integration approach is determined during scoping based on what your specific EHR version exposes.
Time savings depend on your current process, claim volume, and payer mix. Measure the baseline first: minutes per claim, prior auth turnaround, and hours spent on rework. A pilot on one workflow gives you real numbers before committing to more.
They can. Screen-based bots break when interfaces change, and shared bot accounts create PHI exposure. The fix is governance: unique bot identities, monitoring with alerts, a defined owner for each bot, and re-testing after system updates. Most RPA failures trace back to missing maintenance and ownership, not the technology itself.
RPA follows scripted rules and handles predictable steps; AI agents read unstructured input and handle judgment-based ones. Most working healthcare deployments combine both: RPA for the predictable steps, AI for document reading and exceptions. Start with high-volume, rule-based tasks like claims status checks, denial workflows, prior auth routing, and eligibility verification.
We scope before pricing: the number of processes, payer and system complexity, and integration requirements set the cost. Most organizations start with one workflow, then expand as it proves its return. Every engagement is scoped and fixed-price before work begins.