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Health systems often have longer payment cycles than standard commercial customers due to EHR-driven AP workflows. When a medical device company or healthcare equipment distributor sells to a hospital running Epic, Cerner, or Athenahealth, payment release depends on how that system routes invoices through its EHR-linked AP workflow. A purchase order mismatch in Epic or a disputed charge in Cerner can push a 30-day invoice past 90 days without a single outbound call from your AR team triggering a resolution.
AR automation handles dunning, cash application, and dispute resolution without human intervention at each step. For companies selling to health systems, that means tracking invoice status inside your customer's EHR-linked workflow, identifying which aging accounts are stalled in an approval queue versus genuinely disputed, and contacting the right person before invoices age past 60 days. This guide covers how Epic, Cerner, and Athenahealth process payments from your perspective as a vendor, along with the implementation patterns and common stall points that extend collection timelines.
What this guide covers and what Stuut does: The Epic, Cerner, and Athenahealth sections below describe your customer's payment environment, not Stuut's integration surface. Stuut connects to your ERP via API and automates collections outreach, cash application, and dispute handling on your side. Stuut does not integrate with customer EHRs. Understanding how your customers' EHR workflows delay payment release helps your AR team act earlier and contact the right people. That is the value of the EHR content here.
Your health system customer's EHR controls the data that drives their payment release: Purchase order records, invoice approval queues, contract pricing data, and payment authorization workflows. Without visibility into how those systems process vendor invoices, your AR team follows up on accounts based on aging date rather than actual payment status, which wastes calls and misses the accounts that are genuinely stalled.
This changes how AR teams selling to health systems work daily. When invoice status tracking, remittance matching, and first-contact outreach run automatically against your health system accounts, your collectors shift from dialing aging buckets to managing the exceptions that actually require negotiation: Disputed contract pricing, purchase order discrepancies, and approval escalations inside the customer's system. The path to lower DSO for companies with health system customer concentrations runs through eliminating the manual steps between your invoice date and the customer's payment release.
Manual collection processes between invoice delivery and payment posting introduce compounding delays across health system accounts. AR teams that rely on aging reports and manual outbound calls miss the accounts stalled inside the customer's EHR-linked AP workflow early enough to intervene. By the time an invoice ages past 60 days, the customer's internal approval process has often created a dispute that requires escalation rather than a simple follow-up call.
When an AR platform tracks invoice status inside your customer's EHR-linked workflow, it updates aging buckets based on actual payment queue position rather than elapsed days alone. This reduces the gap between when a payment stalls and when your team contacts the right person to resolve it. For invoices approaching contractual payment terms, faster status visibility reduces the risk that a resolvable approval delay becomes a formal dispute.
Mismatches between your invoice data and the health system's purchase order or contract terms are the most common reason vendor invoices stall in an EHR-linked AP workflow. Wrong ship-to address, mismatched product codes, or pricing that doesn't match the contract on file in the customer's system can hold a payment without triggering an outbound dispute notification. Validating invoice data against the customer's procurement records before submission reduces the rejection rate and shortens the payment cycle.
Epic covers more than 325 million patient records worldwide, and most major health system customers in the medical device and healthcare equipment markets run Epic as their clinical and financial system of record. When your customer runs Epic, payment release depends on how their Epic-linked AP workflow processes vendor invoices, which adds approval steps and timeline variability compared to customers running standalone accounting systems.
Epic uses the HL7 FHIR (Fast Healthcare Interoperability Resources) standard, and all FHIR API access requires OAuth 2.0 authentication. Backend system-to-system integration uses the Client Credentials flow with JWT-based client certificates.
Epic uses the HL7 FHIR standard and OAuth 2.0 authentication for API access. For vendors selling to Epic-based health systems, the relevant integration question is how your invoicing and collections platform accesses payment status and purchase order data from the customer's Epic environment. Every Epic customer site requires independent approval and configuration for third-party API access, regardless of technical readiness. A basic FHIR read-only connection to a single Epic site can take 2 to 6 months. Full bidirectional access covering payment status and invoice approval typically runs 6 to 12 months. For medical device companies running AR through SAP, Oracle, NetSuite, or Dynamics 365, Stuut connects to your ERP via API in 3 to 4 days without touching your ERP configuration. That connection automates collections outreach and cash application on your side. Accessing your customer's Epic environment for invoice status is a separate project governed by Epic's per-site credentialing process, and Stuut does not provide that connection.
The FHIR Patient and related resources manage clinical data, but vendor-facing AR work depends on Epic's financial module data: Purchase order records, contract pricing, invoice approval queues, and payment authorization workflows. When an AR platform reads invoice status from a customer's Epic environment in real time, it identifies which invoices are in an approval queue, which are matched to POs, and which are flagged for pricing review. This shifts follow-up calls from generic aging buckets to specific resolution paths based on where the invoice actually sits in the customer's workflow.
AR platforms with visibility into Epic payment release workflows can identify when payments are authorized, track them through the customer's payment run, and match remittance data to the correct invoices in real time. For ERP-based AR environments, Stuut achieves a 95%+ automated match rate by reading remittance data across bank accounts, lockboxes, and digital payment rails, helping reduce the payment matching backlog that delays month-end close.
Epic's approval hierarchy means a held invoice can sit with a department budget owner, a central AP approver, or a contract pricing reviewer depending on the hold reason. AR platforms that integrate directly with a customer's Epic environment can read queue position alongside hold type and route outreach to the correct escalation contact. For AR teams without that EHR connection, the same outcome requires your collector to contact the customer's AP team, confirm the hold reason, and route follow-up manually. Once the hold reason is identified, Stuut's AI voice agent can place outreach to the AP contact carrying full invoice context, open balance, and prior communication history from your ERP, so the first call is a targeted resolution conversation rather than a status check.
Cerner Millennium, now under Oracle Health, is the second-most deployed EHR in U.S. health systems. Cerner's Ignite platform and the RevElate patient accounting module handle financial workflows for many mid-size and regional health systems. For vendors selling to Cerner-based customers, Cerner's more standardized API architecture across instances means payment status and invoice approval data is more consistently accessible than in heavily customized Epic environments. RevElate supports open API and workflow automation, reducing the customization burden compared to legacy Cerner integrations. The Cerner Open Developer Experience program provides sandbox environments and developer resources.
Cerner supports RESTful APIs and SMART on FHIR APIs through Ignite. The credentialing process involves registering your application in the Cerner developer portal, obtaining OAuth 2.0 credentials, and completing sandbox testing before connecting to production. For vendor AR purposes, the key Cerner API resources cover purchase order data, billing account information, and payment status. Compared to Epic's per-site approval model, Cerner's Ignite APIs offer more standardization across instances, which can reduce initial setup to 4 to 8 weeks for a single customer organization.
AR platforms that integrate directly with a customer's Cerner environment can poll for invoice status updates on a configurable schedule, typically every few hours for active accounts in the 0 to 30 day bucket and daily for older aging buckets. When Cerner returns a hold, the platform can categorize it by reason code, attach supporting documentation, and route it to the appropriate workflow, reducing per-dispute processing time from approximately 15 minutes to seconds.
Medical device and healthcare equipment companies that receive bulk ACH deposits covering hundreds of individual invoices benefit from automated matching logic that runs on your ERP-side data, not inside your customer's Cerner environment. Stuut breaks bulk deposits into sub-payments, matches each one to the corresponding invoice using remittance data and bank transaction records from your ERP, and posts cash application entries back in real time. This shifts your cash application staff toward the exceptions that require judgment rather than routine matching, and does not require access to your customer's Cerner environment.
Proactive contact resolves holds faster than waiting for the customer's system to send a notification. Because Cerner's Ignite APIs return standardized hold reason codes, an AR platform can identify whether an invoice is held for PO mismatch, pricing review, or missing documentation and tailor the outreach message accordingly. An email that references the specific hold reason and attaches the missing document resolves faster than a generic follow-up call asking the AP team to investigate.
Athenahealth's cloud-native architecture offers more than 800 API endpoints, covering standard FHIR resources and proprietary endpoints for administrative, clinical, and financial functions. Athenahealth is most common in physician group practices, ambulatory care networks, and smaller health systems, which means medical device companies with physician group customers are more likely to encounter Athenahealth than Epic or Cerner. Its cloud-native model makes it the fastest of the three major EHRs to access for AR-related data, with typical integration timelines of 3 to 6 weeks for standard configurations.
Athenahealth uses OAuth 2.0 for API authentication. You register your application through the Athenahealth developer portal, obtain client credentials, and configure scope to cover billing accounts, purchase order data, and payment resources. Unlike Epic, which requires per-site approval at each customer location, Athenahealth's cloud-native, multi-tenant architecture means a single credential set covers your entire practice or network. This cloud-hosted model is the primary reason Athenahealth integrations complete faster than comparable Epic projects.
Athenahealth's billing API supports pre-submission validation that flags data mismatches before an invoice enters the approval queue. AR platforms with direct Athenahealth access can validate invoice fields against the customer's records before submission. Without that EHR connection, the equivalent discipline is validating your invoice data against your own contract records and purchase order confirmations before submission, which removes the most common hold triggers without requiring access to the customer's system.
Athenahealth posts payment data automatically, but complex payment scenarios, such as bulk ACH deposits covering multiple accounts or partial payments with contractual adjustments, still require an AI layer to resolve without manual intervention. An AI matching layer running against your ERP-side bank transaction records and payment remittance data resolves bulk deposits and flags exceptions that need human review, without requiring access to the customer's Athenahealth environment. Stuut handles this matching on your side of the transaction. Manual remittance matching is one of the most time-consuming tasks for AR teams with high health system customer volumes, and eliminating it returns hours your collectors can spend on the accounts where a human conversation is the only thing that moves payment forward.
Athenahealth's cloud-native architecture supports event-based webhooks, which means AR platforms with direct Athenahealth access can trigger outreach the moment a hold is flagged. For vendors without that EHR connection, Stuut triggers outreach based on aging thresholds and payment status changes visible in your ERP, which narrows the response gap without requiring access to the customer's system. For medical device companies with physician group customers, Athenahealth's typical AP contact is a practice manager rather than a centralized hospital AP department, so SMS and AI voice reach the decision-maker faster than formal email chains. Reaching AP contacts through the channels where they actually respond improves payment rates, and the shorter response chain in physician group environments can reduce the number of touchpoints needed to resolve a hold.
The three major EHRs differ meaningfully in API maturity, credentialing complexity, and how quickly vendors can gain visibility into payment status and invoice approval data. For AR teams managing health system customer concentrations, knowing which EHR your customer runs affects how you prioritize integration effort and how quickly you can reduce collection lag on those accounts.
Integration timeline comparison:
Source: Stuut estimates based on implementation experience. Actual timelines vary by customer site configuration, IT resource availability, and EHR version.
Legacy AR platforms following the 6-plus month implementation timeline typically require dedicated developer resources, custom HL7 interface builds, and extensive change management before go-live. Modern FHIR API approaches eliminate the custom code layer and reduce total effort significantly, though EHR integrations remain more complex than connecting to a standard ERP.
Rate limiting is a common technical obstacle after credentials are provisioned. High-volume queries, such as polling invoice status for thousands of active accounts simultaneously, can trigger throttling that delays updates. The fixes are straightforward:
Athenahealth's cloud architecture handles high-volume polling more predictably than on-premise Epic configurations, where per-site rate limits vary based on each hospital's infrastructure.
The following checklist covers the primary steps for AR teams at medical device and healthcare equipment companies integrating with health system customers running Epic, Cerner, or Athenahealth.
EHR AR integration checklist:
For EHR integrations, IT's involvement typically covers two tasks: Generating client credentials in the EHR developer portal and configuring scope permissions. The level of effort varies meaningfully by EHR. Epic requires a security review and Business Associate Agreement evaluation at each site. Cerner and Athenahealth have more standardized credentialing processes. For ERP-based AR integrations, the credential setup typically involves less complexity and fewer hours of IT time.
No two Epic environments are identical. Hospitals configure custom fields, status codes, and Z-segment extensions (custom data fields appended to standard HL7 messages to capture site-specific information) that deviate from base FHIR resource definitions. During the initial integration setup, the AR platform must map your environment's specific field structure to its data model. This custom field mapping can contribute to longer Epic integration timelines compared to Cerner or Athenahealth, and it requires documentation before development begins rather than during it.
Duplicate payment posting can occur when remittance data arrives before the EHR's invoice records are fully updated, potentially causing the same payment to be matched and posted twice. The solution combines idempotency keys that check for existing postings before committing each transaction with audit logging that flags anomalies and treats the EHR as the authoritative source. AR platform comparisons frequently turn on this specific capability because duplicate posting errors consume the time savings automation was meant to generate.
Where modern FHIR APIs are not available, three integration methods cover legacy EHR environments:
API-first integration is more durable than RPA because it connects to data structures rather than user interface elements. An Epic version upgrade changes the UI but does not change the FHIR Patient resource structure, so API connections are less likely to break than screen-scraping tools. That said, FHIR version transitions can introduce backward compatibility considerations that require testing and planning, so integration maintenance is an ongoing responsibility regardless of approach.
Sync conflicts between the customer's EHR and your AR platform can trace to timing gaps: An invoice approval or PO match status updates inside the customer's Epic environment, but your AR platform's next polling cycle runs before the EHR has fully committed the change. The resolution is a short delay between EHR write events and AR platform reads, combined with conflict resolution logic that treats the customer's EHR as authoritative and overwrites stale AR platform data on the next successful poll. This is a configuration decision made during implementation, not a reactive fix.
Organizations operating across multiple EHR systems benefit from an AR platform that normalizes data internally. Design your internal data models around FHIR resources, then build adapters that translate each EHR's specific data format to the normalized schema. EHR integration enables comprehensive insights across systems when the normalization layer handles EHR-specific variations rather than pushing that complexity to the AR platform's application logic. This approach lets you add additional EHR connections incrementally without rebuilding the core integration each time.
Book a demo with the team to see how Stuut connects to your ERP via API in 3 to 4 days, automates cash application at a 95%+ match rate, and executes collections outreach across email, SMS, and AI voice. Stuut connects to SAP, Oracle, NetSuite, or Dynamics 365 on your side and does not require access to your customer's EHR.
For a medical device company seeking to track invoice and payment status inside a health system customer's Epic environment, standard FHIR API integration for a single Epic site takes 2 to 6 months, driven primarily by per-site credentialing, security review, and sandbox testing requirements. Full bidirectional access covering payment status and invoice approval can run 6 to 12 months for complex configurations.
Some configuration is required, particularly for mapping custom fields specific to your customer's EHR environment and establishing the correct scope permissions for vendor-facing financial data. Modern FHIR API integrations avoid modifying the EHR's core clinical or financial workflows. By contrast, ERP-based AR integrations like Stuut's connection to SAP, Oracle, NetSuite, or Dynamics 365 complete in 3 to 4 days without modifying your ERP configuration.
AR teams that automate invoice tracking, remittance matching, and collections outreach for health system customers typically reduce DSO by eliminating the manual gap between payment stalls and first contact. Stuut customers have achieved an average 37% DSO reduction across their portfolios. Results vary by customer mix and existing AR process maturity.
Athenahealth's cloud-native, multi-tenant architecture means a single credential set covers your entire practice or network without per-site approvals. Epic requires individual credentialing and security review at each customer site, which is the primary driver of longer integration timelines.
Stuut reduces manual effort in payment matching, invoice resends, and routine AP-contact follow-ups by up to 70%, running against your ERP data rather than your customer's EHR. Your AR team shifts to complex disputes, escalated PO mismatches, and high-value health system relationship management that requires human judgment. PerkinElmer's AR team used this shift to cover 80% of tail customers through automation while focusing human effort on their largest accounts, collecting $300M in the process.
DSO (Days Sales Outstanding): The average number of days between invoice date and cash receipt. For companies selling to health systems, DSO is often elevated compared to commercial customers because EHR-linked AP workflows add approval steps between invoice submission and payment release. Stuut customers average a 37% DSO reduction after deploying autonomous collections.
CEI (Collection Effectiveness Index): A ratio measuring the percentage of revenue collected against revenue available to collect over a period. A CEI above 80% indicates an effective collections function.
FHIR (Fast Healthcare Interoperability Resources): An HL7 International standard for exchanging healthcare data via RESTful APIs. FHIR R4 is the current version supported by Epic, Cerner, and Athenahealth for third-party integrations.
HL7 (Health Level Seven): A set of international standards for transferring clinical and administrative data between healthcare systems. HL7 v2 remains widely used for real-time clinical messaging via MLLP connections.
Z-segment extensions: Custom data fields appended to standard HL7 messages by individual healthcare organizations to capture site-specific information not covered by the base HL7 standard. No two Epic environments are guaranteed to use identical Z-segment configurations, which requires custom field mapping during EHR integration.
Three-way match: The AP process by which a health system confirms that a vendor invoice aligns with the original purchase order and the goods receipt record before releasing payment. Three-way match failures are among the most common reasons health system vendor invoices stall past 30 days without a formal dispute notification reaching the vendor's AR team.
RPA (Robotic Process Automation): Software bots that automate repetitive tasks by replicating user interface actions. RPA handles legacy EHR environments without API access, but bots require maintenance after EHR version upgrades.
