Prior auth, eligibility, and denials are leaking at every family medicine location.

Prior auth is the loudest leak in family medicine, and it is structural. Your EHR can submit a request, but it does not consistently integrate with the insurer's system. After submission, someone has to live in the payer portal, watch the status, and chase the ones that stall. Referrals, imaging, specialist visits, and branded medications each carry their own payer-specific form and approval window. Across multiple locations, the open requests run into the dozens at once.

The cost compounds quietly. An imaging order that goes out without auth means the radiologist gets paid and your group eats the denial. An auth-related denial is often winnable on appeal, but only if someone assembles the documentation inside the window, and your auth coordinator does not have the hours. Every week the backlog grows, and the leak grows with it. The AMA reports physicians average 39 prior auths weekly and spend 13 hours on the process. Six in ten practices involve at least three employees in a single PA request.

An AI employee monitors every open prior auth across every location, checks payer portal status daily, and flags the ones that have stalled past the expected decision window. When a denial comes back it drafts the appeal with the supporting clinical documentation pulled from the EHR, and it escalates the time-sensitive cases first into the coordinator's queue. The coordinator reviews and submits every one. Expired authorizations stop turning into write-offs, and the backlog becomes a managed dashboard instead of a stack of sticky notes.

Prior auth automation for multi-location family medicine groups works across athenaOne, eClinicalWorks, NextGen, and the rest of the stack your group already runs.

Most family medicine denials are born before the visit even happens. New patient paperwork arrives incomplete the day of the appointment, staff key demographics and insurance IDs into the PM by hand, and the provider walks into a room without a usable chart. Then the deeper problem: eligibility is checked at booking and not re-run at the time of service. Coverage that lapsed from a job change, an open-enrollment swap, or a Medicaid redetermination is still on file when the claim goes out. The denial lands 30 to 45 days later, and now it is rework, not prevention.

Front-end eligibility failures are a leading source of preventable claim denials in primary care. Redetermination waves produce mass eligibility changes no manual workflow can keep up with across a multi-location panel. Every failed claim costs staff time to rework and delays cash you already earned.

An AI employee sends the intake link the moment the appointment is booked, follows up by text if forms are not done 48 hours out, and cross-checks submitted insurance IDs against eligibility in real time. It re-runs eligibility on every patient 24 to 48 hours before the visit and flags any coverage change to the front desk before the claim is cut. When a Medicaid patient shows terminated, it drafts the patient outreach and a task for the billing coordinator to check for a secondary. Staff confirms every message and every corrected record. The front desk catches the dead coverage before the visit, not six weeks later when the denial arrives.

Front office automation for multi-location family medicine groups covers intake, insurance verification, and Medicaid eligibility across every site in one workflow.

Clean claims have to leave clean, and in a multi-location group they often do not. Different providers at different sites develop different coding habits, and the billing team cannot audit every encounter before it goes out. Coding errors, missing modifiers, wrong place-of-service codes, and bundling violations all bounce back as front-end rejections that delay cash by weeks. Worse than the rejection is the charge that was never created at all: a service rendered but no charge queued, a closed chart with no matching claim. That revenue does not bounce back; it simply never shows up at all.

Then denials arrive as a daily batch, and the team has to triage by payer, denial code, and dollar value, decide what is worth appealing, pull documentation, and beat the appeal deadline. Most payers enforce 90-day to 1-year timely-filing windows. Claims that miss the window are written off, not denied with appeal rights. Patient balances pile up too, and with high-deductible plans shifting more cost to patients, follow-up no one has time for becomes revenue no one collects.

An AI employee runs a pre-submission audit on every claim: checks E/M coding against documentation, flags unbundling risk, confirms place-of-service matches the rendering location, and reconciles closed encounters against created charges so rendered services with no charge surface for review. It ingests the daily denial file, categorizes each denial by root cause, ranks by dollar value and appeal probability, drafts the appeal with attached documentation, and works the patient-balance and AR-aging queues on a cadence you set. The billing coordinator approves every submission and every outreach batch. Denials get worked daily instead of at month-end, so fewer claims age past the filing window.

Back office automation for multi-location family medicine groups covers charge capture, claim scrubbing, denial management, and patient balance collection across every location in one view.

Every no-show at a multi-location group is a slot that cannot be backfilled by hand at scale. Family medicine carries high no-show rates, and the highest-cost cancellations are the high-complexity visits: Annual Wellness Visits, Chronic Care Management, Transitional Care Management. Those slots carry the highest reimbursement, and when they go empty the revenue is simply gone. Same-day walk-ins fill some gaps, but they tend to be lower-acuity visits, not the billable ones you lost.

Scheduling across sites adds its own trap: a patient booked with a provider not credentialed for their plan produces a claim that denies in full. No front desk can hold every provider-payer panel combination in their head across every location.

An AI employee monitors the schedule nightly, matches open slots against a waitlist sorted by visit type and insurance, and drafts fill-the-slot outreach to matched patients, prioritizing high-reimbursement visits. It cross-checks provider credentialing against the payer panel before confirming any booking. A staff member reviews the suggested fills each morning and confirms the rebooking. The outreach runs through your own comms tool, so your team is sending messages they reviewed, not messages the AI sent on its own.

Relay also handles call-overflow: inbound cancellation calls that come in after hours get logged and routed to the rebooking queue the next morning. High-value slots that would have gone empty get a second chance to fill.

Credentialing is the quietest revenue leak and the most expensive when it goes wrong. A lapsed CAQH attestation or an expired license silently freezes a provider's billable status, and you find out weeks later when the claims start denying. Across a multi-location group running employed physicians, advanced practice providers, and part-time coverage, the credentialing matrix lives on a spreadsheet someone has to remember to check. A provider who starts seeing patients before credentialing is complete produces claims that have to go under a supervising provider, which creates incident-to compliance risk.

CAQH attestation must be re-attested every 120 days. That is a recurring, hard deadline running in the background for every provider you employ. Missing it on even one provider at one payer freezes that revenue stream until someone notices.

An AI employee tracks credentialing and license expirations across every provider and location, watches the CAQH 120-day attestation cadence, and flags any provider within 30 to 90 days of a lapse to the practice manager. It drafts the renewal data and the payer-enrollment paperwork and presents it for provider signature. It works on top of CAQH, Medallion, or Modio, whichever your group already runs. The coordinator signs off on every renewal. Lapsed credentialing gets caught before it shows up as a denied claim, not after.

athenaOne is EHR, practice management, and RCM in one, and it still leaves real work on your team's plate: patient balance follow-up, referral coordination, and prior auth that tracks but does not proactively trigger renewal at visit-count caps. An AI employee works on top of athenaOne through its REST API and FHIR R4 layer, handling outbound patient-balance outreach, referral status tracking, and the prior-auth and denial queues, then surfacing finalized actions for staff to approve inside athenaOne. The connection runs through athenahealth's FHIR R4 layer updated for ONC HTI-1 Final Rule requirements, so there is no new system of record to stand up.

eCW's documented gaps are exactly where an AI employee earns its keep: the charge-capture gap where rendered services never become charges, a claim scrubber not pre-tuned to payer-specific rules, and prior-auth requirements not enforced at the claim level. An AI employee works on top of eCW to reconcile closed encounters against created charges, pre-audit claims against payer rules before they leave, and track auth status the platform does not surface, handing each flagged item to a staff member to finalize. The billing-side connection uses HL7 v2 DFT/ADT messages because eCW's FHIR R4 endpoints do not expose insurance, claims, or authorization data directly.

NextGen is common in mid-size to enterprise ambulatory groups and runs a tighter API ecosystem than its peers, which is precisely why bolt-on AI tools struggle here. An AI employee works on top of NextGen through its documented FHIR R4 and HL7 layer to handle the prior-auth, denial, and intake queues the platform leaves to staff, without requiring you to swap systems or buy more NextGen modules.

Veradigm (formerly Allscripts) and Elation Health are both common in independent and small-to-mid family medicine groups. Veradigm ranked number one for family practice and primary care ambulatory EHR by Black Book Research in 2025; Elation earned Best in KLAS 2026 for small ambulatory. An AI employee works on top of either, handling the prior-auth, eligibility, and denial queues the platform surfaces and leaves to your staff.

Your clearinghouse moves claims and eligibility. It does not work the queue it surfaces. Waystar automates clean-claim submission and rule-based denials. Availity returns eligibility and runs PA. Office Ally moves claims without much of a denial workflow at all. An AI employee works on top of whichever you run: it reads rejection and denial reports, classifies by root cause, drafts corrected claims and appeals with documentation, and routes them for one-click staff submission. The clearinghouse stays the pipe it has always been, while the AI works the exceptions it surfaces but never clears.

CoverMyMeds is the largest electronic PA channel for prescription drugs, integrated with more than 350 EHRs. pVerify runs real-time multi-payer eligibility via API. Both surface data. Neither chases the stalled request or acts on the deductible gap. An AI employee monitors CoverMyMeds PA status, flags requests past the decision window, drafts payer follow-ups, and calls pVerify to batch-check tomorrow's schedule and surface the patients who need front-desk attention. Staff reviews every flag.

Comms tools like Weave and Solutionreach send the scheduled reminders and recall touches. They do not route the inbound responses or work the unscheduled replies. Credentialing tools like CAQH, Medallion, and Modio store provider data and surface expiration alerts. They do not chase the missing document or draft the renewal. An AI employee handles the inbound side of comms and the action side of credentialing, queuing each for the right staff member to approve.

No. Relay is not an EHR. Our AI employees work on top of the EHR your family medicine group already runs, whether that is athenaOne, eClinicalWorks, NextGen, Veradigm, or another, reading what it surfaces and acting on the work it leaves to your staff. Nothing gets ripped out or replaced.

An AI employee monitors every open prior auth across all your sites in one queue, checks payer portal status daily, drafts appeals with documentation from the EHR when a denial comes back, and escalates urgent cases first. Your auth coordinator reviews and submits every request. The AMA's 2024 Prior Authorization Physician Survey reports physicians average 39 prior auths a week and spend 13 hours on the process. This is the work the AI takes off your team, with staff finalizing every submission.

No. Every workflow is human-in-the-loop. The AI employee does the watching, chasing, and drafting, then hands the finished claim, appeal, or outreach to a staff member to approve. Nothing is submitted autonomously. Staff finalizes every action.

Yes. The AI re-runs eligibility on every patient 24 to 48 hours before the visit and flags any coverage change to the front desk before the claim goes out, whether a lapsed commercial plan, a Medicaid redetermination, or an open-enrollment swap. Front-end eligibility failures are a leading, largely preventable source of primary care denials. Catching them before the visit stops the rework entirely.

The AI employee connects through athenaOne's REST API and FHIR R4 layer to work the patient-balance, referral, prior-auth, and denial queues athenaOne tracks but leaves to your staff. Finalized actions surface inside athenaOne for your team to approve. You keep athenaOne exactly as it is. Family medicine practice automation on athenaOne does not require a new system of record.

eCW has a documented charge-capture gap where rendered services never become charges. The AI employee reconciles closed encounters against created charges, flags any service with no matching charge, and queues it for your billing coordinator to review. The revenue you earned stops disappearing into the gap between charting and billing.

Yes. The AI tracks credentialing and license expirations across every provider, location, and payer, watches the CAQH 120-day attestation cadence, and flags any provider within 30 to 90 days of a lapse. It works on top of CAQH, Medallion, or Modio. Your coordinator signs off on every renewal.

The AI monitors the schedule nightly, matches open slots to a waitlist sorted by visit type and insurance, and drafts fill-the-slot outreach to matched patients, prioritizing high-reimbursement visits like Annual Wellness Visits, Chronic Care Management, and Transitional Care Management. It cross-checks provider credentialing against the payer panel first. Your front desk confirms every rebooking. Outreach runs through your own comms tool.

The first two to three weeks are discovery: working sessions with your team, mapping the operation across every location, and identifying the highest-value leaks to address first. Builds run eight to twelve weeks from discovery to live. The timeline depends on the number of workflows, locations, and integrations in scope.

It is an ongoing monthly service. We build AI employees custom to your stack and your workflows during the discovery period, then run and maintain them for a recurring monthly fee. There is no one-time build and no separate system you have to run or maintain. Family medicine group practice automation built this way stays current with your payer rules, your staff changes, and your EHR updates.

Start with a free 30-minute intro call. The first few weeks are discovery: we run working sessions with your team, map your operation across every location, and show you exactly where prior auth, eligibility, denials, and no-shows are costing you. That map is what tells us what to build first. There is no audit fee and no commitment to proceed.