Revenue leaks at the handoffs: between scheduling and eligibility, between the note and the code, between the remit and the ledger. The platform connects the stages, and an AI agent works each one with a person reviewing the exceptions.
Real time 270/271 checks at scheduling and again before the encounter, with coverage gaps and patient responsibility surfaced to the front desk. One practice cut 20 hours a week of verification calls to under one. Eligibility verification agent.
Detects which orders need authorization from payer rules, assembles the clinical evidence from the chart, submits, tracks and escalates. Turnaround from six days to under 24 hours in one deployment. Prior authorization automation.
Charges reconciled against the schedule and the documentation so nothing performed goes unbilled, including implants, drugs and time based services that generic systems drop. Charge capture agent.
ICD-10, CPT and HCPCS suggested from the note with confidence scores and documentation gap alerts, routed to a certified coder for sign off below threshold. 94% first pass acceptance on medical to dental cross coding. Medical coding agent.
Payer specific edits applied before the 837 leaves, rejections corrected and resubmitted the same day, status tracked through 276/277 so nothing sits unworked. Claim rejection rate held at 6% in one build. Claims processing AI.
Denials categorised by root cause, prioritised by recoverable value and likelihood of overturn, appeal letters drafted with the payer's own policy cited, and the cause fed back to prevention. Denial management automation.
835 remits posted automatically, every paid line compared to the contracted rate, variances flagged and appealed. $200K in underpayments found for one group with document AI. Underpayment recovery agent.
Accurate estimates before the visit, statements and payment plans that patients actually respond to, and outreach by text and voice that books a payment instead of leaving a voicemail. AI voice agent.
Six deployments, six published case studies. Each card links to the full write up.
See all case studiesFour very different ways to run a revenue cycle get sold under the same three letters. Here is what each one actually does with a denied claim, and what it costs you as you grow.
Charge entry, claim generation, scrubbing against basic edits, submission and payment posting. It covers the back half of the cycle and leaves eligibility, authorization, denial prevention and analytics to people. Fine for a small practice with a strong biller. Not a revenue cycle.
Eligibility through collections in one product, usually bundled with or bolted onto a PMS. Broad coverage, vendor maintained payer rules, and analytics. Customisation stops at configuration, your specialty is one of thirty it serves, and pricing is per provider or a percentage of collections that rises with your revenue.
You hand the cycle to a service company for four to nine percent of collections. Headcount and expertise on day one, no software to run. You also lose visibility into why claims fail, the incentive to prevent denials sits with you rather than them, and the fee grows with every dollar you collect.
A coding tool here, a denial tool there, an eligibility bot from a third vendor. Each is good at its stage and none of them sees the whole claim journey, so the handoffs where most leakage happens stay manual, and you now integrate and reconcile four systems.
Built around your payer mix, your specialties and the PMS or EHR you already run, with an AI agent working each stage and a person reviewing exceptions. Every step sees the full claim journey, so prevention actually happens. You own the code and the models. No per claim fees, no percentage of collections, so the cost does not rise when your revenue does.
Below roughly two million dollars in annual collections, or with a single specialty and a clean payer mix, a good billing product plus a strong biller is usually the right answer and we will say so. The platform pays off where volume, specialty complexity and payer variety make the handoffs expensive.
Four steps, each ending in a number you can check. Hover or tap a step to see what happens in it.
We take two to three years of your 837s, 835s and denial history and find where the money is actually leaking: which payers, which codes, which stages, which sites. You get a written revenue leakage report with the dollar value of each problem before anything is designed. Sometimes the report says the platform is not worth it yet.
The platform is only as good as its payer rules and its connections. We encode your payer contracts, medical policies and edits into a rules engine your billing team can maintain, and connect to your PMS or EHR, your clearinghouse and your payment processor. Integrations are the largest line item and the first thing built.
Each agent runs against live volume while your team still makes the decision, so you see its accuracy against theirs before anything is at stake. Confidence thresholds are approved by your revenue cycle director in writing. Eligibility and claim scrubbing usually go first because the results show within a billing cycle.
Days in A/R, clean claim rate, first pass resolution, denial rate and cost to collect tracked from day one against the baseline from discovery. As accuracy holds, agents take on more. Your team owns the rules engine and the thresholds, so the platform keeps improving after we step back. You own the code either way.
A revenue cycle platform is an integration project with a rules engine on top. These are the transaction sets, clearinghouses and systems we connect to, so claims, remits and eligibility responses flow without anyone rekeying them.
The HIPAA mandated formats every payer speaks. Generated, validated and parsed natively rather than through a spreadsheet export.
Direct connections where the payer supports them, clearinghouse routing everywhere else, and payer portals automated where nothing else exists.
The platform reads the schedule, the encounter and the charges from the system you already run, and writes status back to it. No double entry.
Where the money actually lands, and the controls that let a finance team and an auditor trust the numbers.
A clearinghouse or PMS not listed here is scoped in discovery before anything is quoted. The integration inventory is what sets the price, so it is the first thing we do.
Revenue cycle software that cannot show you these six on one screen, by payer and by site, is billing software. Here is what each one means and the range well run organisations work to.
Total accounts receivable divided by average daily charges. Well run practices work to under 40 days; under 30 is strong. The platform tracks it by payer so you can see which one is holding your money. Two of our deployments took it from 60 to 15 and from 52 to 18.
The share of claims that pass payer adjudication without rejection or correction. Leaders work to 95% and above. Every percentage point below that is rework your team is doing by hand. Scrubbing against payer specific edits before submission is what moves it.
Stricter than clean claim rate: paid, not just accepted. Strong organisations reach 90% and above. Eligibility errors and authorization gaps are the two biggest reasons claims fail this test, which is why those agents go live first.
Industry wide it has been drifting upward for years and double digits is common. Well run groups hold it under 5%. The platform categorises every denial by root cause and payer, so the fix goes into prevention rather than into another appeal queue.
Payments received divided by allowed charges after contractual adjustments. The honest measure of leakage. Leaders work to 95% and above. Underpayment detection against contracted rates is where the gap usually hides. One of our DSO deployments runs at 98%.
Total revenue cycle cost divided by collections, usually between two and four percent for efficient organisations and well above that where the cycle is manual. This is the number that decides whether automation paid for itself, so the platform reports it against the discovery baseline every month.
Every setting has its own payer mix and its own place where the money leaks.
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Software that manages every step between a patient scheduling an appointment and the final payment landing in your account: eligibility and benefits verification, prior authorization, charge capture, coding, claim scrubbing and submission, payment posting, denial management, underpayment recovery, patient statements and collections, with analytics across all of it. The distinction from medical billing software is scope: billing software creates and submits claims; RCM software runs the whole cycle and, done well, prevents the failures rather than working them afterwards.
Medical billing software covers the back half of the cycle: charge entry, claim generation, basic scrubbing, submission and payment posting. It leaves eligibility, authorization, denial prevention and financial analytics to people. RCM software covers the front end and the middle as well, so an eligibility problem is caught at scheduling rather than as a denial six weeks later. Most revenue leakage happens at the handoffs between stages, which billing software never sees.
In production, six things: verifies eligibility and benefits in real time, detects and assembles prior authorizations from payer rules and the chart, suggests codes from the note with confidence scores for a coder to approve, scrubs claims against payer specific edits, categorises denials by root cause and drafts appeals citing the payer's own policy, and compares every remit to the contracted rate to find underpayments. Each is an agent with a confidence threshold your revenue cycle director approves; below it, a person decides. All six are agents we run in production.
Usually not. The platform reads the schedule, encounters and charges from the PMS or EHR you already run, connects to your clearinghouse, and writes status back. Your team keeps working in the screens they know while the agents work the stages around them. Where an existing billing system is the problem rather than the process, we will say so and scope the replacement, but that is the exception.
Epic, Oracle Health, athenahealth, eClinicalWorks and NextGen on the PMS and EHR side through HL7 v2 and FHIR R4; Availity, Optum, Change Healthcare and Waystar as clearinghouses, plus direct payer APIs and portal automation where that is all a payer offers; Stripe and card processors for patient payments. We generate and parse X12 837, 835, 270/271, 276/277 and 278 natively. A system not on that list is scoped in discovery before anything is quoted.
Software you own, built to your payer mix and specialties, with agents doing work a service company would staff. An outsourced RCM service charges four to nine percent of collections and keeps the visibility into why claims fail; the platform costs a build plus a monthly figure for hosting, models and support, and the fee does not rise when your revenue does. For groups above roughly two million dollars in annual collections the arithmetic usually favours owning it. Below that, we will often tell you to buy a billing product and hire a strong biller.
A discovery on your own claims data is a fixed fee and ends in a revenue leakage report with dollar values. The build is quoted as a fixed price after that, because by then the payer mix, the integration count and the agent scope are known. Integrations and the payer rules engine are the largest lines. Ongoing cost is a monthly figure for hosting, model usage, monitoring and support, never a percentage of collections or a per claim fee. The business case is built on your own leakage numbers before you commit.
Discovery runs two to three weeks. Integrations and the rules engine four to eight. Each agent then runs in shadow for two to four weeks before acting alone. A first stage, usually eligibility or claim scrubbing, is typically live and measurable within a billing cycle of the integrations finishing; the full cycle across a multi site group takes five to eight months. Results show stage by stage rather than all at once at the end.
Every decision has a confidence threshold approved in writing by your revenue cycle director: act alone above it, route to a person below it, never automate certain decisions at all. Before go live each agent runs in shadow while your team still decides, so you see its accuracy against theirs with nothing at stake. In production every action is logged with its reasoning and every claim has an immutable audit trail. Thresholds only widen as measured accuracy holds.
Yes, that is where the platform earns its cost. Specialty coding rules, payer contracts and documentation requirements are configured per specialty and per site inside one platform, with one view of the claim journey and group level reporting on top. A five location DSO in our case studies runs at a 98% collection rate on a unified cycle, and a twenty five location group moved from twenty five billing operations to one.
From our published case studies: a 98% collection rate with $275K recovered and days in A/R down to 18 for a DSO; reimbursement from 60 to 15 days with $150K recovered from denials; 20 hours a week of eligibility calls cut to under one with $87K in prevented denials; prior authorization from six days to under 24 hours with $210K protected; $200K in underpayments found. Your numbers depend on your baseline, which is exactly what discovery measures before you commit.
You do. Full source code, models, rules engine and documentation transfer at project close. No per claim fees, no percentage of collections, no dependency on us to keep it running. Support and continued development are available on a monthly agreement if you want them, and are not a condition of ownership.
Send us a year of 835s and your denial report under NDA. In two weeks you get a revenue leakage analysis with a dollar figure on every problem, by payer and by stage. If the number does not justify a platform, we will tell you what to fix instead. Working one stage at a time? Start with denial management automation or prior authorization automation.
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