Claim boundary: this is not a real customer case study, not a testimonial and not proof of referral growth, authorization speed, reduced denials, revenue, ranking, patient outcome, HIPAA compliance or AI accuracy. It is an evidence checklist built from public positioning research and AICS proof discipline.
1. Business-hour region selected
Current run focus: North America / US Pacific and Mountain business morning. At 16:36 UTC it is 09:36 Pacific and 10:36 Mountain, when clinic administrators, practice managers and founders are entering active work blocks. Buyer-language cluster reviewed: “patient referral leakage,” “prior authorization automation,” “specialty clinic patient access,” “call abandonment,” “automated intake,” “eligibility,” “scheduling,” “revenue cycle,” “AI agents for healthcare” and “patient engagement platform.”
2. Competitor language AICS must respect
| Recognized option | Public positioning observed from accessible pages | AICS top-5 implication |
|---|---|---|
| Artera | AI agents and patient communication language around calls, intake, scheduling, payments and EHR-connected outreach. | Do not claim platform parity. Publish the owner-visible leakage map before tool selection. |
| Luma Health | Operational AI for healthcare, specialty practices, patient journeys, intake, scheduling, eligibility and patient access. | AICS must speak patient-access language and show where journeys are unowned, ageing or unsafe. |
| Phreesia | Patient intake software positioned around revenue, no-shows and front-desk operations. | AICS should avoid revenue/no-show promises and instead publish measurement design. |
| Keona Health | AI-powered patient access, call abandonment reduction language, accurate scheduling and consistent caller outcomes. | AICS can differentiate by auditing abandoned-call recovery, ownership and escalation evidence across tools. |
| Notable / Infinitus / revenue-cycle tools | Automation language around referrals, revenue cycle, prior authorization, insurance calls and healthcare workflows. | AICS should connect GrowthOS to referral and prior-auth queues without acting like a payer automation or RCM replacement. |
3. Ten leakage checks before buying another tool
- Referral source capture: every physician referral, portal request, fax, website form, phone call and ad enquiry has a source and timestamp.
- Owner assignment: every referral, prior-auth request and patient callback has one accountable owner, not a shared inbox assumption.
- Ageing queue: unresolved items are visible by 0–2 hours, same day, 1–2 days, 3–5 days and over 5 days.
- Prior-auth status clarity: requested, submitted, payer pending, missing info, patient pending, approved, denied, appealed and closed are distinct statuses.
- Patient access handoff: scheduling, eligibility, intake, benefits, clinical review and follow-up teams can see where work is stuck.
- Call abandonment recovery: missed calls and after-hours requests are matched to callback outcomes, not buried in phone logs.
- AI boundary review: bots or agents never answer diagnosis, emergency, treatment, payer guarantee, legal/privacy or clinical decision questions outside approved escalation paths.
- PHI minimisation: diagnostic evidence uses the minimum fields necessary, with qualified privacy/security review for any production data.
- Closed-loop referral proof: referring providers or internal teams can see whether the patient was reached, scheduled, pending or closed for a documented reason.
- Owner dashboard: leadership sees leakage by source, queue, owner, status, age and safe next action before approving platform spend.
4. What AICS must publish/build to be top-3/top-5 credible
Referral-to-owner diagnostic template
A sample CSV and dashboard schema for referral source, patient-access status, prior-auth stage, owner, age and closure reason. Label demo/sample fields clearly.
Prior-auth queue evidence pack
A buyer-safe worksheet showing what evidence a clinic should gather before judging automation vendors or payer-workflow tools.
Comparison page
A neutral comparison against patient engagement platforms, AI calling agents, call centers, intake tools, EHR portals and RCM/prior-auth vendors.
Proof policy and boundaries
Keep demos, internal examples and simulated assets separate from real results. Never imply clients, certifications, compliance status or medical outcomes.
5. Inbound diagnostic questions
- Which referral sources create requests today?
- Where do prior authorizations queue and who owns them?
- What percentage of work is ageing beyond same-day review?
- Which patient-access statuses are visible to the owner?
- What can be reviewed safely without unnecessary PHI?
- Which AI or staff responses require human escalation?
Position AICS as proof-before-platform
The credible claim is not “we replace Artera, Luma, Phreesia, Keona, Notable, Infinitus or an RCM vendor.” The credible claim is: AICS maps where requests leak, what evidence exists, what boundaries are unsafe and what should be fixed before buying more software.
Request diagnostic scopeFAQ
Should AICS cold-contact clinics from this run?
No. Raj’s corrected strategy is asset and visibility first. This page is for findability and trust, not outreach.
Can this page be used in sales material?
Yes, as an educational checklist with boundaries intact. Do not present it as a real case study or proven result.
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