Time on prior authorization paperwork
Baseline measured for 30 days before Prescriber.AI deployment, then again at 90 days post-deployment, across MAs, RNs, and provider time.
Your virtual medical assistant — always available. Delegate coverage, prior authorization, financial assistance, and clinical research. Approve the work and get back to patients.
Tell Prescriber.AI what you'd like to prescribe. It does the work — you approve every action before it leaves your office.
Prescriber.AI is the first tool I’ve seen that handles the work — not just the questions.
Other tools help you find the answer. Prescriber.AI is the virtual medical assistant that does the work.
“Will Aetna cover this?” shouldn’t cost 20 minutes on the phone.
Phone trees. Formulary lookups. The same questions, asked twice.
Multiply by every drug, every plan, every patient — and your front desk is doing this all day instead of seeing patients. Coverage rules shift weekly. The right answer this morning is the wrong one this afternoon.
23 min avg per patient on coverage research — industry benchmark
Stop filling forms. Submit prior auths in one conversation.
Forms. Faxes. Appeals. Denials. 14-day waits per drug.
Every PA is a question set the payer designed and your office has to answer — pulled from the chart by hand, typed into a portal, faxed, followed up on. Patients wait without therapy while paperwork moves.
14 days median time-to-decision per PA — national average
When the PA comes back denied, the work isn’t done. It just got harder.
Letters. Peer-to-peer calls. Appeal forms. Evidence packets. Every payer plays it differently.
Most biologic denials are reversible — but appeals require parsing the denial letter, gathering supplemental documentation, scheduling peer-to-peer, and drafting a custom letter for each plan. Your office runs out of bandwidth and most denials get dropped instead of fought.
~40% of biologic denials reversed on appeal — but only ~15% get appealed
Find every dollar of help your patient is entitled to.
Copay cards. PAPs. Foundations. Buried across hundreds of brand websites.
Financial assistance programs change weekly. Income thresholds, eligibility criteria, enrollment steps — all different. Most prescribers know one or two programs by reflex; the patient pays the rest in adherence.
~$500/mo avg potential savings missed per patient — estimate
Pull the literature in plain English. With citations.
Updated guidelines. Drug interactions. Comparative efficacy. Between encounters.
You don’t have 20 minutes to read a SURMOUNT-1 abstract between patients. But you do need to know: is this the right drug for this patient, and what does the literature say since the last time you checked?
~8 min avg search-to-answer for a clinical question — survey data
Every coverage check, prior auth, enrollment form, and clinical answer is drafted by Prescriber.AI and surfaced for your review. Nothing is submitted, sent, or filed until you approve it. Every action is logged and auditable.
We track three things across active practices. Live outcome data publishes at general availability.
Baseline measured for 30 days before Prescriber.AI deployment, then again at 90 days post-deployment, across MAs, RNs, and provider time.
Days from prescription decision to first-fill at pharmacy, measured against the practice's pre-Prescriber.AI baseline.
Time previously spent on coverage research, PA paperwork, and financial-assistance lookup — measured at the office level, not just per-provider.
Methodology and live data will publish in the trust center at GA. Design-partner case studies available on request.
Individual providers use Prescriber.AI free. Practices and health systems unlock the full suite.
Multi-site rollout, integration with your EHR, governance frameworks, and ROI modeling for your CIO and CMIO.
Your virtual medical assistant — free for verified US prescribers. No credit card.
Running a health system? Book a briefing.