Medicine Recommendation AI · A LeapHealth AI Agent

Suggest the drug, flag the risk, doctor decides.

For prescribers in busy OPD and IPD, it suggests guideline-based drug options and flags interactions and allergies before sign-off.

Book a Demo See how it works

The problem

What Medicine Recommendation AI removes from your team.

Interactions slip through.

A patient on three existing drugs gets a fourth at a packed OPD, and a contraindicated combination is only caught when the pharmacy queries it.

Allergies buried in notes.

A documented penicillin allergy sits two visits back in the record, so the prescriber writes the drug and the alert never surfaces in time.

Formulary drifts.

The hospital formulary and preferred brands exist in Leap OS, but during a rush the doctor writes from habit, and procurement sees off-list drugs.

Scope of work

Tasks Medicine Recommendation AI takes over from your team.

The repetitive human moments this agent absorbs — so prescribers focus on the work that needs a person.

Read

Pull medication history Read recorded allergies Check active vitals Load formulary list

Suggest

Offer guideline options Match formulary brand Propose dose by weight Note renal adjustment

Flag

Mark drug interaction Surface allergy conflict Warn on dosage Highlight duplicate therapy

Hands off to a human when any interaction, allergy conflict, dosage warning, or off-formulary case is held and routed to the prescriber for the final call.

How it works

Four capabilities, one agent.

Suggests drug options.

Reads the diagnosis and history, then offers guideline-based drug choices mapped to your hospital formulary and preferred brands for the doctor to pick from.

Touches: Leap OS · EMR

Flags the conflicts.

Checks each proposed drug against recorded allergies, current medications, and dosage limits, surfacing interactions and contraindications on the screen before sign-off.

Touches: Leap OS · EMR

Keeps to formulary.

Steers suggestions toward in-formulary drugs and flags off-list choices, so procurement and pharmacy stock stay aligned with what gets prescribed.

Touches: Leap OS

Waits for the doctor.

Every suggestion and flag is advisory. Nothing is added to a prescription until the prescriber selects it, reviews the warnings, and signs.

Touches: Leap OS · WhatsApp

Before vs After

What changes when Medicine Recommendation AI is in the loop.

Before LeapHealth

With Medicine Recommendation AI

Prescriber writes a fourth drug without seeing the interaction.

The interaction is flagged on screen before the doctor signs.

A penicillin allergy two visits back goes unnoticed.

The recorded allergy surfaces the moment that drug is proposed.

Pharmacy phones back to query a contraindicated combination.

The combination is caught at prescribing, so the script arrives clean.

Off-formulary brands creep in and procurement chases stock.

Suggestions favour formulary drugs and off-list picks are flagged.

Customer outcome

It checks the patient's allergies and current drugs faster than I can scroll the history, and shows me the interaction before I sign. I still choose every drug myself.

Medical Director · Multi-speciality hospital, Pune · Illustrative

Get in touch

See it check against your formulary.

Bring a few anonymised cases on your own formulary and watch it suggest options and flag conflicts. Tell us what you need; our team responds within one business day.

Submit Inquiry & Schedule Call

One-business-day response

No per-message charges

Volume tiers for chains

Real call, real numbers

FAQ

Common questions before a demo.

How long until it is running in our OPD?

Most centres go live in two to three weeks. We load your formulary, preferred brands, and interaction rules, connect to Leap OS, and run a supervised pilot with a small group of prescribers first.

Does it work with our formulary and existing EMR?

Yes. It reads medication history, allergies, and vitals from Leap OS and connects to your EMR through standard APIs. Suggestions map to your own formulary, and your sign-off flow stays the same.

Where does our patient and clinical data sit?

Data stays in India on AWS Mumbai. The setup is DPDPA-aligned, ISO 27001 certified, with role-based access and full audit logging on every suggestion, flag, and edit.

Can it handle prescribers working in regional languages?

Yes. It reads diagnoses and notes captured in English and major Indian languages, including mixed speech, and returns drug suggestions in your standard clinical format for review.

Will it ever prescribe on its own?

No. It only suggests and flags. Every drug is chosen and signed by the prescriber, and any interaction, allergy, or out-of-policy case is routed to the clinician rather than acted on.

Give your prescribers a second set of eyes.

See Medicine Recommendation AI suggest and flag against your own formulary and patient records, with your doctor in control. Real workflows, no slideware.

Book a Demo