Documentation happens after everything else
Discharge summaries pile up behind the clinical day. Coding waits on the summary, billing waits on the coding, and a bed that could have turned over is held while a document is drafted.
Documentation that keeps up with the clinic, claims that leave complete, and a front desk that answers on the first ring.
Clinical documentation, patient triage assistants and back-office automation.
The clinical work is not the bottleneck in most hospitals — the paperwork around it is. Discharge summaries are written after the ward round, coding waits for the summary, the claim waits for the coding, and the TPA queries what was missing three weeks later. Meanwhile the front desk absorbs appointment calls, report requests and insurance questions with the same headcount it had before the OP volume grew.
We work strictly on the administrative and documentation layer, and we design for a clinician to sign everything that touches care. A drafting assistant that pre-fills a discharge summary from the HIS fields, the medication chart and the investigation results is a time saver with a human decision at the end of it. A model that decides is a different product with a different regulatory weight, and we say so before the engagement starts.
The second front is flow. OP waiting time is a function of scheduling, consultant punctuality, walk-in ratio and investigation turnaround — all measurable from systems already in place, and all improvable without buying anything new. Bed occupancy, average length of stay and discharge timing respond to the same treatment.
Named the way your operators name them, not the way a vendor deck names them. If none of these land, we are the wrong partner for this problem.
Discharge summaries pile up behind the clinical day. Coding waits on the summary, billing waits on the coding, and a bed that could have turned over is held while a document is drafted.
No-shows, walk-ins and a consultant running late compound through the session. The waiting hall becomes the only real indicator, and it is a lagging one.
TPA and payer queries land weeks after discharge, usually for a missing investigation note, an unmatched code or an incomplete pre-authorisation trail. The reconstruction costs more than the original entry would have.
Appointments, report status, insurance eligibility, department directions and follow-up reminders all arrive on the same counter and the same phone line, during the same peak hours.
Ordered the way we would sequence them in a healthcare engagement. Each one links to the capability behind it.
A draft summary assembled from the HIS record, medication chart, investigation results and the clinician's own dictation, in the format your department already uses. The clinician edits and signs; nothing is filed without that signature.
Every file checked against the payer's documentation requirements before it leaves — pre-authorisation trail, investigation notes, code and procedure consistency — so queries are answered before they are raised.
Appointment booking, rescheduling, report status and department guidance handled in the patient's language, around the clock, writing straight into the HIS. Anything clinical is handed to a human immediately.
Structured symptom and history capture before the consultation, and routing to the right clinic or department. It organises information for a clinician — it does not diagnose, triage acuity or advise a patient.
Nursing protocols, NABH standard operating procedures, formulary notes, tariff and package rules answered from your own approved documents with the source cited, instead of from memory at the counter.
A single queue that shows where every patient episode is stuck — sample pending, report unverified, summary undrafted, claim unsubmitted — built over your existing systems through HL7 and FHIR interfaces.
Read-only to begin with, write access only where a workflow needs it, and every integration documented before it goes near production.
These are targets and mechanisms, not results borrowed from somebody else’s project. We baseline each one on your data in the first fortnight, and report against that baseline monthly.
Hours from discharge order to a signed summary. Reported alongside clinician edit rate, so speed cannot be bought with a worse draft.
Share of claims accepted without a documentation query. This is where completeness checks either pay for themselves or do not.
Averages hide the sessions patients complain about. The tail is the number worth moving.
Share of routine contact resolved without a person, and the abandonment rate on what remains.
Patient data carries a higher duty of care regardless of category labels. Deployments sit inside your network or a dedicated tenancy, access is role-bound and logged, and de-identified copies are used for evaluation work.
We build drafting, retrieval and workflow tools. We do not build systems that make clinical decisions, and we will not present one as if it does. Where a use case would cross into diagnosis or triage acuity, that is a regulated device conversation and we say so at scoping.
Anything that produces a record kept for accreditation needs to show who authored it, who approved it and what changed. Version history and approval trails are part of the build, not a later request.
For teleradiology, transcription or any workload touching overseas patients, we scope data residency, business associate style contractual terms and encryption controls to the standard the receiving jurisdiction expects, and keep processing in-country where that is the safer answer.
This is how we scope and build, not legal advice. Your compliance, risk and legal teams stay the authority on what applies to your organisation, and we work to their reading of it.
Take one department with a documentation backlog — general medicine or orthopaedics usually — and build discharge summary drafting against its real records. Six weeks, measured on turnaround time and on how much the clinician changes in the draft. Both numbers have to be good; a fast draft that gets rewritten has saved nobody anything.
We sit with your operators, map the workflows, and score every candidate use case on value, data readiness and risk. You leave with a ranked backlog and a cost model.
We build the single highest-value agent against your real data and measure it against the humans doing that job today. If the number is not there, we say so.
Describe how healthcare works in your organisation — the systems, the constraints, the part that goes wrong every week. We will tell you whether it is worth automating and what the first project would cost.