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Industry — Healthcare
Healthcare software fails in a specific way: it works clinically and collapses administratively, or the reverse. The systems worth building respect that a doctor has ninety seconds, a front desk has a queue, and a patient record is legally sensitive from the moment it is created.
What we hear
Four problems that come up in almost every conversation in this sector. If none of these sound familiar, the rest of this page probably is not for you.
Problem 01
Registration takes them, the consultation form takes them again, the lab request repeats them and billing asks once more. Every repetition is a chance to introduce a mismatch that later makes two records look like two patients.
Problem 02
Outpatient, laboratory, radiology, pharmacy and billing frequently run on separate systems chosen at separate times. Results reach the clinician as printouts, and follow-up depends on somebody remembering.
Problem 03
Shared logins at a nursing station or a reception desk make every subsequent access log meaningless. When a question is asked about who read a record, the honest answer is that nobody can say.
Problem 04
Consent for treatment, for data sharing and for contact is collected and filed. It is rarely queryable, so the systems that send reminders or share records cannot check it before acting.
The other side of it
A single patient record with a deliberate matching and merge process, including a reviewable merge history. Duplicate records are a clinical safety issue, not just a data-quality annoyance.
HL7 v2 messaging where the installed base requires it and FHIR resources where the counterpart supports them, so integrations survive the next system replacement rather than being rebuilt.
Role-based permissions with named accounts, break-glass access that is allowed but recorded and reviewed, and an audit log that is written for every read as well as every write.
Discharge summary drafting, coding assistance, appointment triage and document extraction are useful and reviewable. Anything touching diagnosis needs clinical governance, validation and a named accountable clinician before it goes near a patient.
What we build
Healthcare systems earn their place by removing repetition without adding risk. Each of the following is built so that the fastest path through the interface is also the correct one, because a workflow that is slower than the paper it replaces will be worked around.
Patient search that finds the existing record before it offers to create a new one, appointment booking with real capacity rules, and a queue display that tells waiting patients something true. Duplicate prevention at registration is cheaper than duplicate merging later.
Booking, identity verification, consultation, prescription and follow-up as one recorded sequence rather than a video call bolted onto a website. Patients see their own history, reports and prescriptions, which reduces the calls that ask for them.
FHIR resources where the counterpart system supports them, HL7 v2 messaging through an interface engine where the installed base requires it, and a normalising integration layer where only file exchange is available. Fragility is concentrated in one replaceable component.
Orders that flow to the laboratory and return as structured results attached to the encounter, not as a printout. Pharmacy dispensing linked to the prescription, with stock movement and batch and expiry tracking behind it.
Document extraction from scanned reports and insurance paperwork, discharge summary drafting for clinician review, coding assistance and appointment triage. Every one of these produces a draft that a person approves. None of them acts alone.
Consent captured as structured, queryable, revocable data so that any system about to send a reminder or share a record can check it first. Named accounts, least-privilege roles, recorded break-glass access, and an audit log that covers reads as well as writes.
Transaction level
The same encounter as most hospital systems handle it, annotated with the data that has to exist for the next step to avoid asking the patient again. Where a step is missing its capture, somebody downstream retypes something.
Search before create, with fuzzy matching on name, phone and date of birth. A near match is presented for a human to confirm rather than silently merged or silently duplicated.
Recorded here
Consent for treatment, for data sharing and for contact recorded as separate, revocable records with scope and expiry. Every later automated action checks them.
Recorded here
The consultation record, structured enough to be queried and free enough to be written in ninety seconds. Templates per specialty rather than one universal form nobody fits.
Recorded here
Lab, imaging or pharmacy orders raised from the encounter, carrying the patient and clinician context so nothing is re-entered at the receiving department.
Recorded here
Structured results returned against the order and the encounter, with abnormal values flagged and an acknowledgement recorded when the clinician has seen them.
Recorded here
Billing assembled from what was actually ordered and delivered, with insurance or scheme documentation generated from the same records rather than compiled separately.
Recorded here
Step two is the one most often skipped. Consent held on paper cannot be checked by a reminder service at two in the morning, so either the reminder goes out unchecked or the feature is abandoned. Structuring consent early is what makes later automation legitimate.
Constraints
New healthcare software almost never arrives in an empty room. These are the constraints that shape what is realistic, and the ones we raise before an estimate rather than after.
Where to go next
The services below are the ones this sector draws on most. Case studies are published only with written client permission, and none are published for this sector yet. Ask us in a call and we will tell you plainly what we have and have not done.
Service
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Solution
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Questions
Through choices that are made at design time and cannot be added later: encryption in transit and at rest, named individual accounts with role-based permissions, least privilege by default, and an audit log covering reads as well as writes. Environments are separated so production data never reaches a developer laptop, and test data is synthetic or de-identified. Retention and deletion behaviour is specified up front rather than discovered when someone asks for their data to be removed.
We build to the obligations the client's legal or compliance advisor confirms. In practice the DPDP Act pushes specific engineering requirements: recorded and revocable consent, purpose limitation reflected in access rules, breach notification capability, and the ability to produce or erase a data subject's records on request. Those are design constraints we implement. We are engineers, not your compliance counsel, and we will say so rather than imply a certification we do not hold.
Usually, and the method depends on what the incumbent exposes. In order of preference: a documented FHIR or REST API, HL7 v2 messaging over an interface engine, a vendor-supported database view, or a scheduled file exchange. Where only file exchange exists we build an integration layer that normalises and validates, so the fragility stays in one replaceable component instead of spreading through the new system.
Video is the easy part. The parts that need care are identity verification before a consultation, the consultation record itself, prescription generation with the practitioner's registration details, and the audit trail linking all three. Telemedicine practice guidelines also constrain what may be prescribed remotely, which is a rules question to settle with the client's clinical leadership before the workflow is built.
It depends entirely on where it sits. Administrative uses such as drafting a discharge summary, extracting values from a scanned report, or routing an appointment request are reviewable by a human before anything happens, and are a reasonable place to start. Anything that influences diagnosis or treatment is a different category requiring clinical validation, a named accountable clinician, monitoring of real-world performance and an explicit escalation path. We will build the first category readily and will insist on that governance before touching the second.
The most useful first conversation is not about scope or budget. It is walking through one process end to end with somebody who does it every day, and finding out where the data stops being trustworthy.
What happens next
