Healthcare
In healthcare software, a defect in production isn't a bug. It's a patient who receives the wrong information at the wrong moment.
We validate clinical systems, patient portals, pharmacy platforms, and billing infrastructure against real healthcare workflows — before they reach patients and clinicians.
Talk to the founderWhy this sector is different
TGA obligations, patient safety, and privacy — simultaneously.
Healthcare software operates under regulatory and clinical accountability that most industries never encounter. A defect doesn't just frustrate a user — it can delay treatment, surface someone else's medical record, or trigger a mandatory TGA incident report that takes months to close.
Automated testing validates code paths. It cannot replicate the clinical judgment required to verify that a prescribing workflow correctly enforces drug interaction rules, that a patient portal handles privacy edge cases, or that a billing upgrade correctly maps every Medicare item number under the new schedule.
TGA & regulatory compliance
Software used in clinical decision-making may be classified as a medical device under TGA regulations. UAT must validate that the software behaves correctly across the clinical scenarios regulators expect — not just the ones developers anticipated.
Patient safety at stake
When healthcare platforms fail, the consequences can be immediate and irreversible. Incorrect dosage calculations, missing drug interaction checks, and misdirected referrals are not recoverable with a hotfix — they require clinical incident response.
Privacy Act obligations
Health information is among the most sensitive data a system can hold. UAT must verify not just that records are accessible to authorised clinicians, but that they are never accessible to anyone else — including through edge cases no one thought to test.
What we validate
Every layer of healthcare software.
Clinical systems & EMRs
Medication management workflows, dosage calculation rules, drug interaction checking, clinical decision support alerts, and order entry validated against actual clinical protocols — not just technical specifications.
Patient portals
Appointment booking, results delivery, clinical document access, secure messaging, and self-service record management tested across the full range of patient scenarios, devices, and access patterns.
Pharmacy platforms
Dispensing workflows, drug interaction checks across dispensing locations, controlled substance handling, real-time PBS claim submission, and pharmacist override scenarios validated end-to-end.
Billing & Medicare
Bulk billing workflows, item number mapping, telehealth claim rules, DVA billing, gap payments, and rejection handling tested against current Medicare Benefits Schedule rules and edge cases.
Referral & care coordination
Referral generation, patient record association, document routing to specialists, and pathology or imaging order workflows validated for data accuracy, privacy, and clinical completeness.
Compliance & audit reporting
TGA incident reporting workflows, mandatory breach notification processes, access audit logs, and clinical record completeness validated for accuracy and regulatory sufficiency.
What we find
This is what automated testing misses.
Real scenarios our specialists have caught in healthcare UAT engagements.
A medication dosage field accepts decimal values in testing but rounds to the nearest integer in production — clinicians are presented with incorrect dosage recommendations without any system warning.
Appointment booking confirms a time slot to the patient but fails to write to the scheduling system under concurrent load — patients arrive for appointments that don't exist in the clinical record.
Drug interaction checking runs correctly for single-pharmacy dispensing but silently skips the check when a patient's medication history spans multiple dispensing locations — contraindicated medications are dispensed without alert.
Bulk billing claims submit correctly for standard consultations but drop the item number for telehealth services added in a recent update — rejected claims aren't surfaced until the monthly reconciliation run.
Referral letters generated by the system include the correct patient name but pull pathology results from the previously viewed patient record — sensitive data is included in the wrong referral document.
Access logs correctly record logins and record views, but fail to capture records accessed via the bulk export function — a full audit trail is unavailable for the exported records.
The case for human UAT
Healthcare software must be correct before it reaches a patient — not approximately correct, and not correct only in the test environment.
The clinical intent behind a prescribing workflow, the privacy obligations in a patient portal, the compliance expectations of the TGA — these require human testers who understand the context, not just the code. That's what Bugwolf provides.
Platforms commonly used in healthcare
Healthcare release coming up?
Talk to Ash before you flip the switch. 13 years of enterprise UAT — and zero failed go-lives on our watch.
Talk to the founder