What the hospital was dealing with
Metro Multi-Specialty Hospital was running three disconnected legacy MIS systems — one for appointments, one for billing, and one for pharmacy stock. Receptionists duplicated entries manually between all three systems, adding 12–18 minutes to every patient registration.
Pharmacy stockouts were a weekly occurrence because prescription logs from IPD wards were not reconciled with stock deduction systems. Ward nurses handwrote prescriptions on paper, which clerks then manually re-entered into the discharge system — creating a 3–5 hour discharge delay per patient and introducing frequent transcription errors.
The hospital's finance team could only generate billing reports manually, once per day, making revenue leakage detection impossible in real-time.
How Goolk AI approached it
Goolk AI deployed a unified Hospital Information System (HIS) built on an HL7 FHIR-native shared data layer — replacing all three legacy systems with a single source of truth.
Front Desk: Digital check-in kiosks with QR-code patient identification. All appointment data flows automatically to billing the moment a patient checks in.
Pharmacy Integration: Barcode scanners at pharmacy dispensing counters automatically deduct inventory at the moment prescriptions are processed, with stock alert thresholds triggering auto-reorder notifications.
Ward & Discharge: Nurses received tablet workstations with pre-populated prescription templates pulled directly from doctor orders. Discharge summaries are auto-assembled from ward notes, removing 2.2 hours of daily transcription per nurse.
Finance Dashboard: Real-time billing capture dashboard visible to the CFO and billing head, showing department-wise revenue, pending collections, and unbilled procedures in real time.
Measured results at 90 days
At 90 days post go-live, baseline metrics were remeasured against our pre-deployment audit. Results exceeded projected targets:
Patient billing queue wait time dropped from 42 minutes to under 8 minutes. OPD daily throughput increased by 34% because the time previously spent on manual data entry was recovered. Billing leakage from unlogged ward procedures was completely eliminated. Ward nurses reported saving an average of 2.2 hours per shift.
The system passed NABH documentation review within 6 weeks of go-live, and the hospital's EMR is now ABDM-registered for National Health ID linkage.
ROI calculated from billing leakage elimination + 2.2 hrs/nurse/shift savings across 24 nursing staff.
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What we built it with
How we delivered it
On-site discovery & shadowing
Shadowed nurses, ward clerks, billing executives, and pharmacy staff. Mapped every data handoff between departments to identify bottlenecks and leakage points.
System architecture & data schema
Designed the unified HL7 FHIR database schema. Migrated 7 years of legacy patient records with de-duplication and validation.
Module build & integration
Built and connected the front-desk, pharmacy, IPD ward, and billing modules. Lab integration with existing third-party LIS via API bridge.
Staff parallel testing
Ran the new system in parallel with legacy systems. Staff trained in department-specific workflows with hands-on simulations at actual workstations.
Phased go-live & hypercare
Switched departments sequentially over two consecutive weekends. On-site Goolk AI engineer stationed for 2 weeks of hypercare support.
Goolk AI did what three previous software vendors could not — they unified our legacy systems in 11 weeks without a single minute of ward disruption. Our billing team no longer chases patients for missed charges.Chief Medical OfficerMetro Multi-Specialty Hospital, Karnataka
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