NSW Health Pathology has quietly rewritten a playbook for how large public laboratories can use low-code tooling to accelerate genomics throughput and create a single, auditable source of truth for quality management — all without buying an off‑the‑shelf genomics system. The service built two purpose‑built Power Apps —
GLoW, to orchestrate genomics specimen preparation and sequencing workflows, and
QPoint, to consolidate statewide quality management documents and processes — and deployed them inside a disciplined DevOps and governance framework that pairs low‑code speed with pro‑code reliability. The result is faster prototyping, better visibility across labs and devices, and early signs that automation can improve regulatory confidence rather than undermine it.
Background
NSW Health Pathology runs one of Australia’s largest public pathology operations, with thousands of staff, multiple accredited laboratories and collection centres, and statewide referral networks supporting complex specialisms such as infectious diseases and genomics. That scale exposes the classic problem of large public healthcare systems: many local workarounds and disparate systems create inconsistent processes, duplicated content and fragile handoffs — problems that are especially acute in genomics, where pipeline sequencing is both costly and sensitive to pre‑analytical errors. Standardising processes and collapsing tool sprawl were therefore strategic priorities for the organisation. Microsoft’s Power Platform (Power Apps, Power Automate, Dataverse, and related services) was already selected as the organisation’s standard low‑code stack. NSW Health Pathology elected to apply that platform to two high‑value problems: replacing a withdrawn third‑party genomics system and consolidating more than 100,000 quality documents that lived across many different local systems. The in‑house path they chose emphasised speed, interoperability (APIs), strong DevOps pipelines and a single tenant model to preserve governance and auditability.
Overview of the two flagship solutions
GLoW — sequencing readiness, visible and auditable
GLoW is a Power Apps‑driven application designed to coordinate specimen preparation across the genomics pathway. It maps the lifecycle from specimen receipt through robotic processing and sequencing, and provides status visibility to lab staff and scientists. The app was prototyped rapidly — reported at roughly three months to prototype and six months to minimum viable product — allowing the team to avoid procurement delays and the integration risk that comes with replacing one commercial genomics suite with another. GLoW also integrates with the core Laboratory Information System and robotics controllers to remove double‑entry and reduce transcription errors that can lead to wasted sequencing runs. Key reported benefits:
- Reduced error rates in specimen preparation.
- Greater confidence that samples are ready and correctly prepared for sequencing.
- Improved end‑to‑end visibility across the sequencing pipeline, reducing mid‑run failures and wasted reagent costs.
QPoint — a statewide quality management information system
QPoint centralises quality management system (QMS) documentation and workflows into a single Power Apps surface. Previously, each laboratory used its own QMS, leading to duplicated, inconsistent and outdated documents. QPoint aims to consolidate roughly 100,000 disparate documents into a much smaller, standardised corpus — the Microsoft narrative cites a reduction target to fewer than 20,000 documents — and it embeds authoring, review, approval and audit workflows so the same processes are followed consistently statewide. Engagement metrics reported in early rollouts were strong: hundreds of staff attended demonstrations, dozens volunteered for user acceptance testing, and many participated in sprint showcases. Independent conference coverage of pathology innovation programs in Australia has featured QPoint presentations, confirming the platform’s presence in professional forums and peer discussions beyond vendor marketing. This corroboration supports the conclusion that the project is both operational and visible to the pathology community.
Why NSW Health Pathology’s approach matters
Speed without sacrificing control
A defining theme of the NSW approach is
speed, but not as a synonym for risk. Low‑code delivered by a professionalised team — one that enforces DevOps pipelines, automated builds and role‑based access controls — shortens iteration cycles while keeping production reliability high. Building GLoW in‑house avoided the time and integration cost of third‑party procurement and gave the organisation direct control over interoperability between the LIS, robotics and downstream reporting surfaces.
Interoperability as a first‑class concern
One of the most common failures in pathology IT is integrating disparate devices and laboratory automation with a central LIS. NSW Health Pathology designed GLoW and QPoint with API‑first principles, so they can push and pull data from robotics systems, the LIS, and downstream reporting tools. The team emphasises that many SaaS vendors treat interoperability as an afterthought; building their solution internally allowed them to make it a primary design goal. That decision reduces transcription errors and supports a more auditable, machine‑mediated flow of truth.
Regulatory and audit advantages
When automation replaces a human step, regulators can prefer it: an automated, versioned process can be certified and reproduced consistently. NSW Health Pathology found that automation simplified audits because it is easier to demonstrate that a controlled process ran the same way every time. That regulatory argument is a powerful counterpoint to the common concern that automation will introduce opaque machine decisions into regulated workflows. The architecture pairs automation with audit trails, access control and a standard releases pipeline to make compliance defensible.
Technical architecture and governance — practical patterns
Low‑code + pro‑code together
NSW Health Pathology built a
hybrid delivery model: low‑code front ends and process automation for rapid delivery, combined with pro‑code services in Azure where custom compute or advanced integrations were required. This retains the benefits of low‑code for front‑line staff while avoiding platform limitations for complex integrations. All changes flow through automated build and release pipelines, and role‑based access control is enforced at the environment and data level.
DevOps, ALM and quality gates
The team maintained mature DevOps practices:
- Automated build-and-release pipelines that subject all changes to review.
- Role‑based access so production changes are controlled and auditable.
- User acceptance testing and sprint showcases to keep clinicians and scientists involved in prioritisation and quality.
These operational disciplines are essential when a low‑code tool is used for regulated clinical workflows; low‑code without ALM and governance becomes a liability. This pattern aligns with practical recommendations for Power Platform CoEs and SAP/enterprise integration use cases documented in practitioner guidance.
Measured outcomes and adoption signals
Reported operational impacts
Microsoft’s customer story and project brief list several practical outcomes:
- Rapid prototyping (three months) and MVP delivery (six months) for GLoW.
- Reduced sample preparation errors and improved confidence in sequencing runs.
- Early consolidation targets for QPoint: shrinking roughly 100,000 documents toward fewer than 20,000 through standardisation.
- High staff engagement during early demonstrations and UAT.
These metrics are meaningful because they target two cost centers in modern pathology: reagent and sequencing run costs (sensitive to preanalytical error), and the recurring overhead of managing regulatory documentation and audit preparedness.
Adoption indicators
The project attracted strong internal engagement: around 900 demonstration attendees and 90 volunteers for user acceptance testing in early stages, which shows breadth of interest across scientific and operational teams. Early stakeholder buy‑in is an important success factor for digital transformations in healthcare, where clinician acceptance is often the critical path to sustained use.
Strengths and notable innovations
- Practical low‑code governance: The combination of a low‑code centre‑led team with pro‑code practices and CI/CD pipelines is a strong operational pattern for regulated environments. It preserves the speed of Power Apps while enforcing production standards.
- API‑first interoperability: Prioritising integration with LIS and automation hardware reduces manual transcription and allows the apps to operate as coordinating layers rather than islands.
- Regulatory‑friendly automation: Designing automation that is auditable and certifiable turns a perceived risk (automation) into a compliance advantage.
- Rapid, pragmatic delivery: Avoiding lengthy procurement cycles by prototyping in‑house reduced time‑to‑value — a critical advantage in clinical genomics where time and reagent costs are material.
- Statewide, clinician‑driven change: Strong clinician co‑design and visible UAT participation make the product a collaborative solution rather than a top‑down IT imposition.
Risks, limitations and areas that need careful governance
Vendor‑reported numbers need caution
Several of the metrics in the published case are vendor‑reported and come from the organisation’s own reporting. While those numbers are meaningful signals, they should be treated as
vendor‑reported outcomes unless reproduced in independent operational audits or peer evaluations. For example, the document consolidation target (100,000 → <20,000) and the three‑month prototype timeline are plausible but remain specific to NSW Health Pathology’s context and resourcing, and may not be universally replicable. Where exact impact matters (budget planning, scaling), organisations should run representative PoCs and instrument their baseline carefully.
Low‑code sprawl if governance lapses
Low‑code can proliferate rapidly. Without a Centre of Excellence, environment strategy, ALM controls and monitoring, a Power Platform estate becomes hard to maintain and insecure. NSW Health Pathology mitigated this with strong DevOps patterns, but organisations adopting similar tactics must budget for governance, training and lifecycle management. Practitioner guidance in the field reinforces this requirement.
Integration and device certification complexity
Pathology devices and robotics often use proprietary interfaces and require certificate management, deterministic timing and chain‑of‑custody controls. Integrating these safely into a low‑code front end requires careful architecture, private networking, service principals and audited connectors. These are solvable challenges, but they add hidden complexity beyond the visible app screens.
AI and automation guardrails
The story anticipates agentic AI and document classification to support migration and search, but those features must be introduced with transparent provenance, human‑in‑the‑loop verification gates and clear policies about acceptable use. LLM hallucination risks and privacy requirements in clinical data demand conservative rollout plans and robust audit logs.
Practical checklist for other pathology labs considering the same path
- Inventory and prioritise: map mission‑critical processes where mistakes are costly (sequencing prep, specimen labels, regulatory forms).
- Build a mixed team: combine Power Apps makers with pro‑code engineers who can build robust connectors and maintain CI/CD.
- Implement ALM from day one: automated builds, environment strategy, and role‑based release gates.
- Start with a representative PoC: use real specimens/islands of data to validate interoperability and error modes.
- Governance and training: establish a CoE, run role‑based training and maintain a catalogue of sanctioned connectors and templates.
- Compliance baseline: confirm contract and audit requirements (chain‑of‑custody, data residency, BAAs if required), and instrument logs for every automated action.
- Measure iteratively: define KPIs for error reduction, turnaround time, cost per run, and document lifecycle reductions, and track them before and after rollout.
Where the model scales — and where it doesn’t
Power Platform excels at bridging process gaps, digitising forms, and coordinating existing systems. In laboratories, the pattern of “small apps to fill gaps” — short, focused apps that automate a single step and connect two systems — is repeatable and low risk when governance is in place. NSW Health Pathology’s approach shows this pattern translated to high‑value flows such as genomics specimen prep and QMS consolidation.
However, large monolithic replacements that require complex transactionality, heavy duty compute, or proprietary device drivers are not always low‑code wins. For those, a hybrid architecture — low‑code for workforce interfaces, Azure services for compute and orchestration — is the safer pattern. NSW Health Pathology’s explicit mix of low‑code UI and pro‑code backend components provides a practical template.
A critical view: governance, vendor reliance and long‑term ownership
Adopting a single platform has operational and procurement benefits, but it also concentrates dependency. NSW Health Pathology benefited from platform consolidation (fewer tools to maintain, shared expertise), yet long‑term risk assessment must address:
- Licensing and cost management for Power Platform and premium connectors.
- Skills retention — will citizen developers stay, or will the organisation rely on external consultants?
- Exit and interoperability plans in case regulatory or strategic priorities change.
These trade‑offs are manageable but deserve explicit planning and continuous review. Independent community guidance and procurement playbooks stress the need to model total cost of ownership and confirm entitlements for required connectors and APIs as part of any consolidation strategy.
Conclusion
NSW Health Pathology’s GLoW and QPoint projects are a pragmatic demonstration that low‑code platforms, when managed with disciplined governance and pro‑code complements, can deliver production‑grade capabilities in clinical genomics and quality management. The projects address two acute pain points — fragile genomics supply chains and fragmented quality documentation — with rapid prototyping, clinician co‑design and automated DevOps pipelines. Early outcomes suggest fewer specimen prep errors, better sequencing confidence and a measurable path to consolidating statewide quality documents into a single, auditable system. These gains are meaningful for public labs that must balance cost, compliance and service levels under tight timelines. At the same time, the story is a measured reminder: low‑code is not a shortcut to bypass governance. It is most effective when embedded in disciplined ALM, strong integration patterns and a clear compliance framework. For other pathology services considering a similar course, NSW Health Pathology’s experience offers a tested template — combine low‑code agility with pro‑code rigour, invest in governance up front, and treat early prototypes as instrumented experiments rather than final guarantees.
Source: Microsoft
NSW Health Pathology uses Power Apps to scale genomics and unify quality management | Microsoft Customer Stories