Clinics & networks
Clinic networks
Clinic networks
One network. A shared foundation for care.
Bring clinics together around connected workflows and comparable data, while making room for the local requirements that matter.
Start with a blueprint.
Map how your clinics work today. Agree where to standardise, where to preserve local variation and what a shared operating model should enable.
Standardise
Shared treatment journeys, definitions and reporting across every site.
Preserve locally
Prescribing, reporting and the regulatory requirements of each market.
Enable
What the shared operating model should make possible for the network.
Align clinical, lab and operational workflows.
Treatment journeys
Laboratory processes
Patient communication
Finance
Responsibilities across sites
Bring your network’s data together.
A shared view of the network starts with making information from different clinics understandable together.
Our ETL data pipelines extract, transform and load information from agreed source systems into a shared data foundation. We map local structures, align definitions and validate the information behind network reporting.
Agreed source systems
Clinic A
wawa
Clinic B
Existing system
Clinic C
Not yet in scope
ETL & validation
Extract · map local structures · align definitions · validate quality · trace to source
Shared data foundation
Clinical, lab, operational and financial information with shared definitions.
Network reporting & analysis
Activity across sites. Variation worth investigating.
Extension · research and future AI
Build the data blueprint alongside the operating blueprint.
Agree how information should connect across the network, what to standardise, which local differences to preserve and how data quality will be maintained. Migration into wawa and ongoing data pipelines are scoped as distinct pieces of work.
Source systems
Data mappings
Shared definitions
Validation
Refresh requirements
Access
Responsibilities
Build meaningful network visibility.
Define shared measures and data structures before relying on cross-clinic comparisons. Make differences in case mix, definitions and local workflows visible.
Cycles started per month
Illustrative · synthetic data
Site
Cycles
Context
Site A
62
Shared definition
Site B
48
Counts FET separately
Site C
55
Older case mix
Connect data through a staged rollout.
Where agreed connections support it, plan data ingestion from existing clinic systems alongside the rollout of wawa, so the network can develop a shared view while clinics transition at different stages.
Stage 1
Stage 2
Stage 3
Stage 4
Clinic A
Live on wawa
Live on wawa
Live on wawa
Live on wawa
Clinic B
Data ingested
Data ingested
Live on wawa
Live on wawa
Clinic C
Data ingested
Data ingested
Live on wawa
Data ingested from existing system
Live on wawa
Roll out with a clear plan.
Prepare migration, integrations, training and go-live around the realities of each clinic and the priorities of the network.
Create a foundation for innovation.
Connected information and aligned workflows create opportunities for collaboration, research and future AI support across the organisation.
Start with the network you want to build.
Let’s map the operating model and the path to it.