The Challenge

Since 1948 the New Zealand Cancer Registry has tracked the incidence and type of cancer prevalent across New Zealand. With population growth and the move to digital health networks (Connected Health) there was a need to continue to update and enhance the functionality clinicians had at their disposal when diagnosing patients.  

Our Solution 

Working with the Ministry of Health, Solnet designed and implemented a revamped cancer registry system, and is continuing to support and expand, the Online Registry, as an extension to the NZCR application.

Clinicians can join the Online Registry. On receiving an invitation, they can log in from any workplace with the Health Network (ie Connected Health). Lead clinicians can easily enter their clinical diagnosis for a registered cancer event.

Using standard structured reports means that requesting clinicians and Cancer Registry clinical coders can read and understand pathology reports more easily, find key information faster, and make a more accurate diagnosis.

Registryscreenshot1

Speeding up reporting for pathologists

The Structured Report Assistant online tool helps pathologists enter structured data, and presents it clearly for inclusion in their laboratory reports. As a user-friendly national implementation, with no cost to the laboratory.

Pathologists say this saves them a huge amount of time. Using standard, structured reports means that requesting clinicians, and the Cancer Registry coding team, can read and understand pathology reports more easily, find key information faster, and make a more accurate diagnosis.

fasterreportingMoH

Looks great; five clicks, and I am done entering cancer staging information. 

Clinician Ministry of Health

datacollectionMoH

Collecting data for more informed decision making 

A further stream of the Online Registry allows clinicians diagnosing cancer to log in remotely to the Online Registry and submit their clinical diagnosis as they make it, providing additional data to the Registry and contributing to new statistical data for better long-term planning.

Individual items of information, such as specimen size or clearance, can be automatically identified and saved. This will allow statistical comparisons in the future, leading to better research, planning and decision support for cancer treatment.

Case Studies

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We're helping leading New Zealand organisations design and deliver their digital futures.

Air New Zealand
BNZ
Fonterra
Inland Revenue
Kiwirail
Lotto NZ
Ministry of Business, Innovation and Employment
Neon
Sky
Tower