Data drives decision making at St John

eHealthNews.nz: AI & Analytics

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Monday, 29 April 2019

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Pictures:

Right: St John head of business intelligence Dave Richards.

End of story: Predictive analytics simulation program Optima Predict.

eHealthNews.nz editor Rebecca McBeth

St John New Zealand uses real-time data, predictive analytics and connected data sets to inform decisions about the ambulance service.

Head of business intelligence Dave Richards will speak at Emerging Tech in Health 2019 in Christchurch on May 21–22 on how the organisation is driven to ensure that all decisions are informed by data.

He says any potential major changes to the service have to go through his 11-strong BI team, which uses predictive analytics software Optima Predict to run ‘what if?’ simulations and make recommendations.

Simulations usually involve running through a year’s worth of emergency calls and vehicles being sent to test how changing any aspect of the system – such as adding a new station – would impact the service.

“Whatever we do and change, we have a fairly good idea of what the impact is likely to be, so we can ensure our decisions will have a positive impact for patients,” Richards says.

The service has used these simulations to determine a plan of which stations should be staffed first in order to be closest to likely call-outs and to create real-time reports to prioritise where ambulances should go after completing a job.

Decision support software, Optima Live, is also being rolled out to dispatchers, which recommends where ambulances should go to be in compliance with the plan.

“The hardest thing when rolling out the software is the change management side of things: getting dispatchers to use a new tool and do things differently,” Richards says.

“We have got the technology all there, it’s now about getting the staff engaged and using it.”

The service also has two years of clinical data from ambulance staff filling out Electronic Patient Report Forms. It is doing a proof of concept with Canterbury DHB to link a daily extract of data using National Health Index numbers to better understand the full patient journey.

This would allow St John to see what happens to their patients once they are dropped at hospital, such as their length of stay, and to make changes to improve patient outcomes where possible.

This would be particularly beneficial in identifying patients who do not need to be taken to an emergency department, as hospitals are under immense pressure and around one quarter of ED attendances arrive via ambulance.

“If they weren’t admitted, can we train staff to look at alternative options for those patients?,” Richards asks.

The organisation also uses data to do performance monitoring to ensure ambulances are getting to patients as fast as possible and that 95 per cent of 111 calls are answered within 15 seconds.