Hospital patient admission prediction tool


[Music plays] (Dr James Lind) The Patient
Admission Prediction Tool is a tool to look at
exactly what it says, it predicts to
about 95% accuracy which patients are
coming in and when. [Music plays] We know today that there are 12 people
coming in with broken arms and legs. Only one of them has
come in up to date, but we know there’s
another 11 out there, so what we’ve been able to
do is set aside emergency theatre time for these
people already, so we know that they’re coming, and
we know we can treat them. (Patient) At the moment I
walked in I spoke to the person and I sat there for ten minutes, and the doctor called me
in, and so here I am. So it was like less than half an hour
I’m waiting to have my cast put on. (Dr James Lind) It was
difficult at first because many people didn’t believe the tool
could do what we said it could do. Up til recently a fallacy
existed that all hospitals had to be at 85% occupancy
for optimal patient flow. Using the mathematics of CSIRO we’ve
actually dispelled that rumour, and we can actually show
categorically that that’s not true, and we’ve actually worked
out optimal occupancies for not just our hospital
but other hospitals. Now people trust in the tool and
it actually informs our strategy. The performance of this hospital,
compared to the data from 2010, has actually increased its
four hour score by 20%. We now run above the federal
target, and we’re one of the largest HHS’s that
actually is able to do that. The impact for staff is that
this can be done within hours, so that it actually minimises
the amount of overtime. It also minimises the
amount of stress because it’s done in a
well ordered fashion, and everyone knows their
jobs and responsibility, and where the actual problems
that we need to address are. One of the key points
with the partnership with CSIRO is that we
provide the clinical input, and the mathematics resource
optimisation etcetera does come from the CSIRO expertise,
but it’s marrying these two important areas together. You
couldn’t do it without either one, and that’s where the partnership
has been fantastic. The proof of the pudding
really of this tool is we’re in the middle of
winter; it’s the worst point for an emergency
department because of the winter surge that occurs. Up til
recently you would have seen pictures of ambulances queuing
outside to get into emergency, and all the beds being full. If we
look today, on one of our busiest winter’s day, you can see there are
still free beds in the emergency department, and there’s only one
ambulance outside, which has managed to offload its stretcher. What
we’re able to do with this tool is show people that actually
what happens in health care is very predictable on
a day by day basis. [Music plays]

2 thoughts on “Hospital patient admission prediction tool

Leave a Reply

Your email address will not be published. Required fields are marked *