Our vision: to transform access to medical care.

Response time distribution uncovers problems

Good responses stacked up on the left

Good responses stacked up on the left

The distribution of response times shows in more detail than the response time runchart what is happening. It is the number of minutes between the patient calling and the GP responding, whatever the time of day, averaged over the last four weeks.

The first example is about as good as it gets, with most responses very fast.  The closer capacity is matched to demand, the more like this it looks.  Crucially, doctors are starting to call as soon as reception opens.  They start in control and stay in control.  A virtuous circle then means that patients gain confidence and spread out their demand, so faster response is easier.  Note the long tail – a few patients ask for a later call, usually because of work commitments.  That is fine – there is no target to meet.

Poor responses, and many left to late in the day

Poor responses, and many left to late in the day

What can go wrong?  In the next example, the practice has not optimised and may be thinking about GP slots rather than responding to patient demand.  Two modes show that some demand is dealt with soon-ish, but not fast because the GPs are starting later than reception and come in to a depressingly long list.  Then a delay of four hours, as other activities take over, face to face, meetings and visits.  Patients call again to chase, while “Did Not Answer” wastes doctor time.

There is no need and no excuse for such poor planning.  Everyone is happier with chart one, and here’s a secret:  it’s less work.