Demand, capacity, and the law of averages
If you plan capacity without allowing for variation, disaster will follow. Or will it?
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If you plan capacity without allowing for variation, disaster will follow. Or will it?
It's a surprisingly small challenge, so why not?
If you upload data to Gooroo Planner then you should really read this, because you may need to take action. (Updated on 25th May)
Need a forecast of your referral-to-treatment (RTT) profiles for 2018-19? Look no further.
Waiting times rose again, and the longest waits were hardest hit. Continued, severe and widespread capacity pressures are the likely culprit.
Over-one-year waiters shot up by 20 per cent, as admission rates slumped in the face of record A&E pressures.
At the core of this year's planning guidance lay something rather unusual. I think its intention was benign. But it has the potential to cause a lot of trouble, driving up waiting times and distorting clinical practice right across the country.
From a standing start, it usually takes less than a day to write decent queries and generate the first cut of hospital-wide modelling with Gooroo Planner. That's pretty fast. But we thought we could make it even faster.
Admissions per working day fell dramatically, to the lowest January level ever recorded, as the NHS followed central guidance to shut down routine care and release beds for emergency admissions. One year waiters - a key goal for next year's plans - went up again and exceeded 2,000 for the first time since 2012.
There are arguments for and against splitting hot and cold facilities. How would you decide? This example from a real NHS hospital shows how careful modelling can lead to a clear recommendation.