Demand and Capacity for Radiology Hull 16/09/08

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Demand and Capacity for Radiology Hull 16/09/08

Postby Kate Silvester on Tue Sep 16, 2008 4:56 pm

Basic demand and capacity presentation for the Yorkshire and Humber radiology departments.
Objectives:
1. Understand why we have queues in radiology
2. Measuring demand and Pareto analysis
3. Measurement for improvement
4. Basics of statistical process control to access the sustainability & capability of a process
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Kate Silvester
 
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Re: Demand and Capacity for Radiology Hull 16/09/08

Postby snatu on Tue Mar 09, 2010 7:30 pm

i have understood the basic reason why there is demand and capacity variation and why waiting lists build up. but what i do not understand is the solution to these problems. understanding demand and capacity seems to be the message here, yet erlangs curve suggests that whatever we do only 85% of the demand will be met with at any given time with 100% capacity. is there a magical formula? or am i missing something?
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Re: Demand and Capacity for Radiology Hull 16/09/08

Postby joetraff on Thu Jul 15, 2010 6:48 pm

Kate Silvester wrote:Basic demand and capacity presentation for the Yorkshire and Humber radiology departments.
Objectives:
1. Understand why we have queues in radiology
2. Measuring demand and Pareto analysis
3. Measurement for improvement
4. Basics of statistical process control to access the sustainability & capability of a process

Loved your sharing.
Keep up the good work.


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Re: Demand and Capacity for Radiology Hull 16/09/08

Postby pharriman on Wed Aug 11, 2010 3:35 pm

snatu wrote:i have understood the basic reason why there is demand and capacity variation and why waiting lists build up. but what i do not understand is the solution to these problems. understanding demand and capacity seems to be the message here, yet erlangs curve suggests that whatever we do only 85% of the demand will be met with at any given time with 100% capacity. is there a magical formula? or am i missing something?


Erlangs rule suggests that if you try to run any system at more than 80-85% utilisation then it will fail. That being so you require sufficient capacity in a radiology system so that on average it runs at that level of efficiency. In practice you plot your demand and find the difference between min and max demand multiply this figure by 0.8 and then add back the min. This gives your your 80% value (this assumes of course that the system is statistically in control). That value is the capacity that you put in place for every time period. There is another lot of work to do to release the capacity to achieve this without spending more money. Hope that makes sense.
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