Evolution average number of beds per hospital

The OECD collects (among a lot of other statistics) information on the number of hospitals and hospital beds per country. These two parameters combined and its evolution over the years could give an indication on whether or not the country’s hospital landscape is evolving towards large medical centers, small scale hospital settings or whether there is no trend to detect.
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July 27, 2012Permalink 3 Comments

Estimating required hospital bed capacity

Estimating required hospital bed capacity requires a thorough analysis. There are a lot of ways of approaching a capacity requirement problem, but I think we can agree that a simple spreadsheet analysis just won't cut it.

The approach described in this post makes use of discrete-event simulation and, just to clarify, makes abstraction from a lot of variables which should be taken into consideration in a real-life analysis.

To explain the approach, the following case will be used:

An emergency department of a small regional hospital receives complains about its emergency admission capacity. After investigation of its admission data it becomes clear that their service level is not up to par with that of other hospitals. Therefore, plans for the redesign of the emergency department and an investment in its emergency bed capacity are presented. The plan proposes a new bed capacity of 12 beds (coming from a previous of 10 beds). The Chief of Medicine wants to know what the effect of this investment will be on their emergency admission service level.

The emergency department has recorded data on the interarrival times of patients that are admitted (or should be admitted) to an emergency bed. The following graph shows the interarrival distribution (triangular: mode=5, min=.1, max=12):

plot of chunk unnamed-chunk-1

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Using discrete-event simulation to simulate hospital processes

Discrete-event simulation is a very useful tool when it comes to simulating alternative scenario’s for current of future business operations. Let’s take the following case;

Patients of an outpatient diabetes clinic are complaining about long waiting times, this seems to have an adverse effect on patient satisfaction and patient retention. Today, one doctor runs the outpatient clinic. Hospital management has decided that in order to increase patient retention rates, a nurse will be hired to assist and take over some of the doctor’s tasks. This should result in decreased waiting times and, hopefully, increased patient retention rates.

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