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The algorithm can push time average admission rate close to optimal, with a corresponding tradeoff in average queue backlog.
This paper considers optimization of time average admission rate in an energy-constrained network system with multiple classes of data flows.
The general adult multidisciplinary ICU has 10 beds, 92.4% percentage of mechanically ventilated patients and an average admission rate of 392.4+41.6 patients per year.
However, even if we limited the meta-analysis to the most restrictive types of questions in self-reports, we would still have an average admission rate above 1%, which is higher than previous estimates (e.g. [11]).
QECH is a 1250-bed government funded central hospital that provides primary to tertiary care and has an average admission rate of 50,000 patients per year (see below).
The average admission rate for the study group was 15.0 (95% CI, 8.4, 24.7) admissions/million/year.
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Average admission rates were 17/1000/yr for acute wasting and 5/1000/yr for Oedema.
Patients in the 60 69, 70 79 and 80+ age groups had the highest average admission rates (24.3, 35.2 and 45.8 per million/year).
Compared to the results of current community-based studies with similar length of study, our admission rate can be considered rather low; studies with a length between nine and eleven years showed average admission rates between 10.9% and 33.8% over this period [ 10, 22- 25].
Error bars equating to one standard error around the average at each data point are also included, from which it can be visually confirmed that there is an underlying pattern to the data and that average admission rates are significantly different from zero.
The perioperative HDU has 15 beds and admits all surgical patients requiring organ support after vascular, endocrine and digestive surgery with an average annual admission rate of 1076 patients.
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