Booked inpatient admissions and hospital capacity: mathematical modelling study.
OBJECTIVE
To investigate the variability of patients' length of stay in intensive care after cardiac surgery. To investigate potential interactions between such variability, booked admissions, and capacity requirements.


METHODS
Mathematical modelling study using routinely collected data.


METHODS
A cardiac surgery department.


METHODS
Hospital records of 7014 people entering intensive care after cardiac surgery.


METHODS
Length of stay in intensive care; capacity requirements of an intensive care unit for a hypothetical booked admission system.


RESULTS
Although the vast majority of patients (89.5%) had a length of stay in intensive care of < or = 48 hours, there was considerable overall variability and the distribution of stays has a lengthy tail. A mathematical model of the operation of a hypothetical booking system indicates that such variability has a considerable impact on intensive care capacity requirements, indicating that a high degree of reserve capacity is required to avoid high rates of operation cancellation because of unavailability of suitable postoperative care.


CONCLUSIONS
Despite the considerable enthusiasm for booked admissions systems, queuing theory suggests that caution is required when considering such systems for inpatient admissions. Such systems may well result in frequent operational difficulties if there is a high degree of variability in length of stay and where reserve capacity is limited. Both of these are common in the NHS.
Gallivan
Steve
S
Clinical Operational Research Unit, University College London, London WC1E 6BT. s.gallivan@ucl.ac.uk
Utley
Martin
M
Treasure
Tom
T
Valencia
Oswaldo
O
D000289:Admitting Department, Hospital; D001509:Bed Occupancy; D003325:Coronary Care Units / Q000706:statistics & numerical data; D006331:Heart Diseases / Q000601:surgery*; D006742:Hospital Bed Capacity; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D007902:Length of Stay / Q000706:statistics & numerical data*; D008131:London; D015233:Models, Statistical; D010346:Patient Care Management / Q000706:statistics & numerical data*