Capacity planning for intensive care units

Improving operational effectiveness of tactical master plans for emergency and elective patients under stochastic demand and capacitated resources

“…He develops a simulation model designed to assess the impact of the flow of emergency and elective patients over the use of three major resources: beds, operating theatres and medical staff. Simulation models are used for their predictive value as in the work of Ridge et al (1998) which evaluates in particular the bed occupancy level when setting to some value the transfer rate of emergency patients to other hospitals. Emergency transferal as a way to manage patient overflow also is analysed in the paper of Litvak et al (2008).…”

Integrated decision making in healthcare : an operations research and management science perspective

“…The common objective is to dimension the number of beds of a single medical care unit such that occupancy of beds is maximized while a predefined performance norm is satisfied [208,371,373,415,497,519]. The typical performance measure is the percentage of patients that have to be rejected for admission due to lack of bed capacity: the admission refusal rate.…”

“…The desirable occupancy level should be calculated as a complex function of the service mix, the number of beds and the length of stay distribution [242,243]. This non-linear relationship between number of beds, mean occupancy level and the number of patients that have to be rejected for admission due to lack of bed capacity is often emphasized [7,123,242,247,295,371,372,415]. In determining the appropriate average utilization, the effect of economies-of-scale due to the so-called portfolio effect plays a role: larger facilities can operate under a higher occupancy level than smaller ones in trying to achieve a given patient service level [217,243,244,295], since randomness balances out.…”

“…Methods: computer simulation [7,19,104,108,112,156,157,206,221,222,238,241,242,243,244,259,292,295,347,371,372,373,375,415,439,478,497,517,519,523,524], heuristics [309], Markov processes [7,68,172,192,199,245,246,247,335], mathematical programming [127,202,241,318,327,375,376], queueing theory [11,29,…”

“…The first is refusing admissions of a certain patient type when the bed census exceeds a threshold. For example, to prevent the rejection of emergent admission requests, an inpatient care unit may decide to suspend admissions of elective patients when the number of occupied beds reaches a threshold [167,189,270,285,347,355,415,443]. As such, a certain number of beds is reserved for emergency patients.…”