Capacity & Demand Modelling

The increasing influence of "payment by results", are putting enormous pressures on hospitals to cut costs. In response to these pressures, many hospitals have made drastic changes including downsizing beds, cutting staff and merging with other hospitals. These critical capacity decisions generally have been made without the help of Operational Research model-based analyses, routinely used in other industries, to help with capacity planning and management. Such actions have resulted in diminished patient access without significant reductions in costs.

Capacity planning in hospitals: overview

The most fundamental measure of hospital capacity is the number of inpatient beds. Hospital bed capacity decisions have traditionally been made based on target occupancy levels – the average percentage of occupied beds. Historically, the most commonly used occupancy target has been 85%. Certain units in the hospital, such as intensive care units (ICUs) are often run at much higher utilisation levels because of their high costs.
The other major component of capacity is personnel, particularly nurses. Nurses are the chief caregivers as well as managers of the clinical units. In recent studies, nursing has been found to have a significant impact on clinical outcomes. In addition, nursing costs comprise a very substantial fraction of hospital budgets. Though there have been many uses of optimisation models to determine nurse staffing, hospitals often lack basic data, such as patient census by time of day that would be needed to use such models.
Another significant component of capacity is operating rooms. The efficient use of operating rooms, which are often bottlenecks, can be central to the smooth functioning of the hospital as a whole.
Major diagnostic equipment such as MRIs comprises another important category of capacity.

Understanding the problem

Before looking for solutions, it is critical to first understand the nature of the problem. This should begin with the question: How long should patients wait?"

Complexities of capacity planning

Even without specific standards, there is clearly a problem when patients wait for the better part of the day for a bed. What causes these problems? Though one likely cause (and the most widely cited in the media) is the reduction of inpatient beds over the past 10 years, many other factors must be considered. From the capacity planning perspective, the entire process from patient arrival in the hospital (normally the Accident & Emergency Room) to placement in a bed must be examined. Considering only the major steps, the process begins with the Triage Nurse, who determines the patient's condition and registration which is normally a clerical function. Next, the patient is seen by an A & E physician. Often this results in a request for diagnostic testing such as blood analysis and x-rays. Laboratory specimens are generally collected by nurses and sent to a centrally testing facility of the hospital. If the patient needs to be taken to another location in a hospital for diagnostic test, transport personnel are needed. When all the tests are completed, the physician reviews them and determines whether the patient requires admission to the hospital. If so, a bed is requested in the appropriate nursing unit (e.g. medical, surgical, intensive care). The availability of a bed is affected not only by capacity of the relevant unit but also by the admission and scheduling policies of elective patients, particularly surgical patients who compete for the same beds as many emergency patients and by transfer and discharge policies and procedures. Even if a suitable bed is vacant, it must be located and identified as empty, and then cleaned, if necessary. In addition, a floor nurse must be available to admit the patient. When everything is ready, a request is made for transport and when it is available, the patient is finally moved to the assigned bed. Clearly, there is a potential for a mismatch between the demand and availability of capacity in each step of the process.
This description illustrates the complexities of hospital capacity planning and management:-

1.Demonstrates the interdependencies of the various parts of the hospital and the need to identify bottlenecks.
2.These bottlenecks may change from hour to hour, shift to shift, daily, weekly and seasonally
3.Shows the variety of both fixed capacity (e.g. inpatient beds, A&E beds, diagnostic equipment etc) and variable capacity (e.g. nurses, physicians, technicians, transport staff etc) that must be managed.
4.Much of the capacity required for A&E admissions, such as inpatient beds, labs, diagnostic equipment and transport staff is shared by other patients in the hospital and thus policies and procedures are required to allocate these resources amongst the various patient groupings.

The problem with occupancy levels

What is wrong with using occupancy levels to manage capacity? First, reported occupancy levels are generally based on the average "midnight census". However, the midnight census usually measures the lowest occupancy level of the day. One reason is the phenomenon known as the "23 –hour patient" who is admitted in the morning and discharged in the evening. More generally, most patients are admitted in the morning or early afternoon and are not discharged until after attending physicians have conducted examinations, so that the peak census is in the middle of the day and can easily be 20% higher than at midnight. In addition, the utilisation of hospital facilities is far from uniform across the week or across the year. Very few procedures are scheduled for weekends, so elective patients are not usually admitted on weekends when the average daily census is considerably lower. Summer and holiday periods are also slower and other seasonal effects have been observed in specific hospitals and/or for specific units. Reported occupancy levels are yearly averages and hence do not reflect significantly higher levels that may exist for extensive periods of time. For all these reasons, reported occupancy levels are not reliable measures of general bed utilisation.

More importantly, bed occupancy levels do not measure or even indicate patient's delays for beds or delays in discharges. Yet, hospitals do not typically measure bed delays nor do they use queueing or simulation models to estimate the delays that would result from changes in demand or the number or organisation of beds.
 
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