Integral resource capacity planning for inpatient care services based on bed census predictions by hour

Abstract

The design and operations of inpatient care facilities are typically largely historically shaped. A better match with the changing environment is often possible, and even inevitable due to the pressure on hospital budgets. Effectively organizing inpatient care requires simultaneous consideration of several interrelated planning issues. Also, coordination with upstream departments like the operating theatre and the emergency department is much-needed. We present a generic analytical approach to predict bed census on nursing wards by hour, as a function of the Master Surgical Schedule and arrival patterns of emergency patients. Along these predictions, insight is gained on the impact of strategic (ie, case mix, care unit size, care unit partitioning), tactical (ie, allocation of operating room time, misplacement rules), and operational decisions (ie, time of admission/discharge). The method is used in the Academic Medical Center Amsterdam as a decision-support tool in a complete redesign of the inpatient care operations.

Keywords:

• probability
• health service
• hospitals
• medical care units
• bed occupancy
• surgical scheduling

Acknowledgements

This research is supported by the Dutch Technology Foundation STW, applied science division of NWO and the Technology Program of the Ministry of Economic Affairs.The authors would like to acknowledge Peter Vanberkel and Erwin Hans for the discussion that contributed to this study.

Notes

1 The mean absolute error (MAE) is given by MAE=(1)/(n)∑_i=1ⁿ|a_i−y_i|, where a_i is the actual value and y_i the predicted value.

2 The mean absolute percentage error (MAPE) is given by MAPE=(100%)/(n)∑_i=1ⁿ|(a_i−y_i)/a_i|, where a_i is the actual value and y_i the predicted value.