A virtual evaluation of options for managing risk of hospital congestion with minimum intervention.

Hospital congestion is a common problem for the healthcare sector. However, existing approaches including hospital resource optimization and process improvement might lead to huge cost of human and physical structure changes. This study evaluated less disruptive interventions based on a hospital simulation model and offer objective reasoning to support hospital management decisions. This study tested a congestion prevention method that estimates hospital congestion risk level (R), and activates minimum intervention when R is above certain threshold, using a virtual hospital created by simulation modelling. The results indicated that applying a less disruptive intervention is often enough, and more cost effective, to reduce the risk level of hospital congestion. Moreover, the virtual implementation approach enabled testing of the method at a more detailed level, thereby revealed interesting findings difficult to achieve theoretically, such as discharging extra two medical inpatients, rather than surgical inpatients, a day earlier on days when R is above the threshold, would bring more benefits in terms of congestion reduction for the hospital.

Hospital occupancy and discharge strategies: a simulation-based study.

BACKGROUND: Increasing demand for hospital services has resulted in more arrivals to emergency department (ED), increased admissions, and, quite often, access block and ED congestion, along with patients' dissatisfaction. Cost constraints limit an increase in the number of hospital beds, so alternative solutions need to be explored. AIMS: To propose and test different discharge strategies, which, potentially, could reduce occupancy rates in the hospital, thereby improving patient flow and minimising frequency and duration of congestion episodes. METHODS: We used a simulation approach using HESMAD (Hospital Event Simulation Model: Arrivals to Discharge) - a sophisticated simulation model capturing patient flow through a large Australian hospital from arrival at ED to discharge. A set of simulation experiments with a range of proposed discharge strategies was carried out. The results were tabulated, analysed and compared using common hospital occupancy indicators. RESULTS: Simulation results demonstrated that it is possible to reduce significantly the number of days when a hospital runs above its base bed capacity. In our case study, this reduction was from 281.5 to 22.8 days in the best scenario, and reductions within the above range under other scenarios considered. CONCLUSION: Some relatively simple strategies, such as 24-h discharge or discharge/relocation of long-staying patients, can significantly reduce overcrowding and improve hospital occupancy rates. Shortening administrative and/or some treatment processes have a smaller effect, although the latter could be easier to implement.