Decision support for choosing ventilation operation strategy in hospital isolation rooms: A multi-criterion assessment under uncertainty Review Article

Guidelines for isolation rooms in hospitals require keeping these rooms at a negative pressure differential, but the guidelines do not suggest a particular ventilation strategy for how to meet this requirement. In principle, one strategy could use variable air volume (VAV). However, VAV boxes are often set to deliver constant air volume (CAV), perhaps due to a lack of confidence in the controllability of the VAV. In this paper, an adaptive VAV operation is introduced in response to a concern that the current operation is not adequate, as it leads to excessive fan energy consumption. The adaptive VAV temporarily increases the volume offset before the door is opened, and thus induces a higher negative pressure differential. Otherwise the negative pressure differential is kept at an acceptable minimum. This paper evaluates the current practice of the VAV being set to CAV in comparison to the adaptive VAV operation, which will help the facility manager make a decision. A rationale of ventilation operation is chosen by a set of objective performance evaluation criteria: normalized energy consumption, potential exposure to contamination, and thermal comfort. Analysis results show that the two operation modes do not exhibit noticeable differences in their ability to control the spread of contaminants or in their maintenance of thermal comfort. However, the adaptive VAV mode consumes significantly less energy. As transitioning between low and high pressure differentials of the adaptive VAV may result in momentary contamination exposure, caregivers can be asked to pause at the door until the required negative pressure differential is achieved in order to secure a safe transition. As this new process requires a change of the protocol for caregivers in isolation rooms, an additional performance aspect concerning potential loss of care time is incorporated into the decision analysis. A Bayesian decision theory is applied to support multi-criteria decision-making. A decision model is developed that considers stakeholdersʹ different preferences for performance, and risk attitudes are compiled in terms of utility. Case studies emphasize that the ultimate decision should be reached based on multi-criteria comparisons of building environmental and organizational outcomes in a multidimensional and comprehensive manner. Due to the uncertainty of the performance model and the decision model, however, the choosing the decision model without accounting for uncertainty may not be always warranted; in particular, when utilities of decision options do not exhibit significant differences over the utility of the chosen decision option. Besides uncertainty analysis, this study also emphasizes an importance of significant difference testing for decision alternatives as key supplemental measures for the decision support framework under uncertainty.