Designing for resilience: Using a Delphi study to identify resilience issues for hospital designs in a changing climate

Hospitals are facing a triple challenge - meeting mandatory climate change targets and refurbishing aging infrastructure while simultaneously providing quality of care. With the potential of more frequent disruptive weather events, a UK government-funded project was launched in 2009 to investigate practical strategies for the National Health Service to increase its resilience to climate change. This paper presents the process of defining resilience by using the Delphi method and demonstrates its applicability within healthcare design. A Delphi survey is nearing completion which has determined the significant resilience issues and temperature ranges for ideal and critical conditions. Our preliminary findings identified six priorities that lead towards increasing resilience. Using the Delphi method can be a useful tool in clarifying the focus for healthcare design considerations. Copyright © 2002-2012 The Design Society. All rights reserved.

Stress on the ward: evidence of safety tipping points in hospitals

Do hospitals experience safety tipping points as utilization increases, and if so, what are the implications for hospital operations management? We argue that safety tipping points occur when managerial escalation policies are exhausted and workload variability buffers are depleted. Front-line clinical staff is forced to ration resources and, at the same time, becomes more error prone as a result of elevated stress hormone levels. We confirm the existence of safety tipping points for in-hospital mortality using the discharge records of 82,280 patients across six high-mortality-risk conditions from 256 clinical departments of 83 German hospitals. Focusing on survival during the first seven days following admission, we estimate a mortality tipping point at an occupancy level of 92.5%. Among the 17% of patients in our sample who experienced occupancy above the tipping point during the first seven days of their hospital stay, high occupancy accounted for one in seven deaths. The existence of a safety tipping point has important implications for hospital management. First, flexible capacity expansion is more cost-effective for safety improvement than rigid capacity, because it will only be used when occupancy reaches the tipping point. In the context of our sample, flexible staffing saves more than 40% of the cost of a fully staffed capacity expansion, while achieving the same reduction in mortality. Second, reducing the variability of demand by pooling capacity in hospital clusters can greatly increase safety in a hospital system, because it reduces the likelihood that a patient will experience occupancy levels beyond the tipping point. Pooling the capacity of nearby hospitals in our sample reduces the number of deaths due to high occupancy by 34%.