Generating Options for Active Risk Control (GO-ARC): introducing a novel technique.

BACKGROUND: After investing significant amounts of time and money in conducting formal risk assessments, such as root cause analysis (RCA) or failure mode and effects analysis (FMEA), healthcare workers are left to their own devices in generating high-quality risk control options. They often experience difficulty in doing so, and tend toward an overreliance on administrative controls (the weakest category in the hierarchy of risk controls). This has important implications for patient safety and the cost effectiveness of risk management operations. This paper describes a before and after pilot study of the Generating Options for Active Risk Control (GO-ARC) technique, a novel tool to improve the quality of the risk control options generation process. OUTCOME MEASURES: The quantity, quality (using the three-tiered hierarchy of risk controls), variety, and novelty of risk controls generated. RESULTS: Use of the GO-ARC technique was associated with improvement on all measures. CONCLUSIONS: While this pilot study has some notable limitations, it appears that the GO-ARC technique improved the risk control options generation process. Further research is needed to confirm this finding. It is also important to note that improved risk control options are a necessary, but not sufficient, step toward the implementation of more robust risk controls.

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%.