Purpose -The purpose of this paper is to show how the balanced scorecard (BSC) has been a prominent innovation in strategic performance measurement systems. The health care sector has started to adopt this approach. Design/methodology/approach -There are many case studies of BSC applications and this paper reviews this literature to analyse the application of the BSC across this sector. In particular, it is argued that the current applications do not tend to show the health of patients as being central in the development of the BSC; the balance is tilted towards the financial not the health outcomes. BSCs are still in an evolutionary stage in health care settings and strategy mapping is not yet common. Findings -The paper has drawn together and analysed the published cases of BSC in health care. It is possible that some excellent examples of BSC in health care are not yet published or have been missed by this research approach. This analysis was limited by using information from papers which sometimes were very limited. A future research project could investigate the characteristics of unsuccessful implementations -ineffective and short-lived. It is suggested that a more comprehensive view would come from a cross-national survey of best practice use of the BSC in health care; an interesting project for future research. Originality/value -In reviewing the past applications, the paper shows a way forward for future developments of the scorecard in health settings.

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To enable immediate and efficient emergency scheduling during forest fires, we propose a novel emergency scheduling model for such fires subject to priority disaster areas and limited rescue team resources to minimize the total travel distance for rescue teams. Moreover, a hybrid intelligent algorithm integrating genetic algorithm (GA) and particle swarm optimization (PSO) is adopted to solve the proposed model. A case study is presented to illustrate the proposed model and the effectiveness of the proposed algorithm. The goal of this work is to analyze the emergency scheduling problem of forest fires subject to limited rescue teams and priority disaster areas. Both theoretical and simulation results demonstrate that the proposed model can perform effectively the quantitative analysis of an emergency involving forest fires. Such results can help decision makers to make better judgment when dealing with an emergency involving fires.