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Using Constraint Satisfaction Problem approach to solve human resource allocation problems in cooperative health services

机译:使用约束满足问题方法解决合作医疗服务中的人力资源分配问题

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In developing countries, the increasing utilization of health services, due to a great life expectancy, is followed by a reduction in incomes from the public health system and from private insurance companies, to the payment of medical procedures. Beyond this scenery, it is mandatory an effective hospital cost control though the utilization of planning tools.This work is intended to contribute to the reduction of hospital costs, proposing a new tool for planning human resources utilization in hospital plants. Specifically, it is proposed a new tool for human resources allocation in health units. The solution to the allocation problem uses the CSP technique (Constraint Satisfaction Problem) associated with the backtracking search algorithm. With the objective of enhancing the backtracking search algorithm performance a new heuristics is proposed. Through some simulations the performance of the proposed heuristics is compared to the other heuristics previously published in literature: remaining minimum values, forward checking and grade heuristics.Another important contribution of this work is the mathematical modeling of the constraints, that could be unary, multiple, numeric and implicit constraints. In the results it is presented a case study of a human resource allocation in a cooperative health service.Based on the results, it is proposed that for a real allocation problems solution, the best approach is to combine the remaining minimum values heuristics with the grade heuristics, to select the best unit allocation to be filled, and then use the proposed heuristic to select the best physician to the chosen unit allocation. This association shows a satisfactory result for the human resource allocation problem of the case study, with an algorithm convergence time of 46.7 min with no backtracks. The same problem when manually resolved took about more than 50 h.
机译:在发展中国家,由于预期寿命长,医疗服务的利用增加,其次是公共卫生系统和私人保险公司的收入减少,以及用于医疗程序的收入减少。除此以外,还必须通过使用规划工具来有效控制医院成本。这项工作旨在降低医院成本,为规划医院工厂的人力资源使用提出了新的工具。具体而言,提出了一种用于卫生部门人力资源分配的新工具。分配问题的解决方案使用与回溯搜索算法相关联的CSP技术(约束满意度问题)。为了提高回溯搜索算法的性能,提出了一种新的启发式算法。通过一些模拟,将提议的启发式算法的性能与先前在文献中发表的其他启发式算法进行了比较:剩余最小值,正向检查和等级启发式算法。这项工作的另一个重要贡献是约束的数学建模,可能是一元的,多重的,数字和隐式约束。在结果中,提出了一项关于合作医疗机构人力资源分配的案例研究。基于结果,提出对于一个实际分配问题的解决方案,最佳方法是将剩余的最小值启发式方法与等级结合起来启发式,以选择要填充的最佳单位分配,然后使用提议的启发式来为所选单位分配选择最佳医师。这种关联对于案例研究中的人力资源分配问题显示出令人满意的结果,算法收敛时间为46.7分钟,没有回溯。手动解决时,相同的问题大约花费了50多个小时。

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