Lobo Maria Stella de Castro, Estellita Lins Marcos Pereira, Rodrigues Henrique de Castro, Soares Gabriel Martins
Institute for Studies in Public Health (IESC), Federal University of Rio de Janeiro (UFRJ), 21941-598, Avenida Horácio Macedo s/n, Cidade Universitária, lha do Fundão, Rio de Janeiro, Brazil.
Production Engineering Department, CCET, Federal University of the State of Rio de Janeiro (UNIRIO), 22290-240, Av. Pasteur 458, Urca, Rio de Janeiro, Brazil.
Socioecon Plann Sci. 2022 Dec;84:101450. doi: 10.1016/j.seps.2022.101450. Epub 2022 Oct 12.
The COVID-19 pandemic required managerial and structural changes inside hospitals to address new admission demands, frequently reducing their care capacity for other diseases. In this regard, this study aims to support the recovery of hospital productivity in the post-pandemic context. The major challenge will be to make use of all the resources the institution has obtained (equipment, beds, temporarily hired human resources) and to increase production to meet the existing repressed demand. To support evidence-based decision-making at a major university hospital in Rio de Janeiro, hospital managers and operations research analysts designed an approach based on multiple methodologies. Besides multimethodology, one important novelty of this study is the application of a productivity frontier function to future scenario planning through the quantitative DEA methodology. Concept maps were used to structure the problem and emphasize stakeholders' perspectives. In sequence, data envelopment analysis (DEA) was applied, as it combines benchmarking best practices and assigns weights to inputs and outputs. To guarantee that the efficiency measurement considers all inputs and outputs before any inclusion of expert judgment, the scope was redirected to full dimensional efficient facet, if any, or to maximum efficient faces. The results indicate that production scenarios proposed by stakeholders based on the Ministry of Health parameters overestimate the viable production framework and that the scenario that maintains temporary human resource contracts is more compatible with quality in health provision, teaching, and research. These findings will serve as a basis for decision-making by the governmental agency that provided temporary contracts. The present methodology can be applied in different settings and scales.
新冠疫情要求医院内部进行管理和结构变革,以应对新的入院需求,这常常降低了医院对其他疾病的护理能力。在这方面,本研究旨在支持疫情后医院生产力的恢复。主要挑战将是利用该机构所获得的所有资源(设备、床位、临时雇佣的人力资源),并提高产量以满足现有的被压抑的需求。为了支持里约热内卢一家大型大学医院基于证据的决策,医院管理人员和运筹学分析师设计了一种基于多种方法的方法。除了多方法之外,本研究的一个重要新颖之处在于通过定量数据包络分析(DEA)方法将生产力前沿函数应用于未来情景规划。概念图被用于构建问题并强调利益相关者的观点。随后,应用了数据包络分析(DEA),因为它结合了对标最佳实践并为投入和产出赋予权重。为了确保效率测量在纳入任何专家判断之前考虑所有投入和产出,如果有全维有效面,则将范围重新定向到全维有效面,或者到最大有效面。结果表明,利益相关者根据卫生部参数提出的生产情景高估了可行的生产框架,并且维持临时人力资源合同的情景在医疗服务、教学和研究质量方面更具兼容性。这些发现将作为提供临时合同的政府机构决策的依据。本方法可应用于不同的环境和规模。