Influential Factors for Hospital Management Maturity Models in a post-Covid-19 scenario - Systematic Literature Review

The importance of Maturity Models in the health area was proven to support, monitor and direct health organizations to better plan and execute to their investments and developments. In this work, two reviews of the literature were collected: one of them focuses on identifying the main maturity models developed in the health area, the similarities, and gaps between them, identifying which are the Influencing Factors and, the other one, is to identify the lessons learned during the Covid-19 pandemic. In a pandemic scenario, the health sectors demonstrated the importance of the resilience, in which health systems had to adapt abruptly, considering physical structures; professional management; patient safety; supply chain and; technologies. Technologies, played an essential role to mitigating the pressure that health systems faced due to the increase in health costs, growth of chronic diseases, population aging, population’s expectation for more personalized health and, added to that, the confrontation of Covid-19 pandemic. In this sense, we identified the lack of maturity models that address the adversities that occurred during the Covid-19 pandemic in health systems for better hospital management and avoid the pressure to which they could be subjected again.info:eu-repo/semantics/publishedVersio

Inventory Lot Sizing Decisions for Material Requirements Planning to Minimize Inventory Costs

Inventory control is one of the most important factors in achieving optimal organizational performance. Material Requirement Planning (MRP) is a common method used by businesses to manage inventories. This study focuses on a hydraulic firm that has been in operation since 2016. This research examines the planning of eleven components to get the best planning for the company. This study contributes to the integration of Moving Average (MA) and Exponential Smoothing (ES) forecasting techniques alongside the MRP and three lot sizing techniques, such as LFL, EOQ, and LUC. The minimum error values between MA and ES are evaluated and followed by the comparison between three lot sizing techniques. The result shows that ES (α=0.1) is selected as the best forecasting technique, and LUC presents the lowest total inventory cost. However, LUC is only 0.05 percent lower than what LFL presents. A larger difference is shown by EOQ with 14.57 percent higher than LUC which makes EOQ unlikely to be selected