Objectives: To assess the effects of lean healthcare (LH) on patient flow in ambulatory care and determine whether waiting time and length of stay (LOS) decrease after LH interventions. Methods: A systematic review was performed with close adherence to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). We searched for studies of healthcare organizations applying LH interventions within ambulatory care published between 2002 and 2018. Six databases and grey literature sources were used. Two reviewers independently screened and assessed each study. When consensus was difficult to reach, a third reviewer intervened. Finally, a summary of findings was generated. Results: Out of 5627 studies, 40 were included. Regarding LOS for all patients, 19 out of 22 studies reported a decrease. LOS for discharged patients decreased in 11 out of 13 studies, whereas LOS for admitted patients was reduced in 6 out of 7 studies. Waiting time for patients before seeing a healthcare professional decreased in 24 out of 26 studies. Waiting time to treatment and waiting time for appointments were minimized in 4 and 2 studies, respectively. Patients who left without being seen by a doctor decreased in 9 out of 12 studies. Finally, patient and staff satisfaction were measured in 8 and 2 studies, respectively, with each reporting improvements. Conclusions: According to our findings, LH helped to reduce waiting time and LOS in ambulatory care, mainly owing to its focus on identifying and minimizing non-value added (NVA) activities. Nevertheless, evidence of the impact of LH on patient/ staff satisfaction and the translation of the obtained benefits into savings is scarce among studies.

The multiobjective optimization on the basis of ratio analysis (MOORA) method captures diverse features such as the criteria and alternatives of appraising a multiple criteria decision-making (MCDM) problem. At the same time, the multiple criteria problem includes a set of decision makers with diverse expertise and preferences. In fact, the literature lists numerous approaches to aid in this problematic task of choosing the best alternative. Nevertheless, in the MCDM field, there is a challenge regarding intangible information which is commonly involved in multiple criteria decision-making problem; hence, it is substantial in order to advance beyond the research related to this field. Thus, the objective of this paper is to present a fused method between multiobjective optimization on the basis of ratio analysis and Pythagorean fuzzy sets for the choice of an alternative. Besides, multiobjective optimization on the basis of ratio analysis is utilized to choose the best alternatives. Finally, two decision-making problems are applied to illustrate the feasibility and practicality of the proposed method.

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<p class="ADYNAAbstrac"><span lang="EN-US">The supplier selection is a critical activity within the administration of the supply chain. It is considered a complex problem given that it involves different aspects such as the alternatives to evaluate, the multiple criteria involved as well as the group of decision makers with different opinions. In this sense, the literature reports several methods to help in this difficult activity of selecting the best supplier. However, there are still some gaps in these methods; therefore, it is imperative to further develop research. Thus, the purpose of this paper is to report a hybrid method between MOORA and intuitionistic fuzzy sets for the selection of suppliers with a focus on multi-criteria and multi-group environment. The importance of decision makers, criteria and alternatives are evaluated in terms of intuitionistic fuzzy sets. Then, MOORA is used in order to determine the best supplier. An experimental case is developed in order to explain the proposed method in detail and to demonstrate its practicality and effectiveness.</span></p>