Samuel Martins Drei

1. Modern healthcare systems face unprecedented pressures to deliver high-quality patient care while operating under severe resource constraints. Consequently, improving operational efficiency with...

A integração do Lean Healthcare (LH) com a Análise Envoltória de Dados (DEA) oferece potencial significativo para aprimorar a eficiência hospitalar, contudo, abordagens metodológicas robustas que unifiquem ambas ainda são limitadas na literatura. Este estudo tem como objetivo aplicar uma abordagem Lean-DEA integrada de quatro estágios em hospitais públicos brasileiros, visando a melhoria de processos e o aumento da eficiência. Para tanto, utiliza-se um novo conjunto de variáveis (Repasse Financeiro do SUS, Número de Leitos de UTI como inputs; Número de Procedimentos de Alta Complexidade como output) e parâmetros (modelo SBM-DEA com orientação a outputs e Retornos Constantes de Escala). A metodologia compreende: (1) Construção de Perfis Hospitalares Lean; (2) Avaliação inicial da eficiência; (3) Refinamento da análise com o cálculo de DMUs Ideais, utilizando o Ajuste Ideal Lean-DEA com limiar de 50%; e (4) Geração de direcionamentos estratégicos baseados nos benchmarks. A aplicação em 30 DMUs (representando 16 hospitais) demonstrou a adaptabilidade da abordagem, resultando em uma análise contextualizada da eficiência e na formulação de recomendações customizadas para as unidades ineficientes, considerando suas experiências prévias e as melhores práticas identificadas.

Purpose: Propose an integrated approach of Lean Healthcare (LH) with Data Envelopment Analysis (DEA), establishing best practices for waste reduction and process improvement along with hospital efficiency. Design/methodology/approach: The study proposes a two-stage approach integrating LH and DEA to enhance hospital efficiency. The first stage identifies efficient hospitals post-LH implementation and projects efficiency for inefficient ones using ideal projections. In the second stage, a new DEA model applies to established extreme-efficient hospital sets, guiding LH technique selection for continuous improvement. This approach is tested on six Brazilian public hospitals before and after LH application (HA and HD, respectively), offering strategic insights for decision-making. The inclusion of ideal DMUs adds a dynamic dimension, projecting future efficiency and guiding inefficient hospitals toward effective practices. Findings: The results confirmed the approach’s effectiveness, providing performance metrics and strategic guidance for healthcare service enhancement. Utilizing non-oriented SBM-DEA in the first stage determined DMU efficiency, revealing both efficient and inefficient hospitals post-Lean implementation. The approach extended beyond efficiency assessment by proposing ideal DMUs for inefficient hospitals. This refinement allowed a comprehensive analysis, considering real DMUs and ideal projections, emphasizing the approach’s holistic evaluative capability. Research limitations/implications: The main limitation of this study lies in the restricted set of hospitals analyzed. Since the sample consisted of a limited number of institutions, the selection of inputs and outputs used in the Lean-DEA model was constrained by the availability of data provided by these hospitals. As a result, some potentially relevant variables for evaluating efficiency and Lean practice adoption could not be included in the analysis, which may have affected the comprehensiveness of the results. Additionally, the use of ideal DMUs generated from a mathematical optimization process – without orientation to the specific context of healthcare – may lead to the suggestion of target values that are unrealistic or unattainable for actual hospitals. Practical implications: The findings of this research provide a decision-support tool in scenarios marked by budget constraints and high demand for services. The application of the Lean-DEA model makes it possible to identify underperforming units and determine which managerial practices can be incorporated based on internal benchmarks within the healthcare system. As a result, managers gain access to a more accurate, evidence-based approach to guide interventions and strategically allocate resources, enhancing the efficiency and quality of services delivered to the population. Social implications: The potential benefits of applying the Lean-DEA approach are directly reflected in improved healthcare services. More efficient hospitals can deliver faster, higher-quality care with reduced waste, which positively impacts the experience of users of the public health system. By contributing to the optimization of hospital processes, this research also supports the strengthening of the healthcare system as a whole, promoting greater equity in access and better public health outcomes. Originality/value: The study innovatively integrates LH and DEA, introducing ideal DMUs in this context. The target analysis highlights the consistent reference of ideal projections, even compared to potential alternative outcomes, offering a unique contribution not found in existing literature.

The main goal of this study is to determine the relative efficiency of the application of Lean Healthcare, based on a set of Brazilian public hospitals, using Data Envelopment Analysis (DEA). The study methodology consisted of establishing na analysis of the efficiency of Lean Healthcare, comparing the hospitals that applied it before and after, establishing the time and displacement as inputs and value as output, expressed in number of hospitalizations, to simulate the development conditions of the Lean in health. For this, the non-oriented SBM-DEA model was used, simulating the conditions of the medical clinics of the established DMUs. As a result, it was possible to observe that the hospitals were all inefficient before the application of Lean and had na improvement in efficiency after the application, but only a part actually became efficient. Thus, it is concluded that a metric that aligns the development of the Lean Healthcare application with DEA may be interesting, given the possibility of improvement arising from the benchmarks for the group of hospitals that remained inefficient.

The purpose of this paper is to applied systematically Lean Healthcare to improve mobility accessibility in the medical clinic ward of a medium-sized hospital.

The purpose of this paper is to prioritize which waste should be treated by Lean Healthcare in a medical clinic of a middle-sized Brazilian hospital, using the multicriteria decision support method THOR 2. It focusses on structuring the problem, establishing alternatives through the study hospital and Lean interventions already made in it, and determining the criteria and parameters of THOR 2 with the help of Value Focus Thinking (VFT) and the hospital directors. THOR 2 was able to identify, taking into account its preference relationships in S2, that establishing a Kanban within the hospital’s medical clinic is the preferred and the main contribution and novelty to the literature is the way that multicriteria methods can help in Lean Healthcare decision making. As conclusions, it was possible to establish a prioritization order, maintaining the concept of continuous improvement, arising from Lean Healthcare, while respecting the limits and restrictions of the hospital.

The paper presents a structured approach to address decision-making challenges within the medical clinic service of a mid-sized hospital located in Brazil, using Soft System Methodology (SSM). Its application extends to the medical clinic, a previously unexplored domain within the hospital. Within this context, we introduce a novel conceptual framework for healthcare, wherein we integrate Plan-Do-Check-Act (PDCA) tool into SSM framework. The overarching goal is to rectify the pivotal issue of excessive workload allocation among the medical clinic staff. The developed model effectively addresses this issue by optimizing task allocation. It achieves this by designating primary and auxiliary nursing staff for specific sets of tasks, taking into consideration the necessity for displacement and ensuring a fair distribution of workloads. Furthermore, our model incorporates PDCA into the implementation phase of SSM, thereby establishing a mechanism for ongoing improvement in the initial equilibrium achieved in terms of staff deployment and task distribution.

Purpose: The objective of this paper is to propose a systematic application of Lean Healthcare in the hospitalization activity in the medical clinic entry process.Design/methodology/approach: The methodology used is established in three stages: the first aims to map the process in which the focus activity is inserted, using lean tools, as well as integrating the employees involved in the application. The second is the proposal to apply the systematic, together with the employees, using the A3 tool step by step. Finally, the third stage confirms the applied systematic, collecting the results and analyzing the initial situation with those reached.Findings: As a result, improvements were made in the medical clinic entry process, such as reduced waiting time for patients, at approximately 53.8%, with a decrease in the standard deviation of the times – of approximately 79.14%, and displacement of those involved, of 72%, in addition to eliminating unnecessary activities for the process. Furthermore, the empirical results on the efficiency of this systemic application in medical clinic enable the replication of this proposal, generating a systematic.Research limitations/implications: Despite establishing a systematic proposal with real results, it is focused on only one application, due to time limitations, may generate a subjective evaluation of the systematic. Thus, for future research, it is recommended to expand this systemic application in other activities of different processes.Practical implications: The practical implications of this paper are precisely related to the data obtained with the application made, developing a Lean Healthcare systematic not previously seen, which is strategic, systemic and has a roadmap to assist in its application and, in addition, brings with it practical results that prove their efficiency.Social implications: The social implications of this paper are presented in its empirical results, considering that the study hospital serves, in addition to its host city, 28 other smaller municipalities around it, improving the flow of processes, ensuring better management of the clinic doctor. In addition, the results can assist the processes flow of other medical clinics in hospitals around the world, especially at critical moments, such as pandemics or epidemics.Originality/value: Due to the positive results obtained in the systematic application, this paper fills a gap identified in the literature, proposing a systematic application of Lean Healthcare that is systemic and strategic, in addition to including a roadmap and analysis of data applied in a medium-sized Brazilian hospital, presenting positive practical results exposed in the paper.