Lean healthcare: improving surgical process indicators through prioritization projects

Purpose: Implementing process management methodology through Lean Management and Design Thinking provides a new way to manage surgical blocks, maximize efficiency and adapt to the high variability of demand. This article presents our experience of implementing a set of improvement actions within the surgical process in the context of Lean Healthcare Processes. The project involved a total of 900 healthcare professionals over a 3-year period (2017-2019) and has impacted over 38,000 surgical patients each year at the Vall d’Hebron University Hospital in Barcelona, Spain. The purpose of this article is to present a set of improvement projects within the surgical process and show the indicators that monitor its evolution. These projects have been implemented successfully in a hospital with high surgical complexity and indicate how health care professionals and process engineers can work together as a team to improve healthcare resources. Design/methodology/approach: To evaluate the effectiveness of the actions presented, we propose a series of standardized indicators showing how our findings increase the efficiency of the surgical process. We also indicate Lean projects that can reduce patient waiting times and increase capacity. Below is a management model for the surgical process that considers industrial production criteria such as resource planning, optimizing the use of operating rooms and professionals’ time and generating the best surgery combinations. Findings: Projects that have increased efficiency in the surgical block the most have been standardized and converted into a model of action. This is designed to adapt to any level of complexity within the hospital process. The set of improvement projects has been divided into 6 stages: Programming, Material logistics process, pre-surgical stage, intra-surgical stage, post-surgical stage and transversal projects; each affecting a different area of the general hospital (not only the surgical unit). Furthermore, a visual flow chart was designed using the results of the project. Findings from the study have led to a 15% increase in surgical capacity without the need for new resources. The average hospital stay also dropped from 7.2 days to 4.1 days. The flow vision in the care process improves the experience of both patients and health care professionals, who see their participation as part of the whole health care process. Research limitations/implications: the projects were mainly developed at the Vall d’Hebron University Hospital. Although several of these projects have been carried out in other hospitals in Spain by the same team of process engineers, results may be biased when the team provides support within its own process department, compared to when it supports the local team in another hospital temporarily. Another important limitation is that it takes several months to implement and consolidate the improvement projects and demonstrate improved indicators in a sustainable way over time. This matrix of projects is more than a specific action, a cultural change with the entire surgical department. Originality/value: This study sets out a proposed practical example of applying surgery management tools in the surgical process. Our proposal can offer hospital managers and surgical coordinators an orderly, streamlined project guide for overall surgical performance indicators. The main results from developing the model include the degree of satisfaction shown by healthcare professionals and the determined commitment from the center’s management team to promote process management using Lean methodology. This commitment continued despite the challenges of shifting the organizational structure towards process management, which is a complex task requiring a period of adaptation and learning. Healthcare management has always prioritized increasing surgical patient safety and satisfaction. Patient flows are increased and resources used more efficiency by shifting the focus to the patient and the processes gone through during their hospital stay. This improvement project provides us with the best example of Lean methodology implementation if reinvested in bettering healthcare. This in turn increases the value perceived by patients, which is the ultimate purpose of the processPeer Reviewe

Knowledge management for small and medium contractors

Effective knowledge management is increasingly considered as a cornerstone of sustainable business success. Knowledge management systems are strategically valuable for both ensuring consistency and continuous improvement of various aspects such as quality delivery, productivity and competitiveness. The small and medium enterprises (SMEs) in the construction industry are mostly operating under tighter timeframes, narrower profit margins and more constrained resources. Hence the recently commenced SMILE-SMC (Strategic Management with Information Leveraged Excellece for Small and Medium Contractors) project aims to support the information and knowledge management needs of the small and medium contractors in Hong Kong. This paper presents some snapshots on the SMILE-SMC project, and its conceptualized deliverables with some highlights of recent developments.postprin

Australian Lamb Supply Chain: A Conceptual Framework

In the last decade, supply chain management has played an important role to lead agribusiness today to succeed in their business goals, to gain competitive advantages, and to improve business performance. As the result of that, there has been extensive studying in a popular topic of strategic supply chain management in order to improve business performance as well as along supply chain performance under the real situation. This is because in current business world, supply chain practices are crucial to influence many agribusinesses to continuously adapt proper supply chain management in their nature of business. This paper will propose a conceptual framework of supply chain practices and supply chain performance indicators of the Australian Lamb Industry.Lamb Supply Chain, Supply Chain Management, Livestock Production/Industries,

Healthcare Management Primer

This primer was written by students enrolled in HMP 721.01, Management of Health Care Organizations, in the Health Management & Policy Program, College of Health and Human Services, University of New Hampshire. This course was taught by Professor Mark Bonica in Fall 2017

The impact of Green Information Systems on sustainable supply chain and organizational performance

This paper reports about a research in progress focusing on the impact of green information systems on sustainable supply chain performance. Green information systems, supply chains and their relation to sustainability and performance measurement are explained. The preliminary literature review resulted in a draft conceptual framework where sustainable supply chain measures focusing on economic, environmental and social aspects are combined with traditional supply chain performance measures of cost, quality, dependability, flexibility and speed. The measures for the triple bottom line of sustainability are listed as internal and external indicators. The research challenges addressed in this preliminary work comprise of integration of sustainability performance with traditional performance objectives in the supply chain, measurement of the social performance of supply chain and establishment of the relationship amongst the sustainable supply chain and performance indicators using a green information system infrastructure

Identifying and Prioritizing the Effective Criteria in Selecting Lean Six Sigma Improvement Projects in the Healthcare Sector

[EN] The main objective of this study was to identify and prioritize effective criteria in selecting Lean Six Sigma improvement projects in the healthcare and treatment sector in Iran. The present study was an applied research in terms of objective and a descriptive and analytical one according to the research methodology and data collection approach. The research statistical population included experts and managers with experience in the field of implementing the lean six sigma methodology in the field of healthcare and treatment in Iran. We used interviews and questionnaire tools to collect the data. The effective criteria were identified through reviewing previous research, which were then prioritized based on the experts’ opinions using the BWM method. According to the results, out of the six main dimensions and 20 criteria identified, the customer development dimension with a weight of 0.387 and the customer satisfaction criterion with a weight of 0.066 were determined as the most effective dimension and the most effective criterion, respectively. Accordingly, the directors of medical centers and organizations affiliated with the healthcare sector are recommended to pay special attention to these defined criteria of the customer development dimension to effectively implement the lean six sigma methodology and managing an effective customer relationship.Bazrkar, A.; Aramoon, V.; Aramoon, E. (2021). Identifying and Prioritizing the Effective Criteria in Selecting Lean Six Sigma Improvement Projects in the Healthcare Sector. WPOM-Working Papers on Operations Management. 12(2):41-55. https://doi.org/10.4995/wpom.15766OJS4155122Ahmed, S., Abd Manaf, N. H., & Islam, R. (2018). Effect of Lean Six Sigma on quality performance in Malaysian hospitals. International journal of health care quality assurance,13(8),973-987. https://doi.org/10.1108/IJHCQA-07-2017-0138Antony, J., Rodgers, B., & Gijo, E. V. (2016). Can Lean Six Sigma make UK public sector organisations more efficient and effective?. International Journal of Productivity and Performance Management,65(7),995-1002. https://doi.org/10.1108/IJPPM-03-2016-0069Aramoon, V., Aramoon, E., & Bazrkar, A. (2020). Investigating the Effect of Implementing the Lean Six Sigma on Organizational Performance Based on the Mediating Role of Strategic Knowledge Management with Structural Equation Modeling Approach. Navus-Revista de Gestão e Tecnologia, 10, 01-16. https://doi.org/10.22279/navus.2020.v10.p01-16.1302Assarlind, M., & Aaboen, L. (2014). Forces affecting one Lean Six Sigma adoption process. International Journal of Lean Six Sigma,5(3),324-340. https://doi.org/10.1108/IJLSS-07-2013-0039Bazrkar, A., & Iranzadeh, S. (2017). Prioritization of Lean Six Sigma improvement projects using data envelopment analysis cross efficiency model. Quality - Access to Success, 18(157), 72-76.Bhat, S., Antony, J., Gijo, E. V., & Cudney, E. A. (2019). Lean Six Sigma for the healthcare sector: a multiple case study analysis from the Indian context. International Journal of Quality & Reliability Management.,37(1),90-111. https://doi.org/10.1108/IJQRM-07-2018-0193Bumjaid, S. E., & Malik, H. A. M. (2019). The Effect of Implementing of Six Sigma Approach in Improving the Quality of Higher Education Institutions in Bahrain. International Journal of Engineering and Management Research, 9,12-27. https://doi.org/10.31033/ijemr.9.2.17de Miranda Lammoglia, J. A., Brandalise, N., & Hernandez, C. T. (2020). Analytical hierarchy processbocr applied for the best lean project selection for production lines. Independent Journal of Management & Production, 11(1), 054-064. https://doi.org/10.14807/ijmp.v11i1.990Erdil, N. O., Aktas, C. B., & Arani, O. M. (2018). Embedding sustainability in lean six sigma efforts. Journal of Cleaner Production, 198, 520-529. https://doi.org/10.1016/j.jclepro.2018.07.048Gupta, H., & Barua, M. K. (2016). Identifying enablers of technological innovation for Indian MSMEs using best-worst multi criteria decision making method. Technological Forecasting and Social Change, 107, 69-79. https://doi.org/10.1016/j.techfore.2016.03.028Gupta, P., Anand, S., & Gupta, H. (2017). Developing a roadmap to overcome barriers to energy efficiency in buildings using best worst method. Sustainable Cities and Society, 31, 244-259. https://doi.org/10.1016/j.scs.2017.02.005Gupta, S., Modgil, S., & Gunasekaran, A. (2020). Big data in lean six sigma: a review and further research directions. International Journal of Production Research, 58(3), 947-969. https://doi.org/10.1080/00207543.2019.1598599Guo, S., & Zhao, H. (2017). Fuzzy best-worst multi-criteria decision-making method and its applications. Knowledge-Based Systems, 121, 23-31. https://doi.org/10.1016/j.knosys.2017.01.010Henrique, D. B., & Godinho Filho, M. (2020). A systematic literature review of empirical research in Lean and Six Sigma in healthcare. Total Quality Management & Business Excellence, 31(3-4), 429-449. https://doi.org/10.1080/14783363.2018.1429259Improta, G., Cesarelli, M., Montuori, P., Santillo, L. C., & Triassi, M. (2018). Reducing the risk of healthcare‐associated infections through Lean Six Sigma: The case of the medicine areas at the Federico II University Hospital in Naples (Italy). Journal of evaluation in clinical practice, 24(2), 338-346. https://doi.org/10.1111/jep.12844Kadarova, J., & Demecko, M. (2016). New approaches in lean management. Procedia Economics and Finance, 39(1), 11-16. https://doi.org/10.1016/S2212-5671(16)30234-9Laureani, A., & Antony, J. (2017). Leadership characteristics for lean six sigma. Total Quality Management & Business Excellence, 28(3-4), 405-426. https://doi.org/10.1080/14783363.2015.1090291Li, J., Wang, J. Q., & Hu, J. H. (2019). Multi-criteria decision-making method based on dominance degree and BWM with probabilistic hesitant fuzzy information. International Journal of Machine Learning and Cybernetics, 10(7), 1671-1685. https://doi.org/10.1007/s13042-018-0845-2Lizarelli, F. L., & Alliprandini, D. H. (2020). Comparative analysis of Lean and Six Sigma improvement projects: performance, changes, investment, time and complexity. Total Quality Management & Business Excellence, 31(3-4), 407-428. https://doi.org/10.1080/14783363.2018.1428087Maghsoodi, A. I., Mosavat, M., Hafezalkotob, A., & Hafezalkotob, A. (2019). Hybrid hierarchical fuzzy group decision-making based on information axioms and BWM: Prototype design selection. Computers & Industrial Engineering, 127, 788-804. https://doi.org/10.1016/j.cie.2018.11.018Malek, J., & Desai, T. N. (2019). Prioritization of sustainable manufacturing barriers using Best Worst Method. Journal of Cleaner Production, 226, 589-600. https://doi.org/10.1016/j.jclepro.2019.04.056Marodin, G. A., Frank, A. G., Tortorella, G. L., & Saurin, T. A. (2016). Contextual factors and lean production implementation in the Brazilian automotive supply chain. Supply Chain Management: An International Journal,21(4),417-432. https://doi.org/10.1108/SCM-05-2015-0170Mason, S. E., Nicolay, C. R., & Darzi, A. (2015). The use of Lean and Six Sigma methodologies in surgery: A systematic review. The Surgeon, 13(2), 91-100. https://doi.org/10.1016/j.surge.2014.08.002McCann, L., Hassard, J. S., Granter, E., & Hyde, P. J. (2015). Casting the lean spell: The promotion, dilution and erosion of lean management in the NHS. Human Relations, 68(10), 1557-1577. https://doi.org/10.1177/0018726714561697Mi, X., Tang, M., Liao, H., Shen, W., & Lev, B. (2019). The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?. Omega, 87, 205-225. https://doi.org/10.1016/j.omega.2019.01.009Morell-Santandreu, O., Santandreu-Mascarell, C., & Garcia-Sabater, J. J. (2021). A Model for the Implementation of Lean Improvements in Healthcare Environments as Applied in a Primary Care Center. International Journal of Environmental Research and Public Health, 18(6), 2876. https://doi.org/10.3390/ijerph18062876Morell-Santandreu,O., Santandreu-Mascarell, C., & García-Sabater, J. (2020). Sustainability and Kaizen: Business Model Trends in Healthcare. Sustainability, 12(24), 10622. https://doi.org/10.3390/su122410622Mrugalska, B., & Wyrwicka, M. K. (2017). Towards lean production in industry 4.0. Procedia Engineering, 182, 466-473. https://doi.org/10.1016/j.proeng.2017.03.135Naumovich, A. (2020). The Japanese concept of lean production: possibility of implementation in the Belarusian economy,http://edoc.bseu.by/.Okpala, C. C., Obiuto, N. C., & Elijah, O. C. (2020). Lean Production System Implementation in an Original Equipment Manufacturing Company: Benefits, Challenges, and Critical Success Factors. International Journal of Engineering Research & Technology,9(7),1665-1672.Pakdil, F., Toktaş, P. and Can, G.F. (2020), Six sigma project prioritization and selection: a multi-criteria decision making approach in healthcare industry,International Journal of Lean Six Sigma, Vol. ahead-ofprint No. ahead-of-print. https://doi.org/10.1108/IJLSS-04-2020-0054Pamučar, D., Petrović, I., & Ćirović, G. (2018). "Modification of the Best-Worst and MABAC methods: A novel approach based on interval- valued fuzzy-rough numbers. Expert Systems with Applications, 91, 89-106. https://doi.org/10.1016/j.eswa.2017.08.042Rahul, G., Samanta, A. K., & Varaprasad, G. (2020, July). A Lean Six Sigma approach to reduce overcrowding of patients and improving the discharge process in a super-specialty hospital. In 2020 International Conference on System, Computation, Automation and Networking (ICSCAN) (pp. 1-6). IEEE.Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57. https://doi.org/10.1016/j.omega.2014.11.009Rezaei, J., van Roekel, W. S., & Tavasszy, L. (2018). Measuring the relative importance of the logistics performance index indicators using Best Worst Method. Transport Policy, 68, 158-169. https://doi.org/10.1016/j.tranpol.2018.05.007Sá, J. C., Vaz, S., Carvalho, O., Lima, V., Morgado, L., Fonseca, L., ... & Santos, G. (2020). A model of integration ISO 9001 with Lean six sigma and main benefits achieved. Total Quality Management & Business Excellence, 1-25. https://doi.org/10.1080/14783363.2020.1829969Shenshinov, Y., & Abdulsattar Al-Ali. (2020). THE TOOLS OF INCREASING EFFICIENCY OF HUMAN RESOURCE IN THE LEAN PRODUCTION ENVIRONMENT: CONCEPTUAL STUDY. International Journal of Core Engineering & Managenet,6(7),1-18.Singh,M.,Rathi,R.,Antony,J.,Garza-Reyes,J.A.(2021).L Lean Six Sigma Project Selection in a Manufacturing Environment Using Hybrid Methodology Based on Intuitionistic Fuzzy MADM Approach, IEEE Transactions on Engineering Management, doi: 10.1109/TEM.2021.3049877. https://doi.org/10.1109/TEM.2021.3049877Sunder, M. V. (2013). Synergies of lean six sigma. IUP Journal of Operations Management, 12(1), 21.Sunder., M, V., & Kunnath, N. R. (2020). Six Sigma to reduce claims processing errors in a healthcare payer firm. Production Planning & Control, 31(6), 496-511. https://doi.org/10.1080/09537287.2019.1652857Swarnakar, V., & Vinodh, S. (2014). Lean Six Sigma Project Selection using Analytical Network Process. 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Towards Leaner Healthcare Facility: Application of Simulation Modelling and Value Stream Mapping

Recently, the application of lean thinking in healthcare has grown significantly in response to rising demand caused by population growth, ageing and high expectations of service quality. However, insufficient justifications and lack of quantifiable evidence are the main obstacles to convince healthcare executives to adopt lean. Therefore, this paper presents a methodology that integrates lean tools with simulation to enhance the quality of patient care in healthcare facilities. This enables healthcare organisations to dedicate more time and effort to patient care without extra cost to the organisation or to the patient. Value stream mapping is used to identify value-added and non-value-added activities.. Then, a comprehensive simulation model is developed to account for the variability and complexity of healthcare processes and to assess the gains of proposed improvement strategies. An extensive analysis of results is provided and presented to managers to illustrate the potential benefits of adapting lean practices

AN ANALYSIS OF HOW THE U.S. GOVERNMENT CAN EFFECTIVELY TACKLE SUPPLY CHAIN BARRIERS TO SCALE UP THE LOW COST UNMANNED AERIAL VEHICLE (UAV) SWARMING TECHNOLOGY (LOCUST) PROGRAM

The LOCUST program is a scalable system of inexpensive swarming unmanned aerial vehicles to provide disruptive capability in contested environments against anti-area access denial defenses, enabling manned strike operations and localized landing site superiority with reduced cost, risk, and operator launch and workload. Our research and analysis will emphasize the challenges of moving from a U.S. Special Operations Command (USSOCOM) effort to a large program of record. Specific supply chain concerns that will be addressed include: 1) DOD organizational structure; 2) service-specific objectives and currently operating platforms; 3) requirements generation and related procurements to include production and quality challenges; 4) safety and quality assurance standards; 5) lead times, inventory plans, and throughput to include supplier base considerations and consolidations; and 6) latest evolving technologies and continuous improvement principles. Our team will utilize the Define, Measure, Analyze, Improve, Control (DMAIC) evaluative methodology that focuses on data-driven improvement cycles to better optimize process, design and results. Our results and recommendations highlighted multiple strategies that the Office of Naval Research (ONR) must focus on when developing the LOCUST supply chain. These conclusions and findings address both current supply chain development opportunities for the LOCUST program, as well as where the program must focus its efforts in the future.http://archive.org/details/ananalysisofhowt1094563516Civilian, Department of the NavyCivilian, Department of the ArmyCivilian, Department of the ArmyApproved for public release; distribution is unlimited