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Souza DL, Korzenowski AL, Alvarado MM, Sperafico JH, Ackermann AEF, Mareth T, Scavarda AJ. A Systematic Review on Lean Applications' in Emergency Departments. Healthcare (Basel) 2021; 9:healthcare9060763. [PMID: 34205337 PMCID: PMC8235665 DOI: 10.3390/healthcare9060763] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/05/2021] [Accepted: 06/12/2021] [Indexed: 11/18/2022] Open
Abstract
This article presents the state of the art of Lean principles applied in Emergency Departments through a systematic literature review. Our article extends previous work found in the literature to respond to the following questions: (i) What research problems in emergency departments can Lean principles help overcome? (ii) What Lean approaches and tools are used most often in this environment? (iii) What are the results and benefits obtained by these practices? and (iv) What research opportunities appear as gaps in the current state of the art on the subject? A six-step systematic review was performed following the guidance of the PRISMA method. The review analysis identified six main research problems where Lean was applied in Emergency Departments: (i) High Waiting Time and High Length of Hospital Stay; (ii) Health Safety; (iii) Process redesign; (iv) Management and Lessons Learned; (v) High Patient Flow; (vi) Cost Analysis. The six research problems’ main approaches identified were Lean Thinking, Multidisciplinary, Statistics, and Six Sigma. The leading Lean tools and methodologies were VSM, Teamwork, DMAIC, and Kaizen. The main benefits of applying Lean Principles were (a) reductions in waiting time, costs, length of hospital stay, patient flow, and procedure times; and (b) improvements in patient satisfaction, efficiency, productivity, standardization, relationships, safety, quality, and cost savings. Multidisciplinary integration of managers and work teams often yields good results. Finally, this study identifies knowledge gaps and new opportunities to study Lean best practices in healthcare organizations.
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Affiliation(s)
- Davenilcio Luiz Souza
- Industrial & Systems Engineering Department, Polytechnic School, University of Vale do Rio dos Sinos, São Leopoldo 93022-750, RS, Brazil; (D.L.S.); (J.H.S.); (A.E.F.A.)
| | - André Luis Korzenowski
- Industrial & Systems Engineering Department, Polytechnic School, University of Vale do Rio dos Sinos, São Leopoldo 93022-750, RS, Brazil; (D.L.S.); (J.H.S.); (A.E.F.A.)
- Accounting Department, School of Management and Business, University of Vale do Rio dos Sinos, Porto Alegre 91330-002, RS, Brazil;
- Correspondence: ; Tel.: +55-51-99163-6371
| | - Michelle McGaha Alvarado
- Industrial & Systems Engineering Department, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL 32611, USA;
| | - João Henrique Sperafico
- Industrial & Systems Engineering Department, Polytechnic School, University of Vale do Rio dos Sinos, São Leopoldo 93022-750, RS, Brazil; (D.L.S.); (J.H.S.); (A.E.F.A.)
| | - Andres Eberhard Friedl Ackermann
- Industrial & Systems Engineering Department, Polytechnic School, University of Vale do Rio dos Sinos, São Leopoldo 93022-750, RS, Brazil; (D.L.S.); (J.H.S.); (A.E.F.A.)
| | - Taciana Mareth
- Accounting Department, School of Management and Business, University of Vale do Rio dos Sinos, Porto Alegre 91330-002, RS, Brazil;
| | - Annibal José Scavarda
- Department of Production Engineering, Center for Exact Sciences and Technology, Federal University of the State of Rio de Janeiro, Rio de Janeiro 22290-255, RJ, Brazil;
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Whitt CE, Tauer LW, Huson H. Bull efficiency using dairy genetic traits. PLoS One 2019; 14:e0223436. [PMID: 31710626 PMCID: PMC6844452 DOI: 10.1371/journal.pone.0223436] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 09/20/2019] [Indexed: 11/22/2022] Open
Abstract
Dairy bulls are evaluated using progeny data and genomic testing to determine the quantity of specific traits that they will pass to their daughters. Some bulls excel in some traits but not others. Specifying these various traits as outputs, with the single input of insemination, technical, revenue, allocative, and profit efficiency of bulls available for artificial insemination are estimated using Free Disposal Hull. Although bulls generally are highly technically efficient, because only high performing bull semen is offered for sale, bulls are less revenue, allocative and profit efficient. These efficiencies are relative to peer bulls and can be updated as new bulls become available.
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Affiliation(s)
- Christine E. Whitt
- United States Department of Agriculture, Economic Research Services, Washington D.C., United States of America
- * E-mail:
| | - Loren W. Tauer
- Charles H. Dyson School of Applied Economics and Management, Cornell SC Johnson College of Business, Cornell University, Ithaca, New York, United States of America
| | - Heather Huson
- Department of Animal Science, College of Agriculture and Life Sciences, Cornell University, Ithaca, New York, United States of America
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Mareth T, Scavarda LF, Thomé AMT, Cyrino Oliveira FL, Alves TW. Analysing the determinants of technical efficiency of dairy farms in Brazil. INTERNATIONAL JOURNAL OF PRODUCTIVITY AND PERFORMANCE MANAGEMENT 2019. [DOI: 10.1108/ijppm-06-2018-0234] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
PurposeThe purpose of this paper is to analyse the determinants of technical efficiency (TE) in dairy farms located in the South of Brazil, aiming for a better understanding of the topic for academics, dairy farmers and policymakers to improve the productivity and competitiveness of dairy farms.Design/methodology/approachThis study was developed using a two-stage approach. Data envelopment analysis was used to estimate the TE level and regression models to understand the factors affecting TE in dairy farms. The sample size is 253 dairy farms in the South of Brazil.FindingsThe variation in the mean TE indexes reported in the literature can be explained by the attributes of the analysed studies, including the education of the farm operator, farm size (number of cows and milk), feed and labour costs, and use of services. Additionally, the results suggest that dairy farmers in the sample could increase milk output by 50.1 per cent (level of inefficiency) on average if they improve their TE.Originality/valueThis study makes three important contributions: first, it formulates hypotheses from the previous literature’s propositions on the estimation of TE in dairy farms; second, it tests the hypotheses in an empirical study to understand the main factors affecting the TE in dairy farms of the selected municipalities in the South of Brazil; and third, it compares previous findings on the determinants of TE in dairy farms serving different stakeholders, such as researchers, farmers and government representatives, to improve the productivity and competitiveness of dairy farms.
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