ADAPTATION OF LEAN METHODOLOGIES FOR HEALTHCARE APPLICATIONS

Lean and Six Sigma quality concepts and terminology have been applied in the manufacturing arena since the late 1980’s and early 1990’s. It has only been in recent years that healthcare administrators have identified these methods as being adaptable to their organizations so that they may realize organizational improvements for continuing success and delighting customers. Unfortunately, this is not an application that is widely taught in typical Industrial Engineering curriculum and therefore there are few educated professionals coming right out of college that are able to apply these principles to healthcare. There are however, many experienced professionals knowledgeable in the basic Lean and Six Sigma principles as applied to manufacturing. This paper presents research conducted by the IUPUI School of Engineering and Technology in partnership with Sister of St. Francis Health Services (SSFHS) which was focused on the development and implementation of a Lean Six Sigma Training Program specifically for healthcare. Through the development of this training program, Purdue faculty have adapted traditional manufacturing Lean methodologies for healthcare specific applications. This paper will present multiple examples of successfully adapted Lean manufacturing training for Healthcare organizations. The authors will then present their findings and recommendations concerning Lean training specifically for Healthcare professionals. They will also present in-depth explanations of hands-on exercises used to demonstrate application of lean tools such as value stream mapping, 5S and visual controls that can be used to effectively train employees in most any healthcare organization

Learning from the 2018 heatwave in the context of climate change: Are high-temperature extremes important for adaptation in Scotland?

To understand whether high temperatures and temperature extremes are important for climate change adaptation in Scotland, we place the 2018 heatwave in the context of past, present, and future climate, and provide a rapid but comprehensive impact analysis. The observed hottest day, 5-day, and 30-day period of 2018 and the 5-day period with the warmest nights had return periods of 5-15 years for 1950-2018. The warmest night and the maximum 30-day average nighttime temperature were more unusual with return periods of >30 years. Anthropogenic climate change since 1850 has made all these high-temperature extremes more likely. Higher risk ratios are found for experiments from the CMIP6-generation global climate model HadGEM3-GA6 compared to those from the very-large ensemble system weather@home. Between them, the best estimates of the risk ratios for daytime extremes range between 1.2-2.4, 1.2-2.3, and 1.4-4.0 for the 1-, 5-, and 30-day averages. For the corresponding nighttime extremes, the values are higher and the ranges wider (1.5->50, 1.5-5.5, and 1.6->50). The short-period nighttime extremes were more likely in 2018 than in 2017, suggesting a contribution from year-to-year climate variability to the risk enhancement of extreme temperatures due to anthropogenic effects. Climate projections suggest further substantial increases in the likelihood of 2018 temperatures between now and 2050, and that towards the end of the century every summer might be as hot as 2018. Major negative impacts occurred, especially on rural sectors, while transport and water infrastructure alleviated most impacts by implementing costly special measures. Overall, Scotland could cope with the impacts of the 2018 heatwave. However, given the likelihood increase of high-temperature extremes, uncertainty about consequences of even higher temperatures and/or repeated heatwaves, and substantial costs of preventing negative impacts, we conclude that despite its cool climate, high-temperature extremes are important to consider for climate change adaptation in Scotland

To what extent are land resource managers preparing for high-end climate change in Scotland?

We explore the individual and institutional conditions and the climate information used to underpin decision-making for adaptation to high-end climate change (HECC) scenarios in a land resource management context. HECC refers to extreme projections with global annual temperature increases of over 4 °C. We analyse whether HECC scenarios are used in the adaptation decision-making of stakeholders who will tackle the potential problem. We also explore whether the adaptation actions being considered are pertinent only to future climate change or whether other drivers and information types are used in decision-making (including non-climate drivers). We also address the role of knowledge uncertainty in adaptation decision-making. Decision-makers perceive HECC as having a low probability of occurrence and so they do not directly account for HECC within existing actions to address climate change. Such actions focus on incremental rather than transformative solutions in which non-climate drivers are at least as important, and in many cases more important, than climate change alone. This reflects the need to accommodate multiple concerns and low risk options (i.e. incremental change). Uncertainty in climate change information is not a significant barrier to decision-making and stakeholders indicated little need for more climate information in support of adaptation decision-making. There is, however, an identified need for more information about the implications of particular sectoral and cross-sectoral impacts under HECC scenarios. The outcomes of this study provide evidence to assist in contextualising climate change information by creating usable, cross-sectoral, decision-centred information

A Decade of Weather – a serious game to understand cascading climate change impacts

This dataset provides all the material to play "A Decade of Weather", a serious game to understand multiple hazards and risk from climate change on interdependent infrastructure. The game was developed through a co-creation process between inter-disciplinary climate researchers from the University of Edinburgh and adaptation stakeholders as part of a NERC-funded project run in late 2017/early 2018. The co-creation process and insights from the facilitated discussion while playing the game are described in the following research paper: S. Undorf, J. Hagg, M. J. Metzger, and S. F. B. Tett (2019), Understanding cascading climate change impacts using a serious game. [in submission]Undorf, Sabine; Tett, Simon FB; Hagg, Joseph; Metzger, Marc J; Wilson, Chris. (2019). A Decade of Weather – a serious game to understand cascading climate change impacts, [dataset]. University of Edinburgh. School of GeoSciences. https://doi.org/10.7488/ds/2577

Diversity of the Cronobacter genus as revealed by multilocus sequence typing

Cronobacter (previously known as Enterobacter sakazakii) is a diverse bacterial genus consisting of seven species: C. sakazakii, C. malonaticus, C. turicensis, C. universalis, C. muytjensii, C. dublinensis, and C. condimenti. In this study, we have used a multilocus sequence typing (MLST) approach employing the alleles of 7 genes (atpD, fusA, glnS, gltB, gyrB, infB, and ppsA; total length, 3,036 bp) to investigate the phylogenetic relationship of 325 Cronobacter species isolates. Strains were chosen on the basis of their species, geographic and temporal distribution, source, and clinical outcome. The earliest strain was isolated from milk powder in 1950, and the earliest clinical strain was isolated in 1953. The existence of seven species was supported by MLST. Intraspecific variation ranged from low diversity in C. sakazakii to extensive diversity within some species, such as C. muytjensii and C. dublinensis, including evidence of gene conversion between species. The predominant species from clinical sources was found to be C. sakazakii. C. sakazakii sequence type 4 (ST4) was the predominant sequence type of cerebral spinal fluid isolates from cases of meningitis