Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

A brief note on quality loss functions used in quality engineering

2-s2.0-85089048188In quality engineering, loss functions play a critical role in understanding process losses. Poorly operated production units and incomplete designed products cause major incidents involving monetary and social losses. In statistics, a loss function describes the monetary loss associated with how far off the result your production process produced is from the expected result. A high value-added product means the product which has reached the predefined target value and manufactured with a low variance. Taguchi’s quadratic loss has brought a different perspective to the classical loss conception. Distances from the target value cause customer dissatisfaction even within the specification limits. Taguchi realized that the step loss function method (i.e., no losses if specifications are met) is an inadequate or unrealistic measure to define ‘perfect quality’. The commonly used loss function is the quadratic function due to its nice analytical properties. However, the disadvantage of Taguchi’s quality loss function is that the arms of the parabola endlessly extend to infinity and is symmetrical. In many production processes, it is improper to assume that the loss of quality is unbounded even if all the other costs are included. Asymmetric quality loss is also common when the cost of leftover differs from the recovering cost. Adhering naively to the purely symmetric process assumption and working under symmetric loss may be an obstacle to producing the correct losses for the product. Moreover, it may not always be possible to convert asymmetric processes into symmetry after the right data transform. A loss function appropriate to the process distribution is important in terms of measuring the correct loss. As a result, it is possible to examine the loss functions in two groups as symmetric and asymmetric. In this study, important loss functions used especially in quality engineering will be briefly reviewed. © 2020 by Nova Science Publishers, Inc. All rights reserved

The effects of gamma noise on quality improvement

Taguchi's robust parameter design is an experimental procedure based on reducing the system variability that noise factors cause. The results, obtained under unrealistic assumptions about noise, may mislead practitioners when it comes to improving quality in robust design. For example, many hydrological data and the multi-path fading of a signal in wireless communication systems are positively skewed and cannot be modeled by any normal distribution. This manuscript focuses on the case where noise factor follows gamma distribution and investigates its true effects on the following: the response, the choice of an estimator in modeling, and the estimation of optimum factor settings. Then, a new density function is proposed for a given response under the gamma effect. A design of simulated experiments with gamma noise is conducted and two related examples are presented to illustrate the findings. © 2018, © 2018 Taylor & Francis Group, LLC