Assessment of Healthcare Solid Waste Composition, Generation and its Management: the case of Two Hospitals of Shashemene Town, Oromiya Regional State, Ethiopia

Hazardous wastes from Hospitals could pose threat to the health of healthcare workers, the general public, and the environment unless managed properly. The study aimed to appraise the healthcare waste (HCW) composition, generation rate and the prevailing management practices in two Hospitals (a Private and a Government-owned) of Shashemene Town, Ethiopia. A cross-sectional study involving Direct Observation, Key Informant Interview, Questionnaire survey, and weighing scale was conducted to evaluate the current HCW management practices and to quantify the HCW generation rate. Data was analyzed using SPSS version 20. The mean generation rates of HCW were 45.2 ± 5.8kg day–1 (0.20kg bed‒1day‒1) and 20 ± 2.4 kg day–1 (0.19kg bed‒1day‒1) from Government Hospital (GH) and Private Hospital (PH), respectively. Of the total solid waste generated, over half (GH: 53.3%; PH: 57.1%) constituted general waste (GW), and the remaining (GH: 46.7%; PH: 42.9%) comprised hazardous waste (HW), which exceeded the WHO threshold (10‒25%) intimates the lack of poor waste segregation. There were significant variations between the hospital wards regarding GW (GH: χ2 = 31; P < 0.001; PH:χ2 = 13; P < 0.01), HW (GH: χ2 = 25; P < 0.001; PH: χ2 = 10; P < 0.01), and total HCW (GH: χ2 = 46; P < 0.01; PH: χ2 = 22; P < 0.01). Besides, significant differences were observed between the mean total HCW (χ2 = 9.016; P < 0.01), GW (χ2 = 9.8; P < 0.01), and the HW (χ2 = 5.011, P < 0.05) of the hospitals. Segregation of wastes and pre-treatment of infectious wastes were not properly practiced, and single-chamber incinerators were the most utilized treatment method indicating poor management of the HCW. The study establishes that little attention is given to medical waste management which primarily proceeds from a lack of due implementation of the national healthcare wastes management guideline/directive at the healthcare facility level. If the poor healthcare solid waste management is not properly addressed at the study hospitals, human (healthcare workers, waste handlers, patients, and nearby community) and environmental health risk will be within the bounds of possibility

Assessment of Healthcare Solid Waste Composition, Generation and its Management: the case of Two Hospitals of Shashemene Town, Oromia Regional State, Ethiopia

Hazardous wastes from Hospitals could pose a threat to the health of healthcare workers, the general public, and the environment unless managed properly. The study aimed to appraise the healthcare waste (HCW) composition, generation rate and the prevailing management practices in two Hospitals (a Private and a Government-owned) of Shashemene Town, Ethiopia. A cross-sectional study involving Direct Observation, Key Informant Interview, Questionnaire survey and Weighting Scale was conducted to evaluate the current HCW management practices and to quantify the HCW generation rate. Data was analyzed using SPSS version 20. The mean generation rates of HCW were 45.2 ± 5.8kg day–1 (0.20kgbed‒1day‒1) and 20 ± 2.4 kg day–1 (0.19kg bed‒1day‒1) from Government Hospital(GH) and Private Hospital (PH), respectively. Of the total solid waste generated, over half(GH: 53.3%; PH: 57.1%) constituted general waste (GW), and the remaining (GH: 46.7%; PH: 42.9%) comprised hazardous waste (HW), which exceeded the WHO threshold(10‒25%) intimates the lack of poor waste segregation. There were significant variations between the hospital wards regarding GW (GH: χ2 = 31; P < 0.001; PH:χ2 = 13; P <0.01), HW (GH: χ2 = 25; P < 0.001; PH: χ2 = 10; P < 0.01), and total HCW (GH: χ2 = 46; P < 0.01; PH: χ2 = 22; P < 0.01). Besides, significant differences were observed between the mean total HCW (χ2 = 9.016; P < 0.01), GW (χ2 = 9.8; P < 0.01), and the HW (χ2 =5.011, P < 0.05) of the hospitals. Segregation of wastes and pre-treatment of infectious wastes were not properly practiced, and single-chamber incinerators was the most utilized treatment method indicating poor management of the HCW. The study establishes that the little attention is given to medical waste management which primarily proceeds from a lack of due implementation of the national healthcare wastes management guideline/directive at the healthcare facility level. If the poor healthcare solid waste management is not properly addressed at the study hospitals, human (healthcare workers, waste handlers, patients, and nearby community) and environmental health risk will be within the bounds of possibility

Endometrial Intraepithelial Neoplasia Clinical Correlates and Outcomes

Objective To estimate cancer outcome and outcome predictors of women with endometrial intraepithelial neoplasia (EIN). Methods Outcomes of women with first diagnosis of EIN (“index biopsy”) was determined by follow-up pathology. Patient characteristics were correlated with EIN regression, EIN persistence, and progression to cancer. Results Fifteen percent (9.8-20.8%, 26/177) of index EIN biopsies had concurrent cancer. Of the women with cancer-free index EIN biopsies, and follow-up by hysterectomy or more than 18 months surveillance, 25% (18.4-33.3%, 36/142) showed regression, 35% (27.4-43.7%, 50/142) persistence, and 39% (31.3-48.0%, 56/142) progression. Non-white ethnicity and progestin treatment reduced cancer outcomes (OR 0.16 (0.03,0.84) and 0.24 (0.08, 0.70) respectively), while body mass index (BMI) greater than 25 increased malignant outcomes (BMI 25 or higher, OR 3.05 (1.10,8.45)). Conclusion EIN confers a high risk of cancer, but individual patient outcomes cannot be predicted. Management should include exclusion of concurrent carcinoma and consideration of hysterectomy

Configuration Design of a High Performance and Responsive Manufacturing System : Modeling and Evaluation

Configuring and reconfiguring a manufacturing system is presented as an issue with increasing importance due to higher frequency of system configuration or major reconfigurations to accommodate new set of requirements and/or the need to configure the system to make it usable across generations of products or product families. This research has focused in the modeling, evaluation and selection decisions which involves multiple, incommensurate and conflicting objectives. Which renders configuration a multi criteria decision making or multi objective optimization problem. A manufacturing system configuration design is strategic, i.e., the effects are long term and determines the competitiveness of manufacturing. A case study in one of Swedish large discrete part manufacturing which produces variants of products for two different market segments is conducted to verify the fit between the manufacturing strategy and the existing system configuration. The relevance of aggregate modeling is discussed and it’s argued that system dynamics has the advantage over analytical methods in its capability to capture the complexity, its capability to evolve into more rigorous and detailed model, and the lesser time needed for the assessment especially when there are a number of alternatives. Circumstances are when a cost model may suffice for certain comparative analysis. The challenge with cost models is the difficulty in projecting intangible factors in terms of cost. However, approximation to some important factors can be made that may give insights in the comparative performances of alternatives. In line with this view a cost model that comprises the investment and operation costs, quality and reliability is proposed. Application of AHP and ANP for preference weight (subjective) elicitation and qualitative performance evaluation, entropy for objective weights calculation that may help to evaluate the discriminating ability of a criteria, Pareto frontier Analysis particularly Data Envelopment Analysis for selection and ranking of alternatives are shown to be relevant and applicable in configuration design. A comprehensive design decision matrix called House of Assessment is proposed that captures the dependency among the criteria and evaluation objectives weights of the criteria using entropy to determine the discriminating ability of the criteria whenever appropriate.QC 2010082

A multilayer shallow learning approach to variation prediction and variation source identification in multistage machining processes

Variation propagation modelling in multistage machining processes through use of analytical approaches has been widely investigated for the purposes of dimension prediction and variation source identification. Yet the variation prediction of complex features is non-trivial task tomodel mathematically.Moreover, the application ofthevariation propagation approaches and associated variation source identification techniques using SkinModel Shapes is unclear. This paper proposes amultilayer shallow neural network regression approach to predict geometrical deviations of parts given manufacturing errors. The neural network is trained on a simulated data, generated from machining simulation of a point cloud of a part. Further, given a point cloud data of a machined feature, the source of variation can be identified by optimally matching the deviation patterns of the actual surface with that of shallow neural network generated surface. To demonstrate the method, a two-stage machining process and a virtual part that has planar, cylindrical and torus features was considered. The geometric characteristics of machined features and the sources variation could be predicted at an error of 1% and 4.25%, respectively. This work extends the application of Skin Model Shapes in variation propagation analysis in multistage manufacturing.Not dublicate with 1505752QC 20201130</p