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The selection of hospital sites is one of the most important choice a decision maker has to take so as to resist the pandemic. The decision may considerably affect the outbreak transmission in terms of efficiency , budget, etc. The main targeted objective of this study is to find the ideal location where to set up a hospital in the willaya of Oran Alg. For this reason, we have used a geographic information system coupled to the multi-criteria analysis method AHP in order to evaluate diverse criteria of physiological positioning , environmental and economical. Another objective of this study is to evaluate the advanced techniques of the automatic learning . the method of the random forest (RF) for the patterning of the hospital site selection in the willaya of Oran. The result of our study may be useful to decision makers to know the suitability of the sites as it provides a high level of confidence and consequently accelerate the power to control the COVID19 pandemic.


2021 ◽  
Vol 11 (22) ◽  
pp. 11054
Author(s):  
Khaled Yousef Almansi ◽  
Abdul Rashid Mohamed Shariff ◽  
Ahmad Fikri Abdullah ◽  
Sharifah Norkhadijah Syed Ismail

Palestinian healthcare institutions face difficulties in providing effective service delivery, particularly in times of crisis. Problems arising from inadequate healthcare service delivery are traceable to issues such as spatial coverage, emergency response time, infrastructure, and manpower. In the Gaza Strip, specifically, there is inadequate spatial distribution and accessibility to healthcare facilities due to decades of conflicts. This study focuses on identifying hospital site suitability areas within the Gaza Strip in Palestine. The study aims to find an optimal solution for a suitable hospital location through suitability mapping using relevant environmental, topographic, and geodemographic parameters and their variable criteria. To find the most significant parameters that reduce the error rate and increase the efficiency for the suitability analysis, this study utilized machine learning methods. Identification of the most significant parameters (conditioning factors) that influence a suitable hospital location was achieved by employing correlation-based feature selection (CFS) with the search algorithm (greedy stepwise). Thus, the suitability map of potential hospital sites was modeled using a support vector machine (SVM), multilayer perceptron (MLP), and linear regression (LR) models. The results of the predicted sites were validated using CFS cross-validation and the receiver operating characteristic (ROC) curve metrics. The CFS analysis shows very high correlations with R2 values of 0.94, 0. 93, and 0.75 for the SVM, MLP, and LR models, respectively. Moreover, based on areas under the ROC curve, the MLP model produced a prediction accuracy of 84.90%, SVM of 75.60%, and LR of 64.40%. The findings demonstrate that the machine learning techniques used in this study are reliable, and therefore are a promising approach for assessing a suitable location for hospital sites for effective health delivery planning and implementation.


2021 ◽  
Vol 2 (5) ◽  
Author(s):  
Dietrich Jehle ◽  
Brian Doherty ◽  
Lexus Dickson ◽  
Melville C O'Brien ◽  
Casey Wilson ◽  
...  

2021 ◽  
Vol 12 ◽  
Author(s):  
Meghan R. Perry ◽  
Hannah C. Lepper ◽  
Luke McNally ◽  
Bryan A. Wee ◽  
Patrick Munk ◽  
...  

Background: Hospital wastewater is a major source of antimicrobial resistance (AMR) outflow into the environment. This study uses metagenomics to study how hospital clinical activity impacts antimicrobial resistance genes (ARGs) abundances in hospital wastewater.Methods: Sewage was collected over a 24-h period from multiple wastewater collection points (CPs) representing different specialties within a tertiary hospital site and simultaneously from community sewage works. High throughput shotgun sequencing was performed using Illumina HiSeq4000. ARG abundances were correlated to hospital antimicrobial usage (AMU), data on clinical activity and resistance prevalence in clinical isolates.Results: Microbiota and ARG composition varied between CPs and overall ARG abundance was higher in hospital wastewater than in community influent. ARG and microbiota compositions were correlated (Procrustes analysis, p=0.014). Total antimicrobial usage was not associated with higher ARG abundance in wastewater. However, there was a small positive association between resistance genes and antimicrobial usage matched to ARG phenotype (IRR 1.11, CI 1.06–1.16, p<0.001). Furthermore, analyzing carbapenem and vancomycin resistance separately indicated that counts of ARGs to these antimicrobials were positively associated with their increased usage [carbapenem rate ratio (RR) 1.91, 95% CI 1.01–3.72, p=0.07, and vancomycin RR 10.25, CI 2.32–49.10, p<0.01]. Overall, ARG abundance within hospital wastewater did not reflect resistance patterns in clinical isolates from concurrent hospital inpatients. However, for clinical isolates of the family Enterococcaceae and Staphylococcaceae, there was a positive relationship with wastewater ARG abundance [odds ratio (OR) 1.62, CI 1.33–2.00, p<0.001, and OR 1.65, CI 1.21–2.30, p=0.006 respectively].Conclusion: We found that the relationship between hospital wastewater ARGs and antimicrobial usage or clinical isolate resistance varies by specific antimicrobial and bacterial family studied. One explanation, we consider is that relationships observed from multiple departments within a single hospital site will be detectable only for ARGs against parenteral antimicrobials uniquely used in the hospital setting. Our work highlights that using metagenomics to identify the full range of ARGs in hospital wastewater is a useful surveillance tool to monitor hospital ARG carriage and outflow and guide environmental policy on AMR.


2021 ◽  
Vol 23 (3) ◽  
pp. 285-291
Author(s):  
Graeme J Duke ◽  
◽  
Frank Shann ◽  
Cameron I Knott ◽  
Felix Oberender ◽  
...  

BACKGROUND: The national hospital-acquired complications (HAC) system has been promoted as a method to identify health care errors that may be mitigated by clinical interventions. OBJECTIVES: To quantify the rate of HAC in multiday stay adults admitted to major hospitals. DESIGN: Retrospective observational analysis of 5-year (July 2014 – June 2019) administrative dataset abstracted from medical records. SETTING: All 47 hospitals with on-site intensive care units (ICUs) in the State of Victoria. PARTICIPANTS: All adults (aged ≥ 18 years) stratified into planned or unplanned, surgical or medical, ICU or other ward, and by hospital peer group (tertiary referral, metropolitan, regional). MAIN OUTCOME MEASURES: HAC rates in ICU compared with ward, and mixed-effects regression estimates of the association between HAC and i) risk of clinical deterioration, and ii) admission hospital site (intraclass correlation coefficient [ICC] > 0.3). RESULTS: 211 120 adult ICU separations with mean hospital mortality of 7.3% (95% CI, 7.2–7.4%) reported 110 132 (42.6%) HAC events (commonly, delirium, infection, arrhythmia and respiratory failure) in 62 945 records (29.8%). Higher HAC rates were reported in elective (cardiac [50.3%] and non-cardiac [40.6%]) surgical subgroups compared with emergency medical subgroup (23.9%), and in tertiary (35.4%) compared with non-tertiary (22.7%) hospitals. HAC was strongly associated with on-admission patient characteristics (P < 0.001), but was weakly associated with hospital site (ICC, 0.08; 95% CI, 0.05–0.11). CONCLUSIONS: Critically ill patients have a high burden of HAC events, which appear to be associated with patient admission characteristics. HAC may an indicator of hospital admission complexity rather than hospital-acquired complications.


2021 ◽  
Vol 108 (Supplement_6) ◽  
Author(s):  
T Stubley ◽  
B El-Khayat

Abstract Aim Sentinel lymph node biopsy (SLNB) is an established aspect of the staging process for primary melanoma, with the results dictating future treatment methods. Due to the COVID-19 pandemic no SLNBs were offered to patients with newly diagnosed melanoma at a hospital site in the West Midlands. The aim of this study was to identify the number of patients who missed out on this investigation in order to ascertain how many patients with a potential positive SLNB were missed. Method A patient list was provided from the dermatology and plastic surgery database, ensuring that all newly diagnosed melanoma patients throughout the period March-May 2020 were included. A retrospective study design was utilised, with all data collected from the computer system at a single hospital site. Results 64 patients were provided via the patient list, of which 44 were appropriate for SLNB using the NICE criteria. After detailed reading of the patient notes, 80% (35/44) of patients were provided with a reason why they did not receive a SLNB, however the remaining 20% (9/44) did not have this clearly recorded. Conclusions A large cohort of patients did not receive a SLNB during the COVID-19 pandemic. Utilising the clinical literature, it can be predicted that around 9 of these patients would have had a SLNB that identified metastasis. These patients have potentially missed out on adjuvant treatment, and the cohort will therefore require follow up to be adapted to reflect this.


2021 ◽  
pp. 1-12
Author(s):  
Melike Yılmaz ◽  
Tankut Atan

As the Covid-19 pandemic also proved, access to health care plays a crucial role in our lives. Public officials, managers and investors should consider many criteria such as public infrastructure, environment, accessibility and demand for selecting the most appropriate site for a new hospital. Thus, the hospital site selection problem is a critical multi-criteria decision-making (MCDM) problem. This paper is a case study for İstanbul where a recent MCDM methodology, the fuzzy Evaluation based on Distance from Average Solution (EDAS) method, is applied to this problem for the first time. We used a comprehensive set of five main criteria and 17 sub-criteria found in the relevant literature regarding hospital site selection. These criteria were evaluated by three decision-makers to choose the hospital site from three districts. The recommendation of the fuzzy EDAS method was then compared to the outcome of a frequently used fuzzy MCDM method. The methods resulted in different site recommendations.


2021 ◽  
Vol 15 (1) ◽  
Author(s):  
George Lee ◽  
Oliver T. Clough ◽  
Joseph A. Walker ◽  
Raymond E. Anakwe

Abstract Background We undertook a prospective qualitative survey to ascertain the perceptions and experience of National Health Service patients in the United Kingdom who underwent planned or elective procedures and surgery at alternate ‘clean’ hospital sites during the coronavirus disease 2019 (COVID-19) pandemic. These alternate ‘clean’ hospital sites were independent hospitals running active staff and patient testing programmes for COVID-19 and which did not admit or treat patients suffering with COVID-19. Methods A prospective survey was undertaken to include patients at least 30 days after a planned surgery or procedure conducted at a ‘clean’ alternate hospital site during the COVID-19 pandemic. The study was conducted using structured interviews undertaken by trained assessors. A 20% sample group of patients were randomly selected to participate in this study. Qualitative data related to confidence, safety and perceptions of safety were collected. Results Ninety-five patients (60%) reported that they had prior worries or concerns about undergoing an elective procedure during the COVID-19 pandemic. A total of 47 patients (30%) had delayed their surgery at least once because of these concerns. A total of 150 patients (95%) felt that the precautions in place to protect their safety in the setting of an alternate ‘clean’ hospital site were well thought out and proportionate. Patients reported high levels of confidence in the measures undertaken. Separation of patient pathways using the independent sector and patient testing were identified by patients as having the greatest impact on their perception of safety. Conclusions Patient confidence will be key to ensuring uptake of planned and elective procedures and surgery during the COVID-19 pandemic. Perceptions of safety will be key to this confidence and efforts to demonstrably enhance safety are well received by patients. In particular, patients felt that a dedicated programme of patient testing and separation of patient pathways provided the greatest levels of confidence in the safety of their treatment.


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