Health Systems最新文献_第3页

Multi-criteria decision-making methods applied in health-insurance underwriting. 多准则决策方法在健康保险承保中的应用。

IF 1.8

Health Systems Pub Date : 2023-01-01 DOI: 10.1080/20476965.2022.2085190

John Mourmouris, Thomas Poufinas

引用次数: 2

Trade, intellectual property, and the public health bearing. 贸易、知识产权和公共卫生影响。

IF 1.8

Health Systems Pub Date : 2023-01-01 DOI: 10.1080/20476965.2022.2062460

Julie Babyar

引用次数: 0

Wait!What does that mean?: Eliminating ambiguity of delays in healthcare from an OR/MS perspective. 等等!这是什么意思?从OR/MS的角度消除医疗保健延迟的模糊性。

IF 1.8

Health Systems Pub Date : 2023-01-01 DOI: 10.1080/20476965.2021.2018362

Maria Van Zyl-Cillié, Derya Demirtas, Erwin Hans

{"title":"Wait!What does that mean?: Eliminating ambiguity of delays in healthcare from an OR/MS perspective.","authors":"Maria Van Zyl-Cillié, Derya Demirtas, Erwin Hans","doi":"10.1080/20476965.2021.2018362","DOIUrl":"https://doi.org/10.1080/20476965.2021.2018362","url":null,"abstract":"Waiting time in healthcare is a significant problem that occurs across the world and often has catastrophic effects. There are various terms used for waiting time (\"sojourn\", \"throughput\" etc.) and there is no consensus on how these terms are defined. Ambiguous definitions of waiting time make it difficult to compare and measure the problems related to waiting times and delays in healthcare. We present a systematic search and review of the Operations Research and Management Science (ORMS) literature on delays in healthcare services. We search for articles from 2004 to 2019 and base our search strategy on a well-known healthcare planning and control decision taxonomy. An important step towards reducing the ambiguity in the definitions is to distinguish between access time and waiting time. We provide clear definitions and examples of access time and waiting time, and we classify our search results according to three categories: article type, healthcare service investigated and ORMS technique used to solve the delay problem. We find that half of the ORMS research on the waiting and access time problem is done on Ambulatory Care services. We provide tables for each healthcare service that highlight key definitions, the techniques that are used most often and the healthcare environment where the research is done. This research highlights the significant ORMS research that is done on access and waiting time in healthcare as well as the remaining research opportunities. Moreover, it provides a common language for the ORMS community to solve critical waiting time issues in healthcare.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"12 1","pages":"3-21"},"PeriodicalIF":1.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/5e/a5/THSS_12_2018362.PMC10013540.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9500501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Embedding OR modelling as decision support in health capacity planning: insights from an evaluation. 在卫生能力规划中嵌入OR建模作为决策支持:来自评估的见解。

IF 1.8

Health Systems Pub Date : 2023-01-01 DOI: 10.1080/20476965.2021.1983476

Sally Brailsford, Steffen Bayer, Con Connell, Abraham George, Jonathan Klein, Peter Lacey

引用次数: 3

Understanding how physician perceptions of job demand and process benefits evolve during CPOE implementation. 了解在CPOE实施过程中，医生对工作需求和流程利益的看法是如何演变的。

IF 1.8

Health Systems Pub Date : 2023-01-01 DOI: 10.1080/20476965.2022.2113343

Arun Rai, Mark Keil, Hyoungyong Choi, Vitali Mindel

{"title":"Understanding how physician perceptions of job demand and process benefits evolve during CPOE implementation.","authors":"Arun Rai, Mark Keil, Hyoungyong Choi, Vitali Mindel","doi":"10.1080/20476965.2022.2113343","DOIUrl":"https://doi.org/10.1080/20476965.2022.2113343","url":null,"abstract":"We examine how physicians' perceptions of two computerized provider order entry (CPOE) capabilities, standardisation of care protocols and documentation quality, are associated with their perceptions of turnaround time, medical error, and job demand at three phases of CPOE implementation: pre-go-live, initial use, and continued use. Through a longitudinal study at a large urban hospital, we find standardisation of care protocols is positively associated with turnaround time reduction in all phases but positively associated with job demand increase only in the initial use phase. Standardisation also has a positive association with medical error reduction in the initial use phase, but later this effect becomes fully mediated through turnaround time reduction in the continued use phase. Documentation quality has a positive association with medical error reduction in the initial use phase and this association strengthens in the continued use phase. Our findings provide insights to effectively manage physicians' response to CPOE implementation.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"12 1","pages":"98-122"},"PeriodicalIF":1.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10013386/pdf/THSS_12_2113343.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10471915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A configurable computer simulation model for reducing patient waiting time in oncology departments. 一种可配置的计算机模拟模型，用于减少肿瘤部门的患者等待时间。

IF 1.8

Health Systems Pub Date : 2023-01-01 DOI: 10.1080/20476965.2022.2030655

Roberto Rosario Corsini, Antonio Costa, Sergio Fichera, Alessandro Pluchino

{"title":"A configurable computer simulation model for reducing patient waiting time in oncology departments.","authors":"Roberto Rosario Corsini, Antonio Costa, Sergio Fichera, Alessandro Pluchino","doi":"10.1080/20476965.2022.2030655","DOIUrl":"https://doi.org/10.1080/20476965.2022.2030655","url":null,"abstract":"Nowadays, the increase in patient demand and the decline in resources are lengthening patient waiting times in many chemotherapy oncology departments. Therefore, enhancing healthcare services is necessary to reduce patient complaints. Reducing the patient waiting times in the oncology departments represents one of the main goals of healthcare managers. Simulation models are considered an effective tool for identifying potential ways to improve patient flow in oncology departments. This paper presents a new agent-based simulation model designed to be configurable and adaptable to the needs of oncology departments which have to interact with an external pharmacy. When external pharmacies are utilised, a courier service is needed to deliver the individual therapies from the pharmacy to the oncology department. An oncology department located in southern Italy was studied through the simulation model and different scenarios were compared with the aim of selecting the department configuration capable of reducing the patient waiting times.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"12 2","pages":"208-222"},"PeriodicalIF":1.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208172/pdf/THSS_12_2030655.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10195641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Efficiency of malaria service delivery in selected district-level hospitals in Ghana. 加纳选定的区级医院提供疟疾服务的效率。

IF 1.8

Health Systems Pub Date : 2023-01-01 DOI: 10.1080/20476965.2021.2015251

Jacob Novignon, Genevieve Aryeetey, Justice Nonvignon, Keziah Malm, Nana Yaw Peprah, Samuel Agyei Agyemang, Samuel Amon, Moses Aikins

{"title":"Efficiency of malaria service delivery in selected district-level hospitals in Ghana.","authors":"Jacob Novignon, Genevieve Aryeetey, Justice Nonvignon, Keziah Malm, Nana Yaw Peprah, Samuel Agyei Agyemang, Samuel Amon, Moses Aikins","doi":"10.1080/20476965.2021.2015251","DOIUrl":"https://doi.org/10.1080/20476965.2021.2015251","url":null,"abstract":"Malaria remains an important public health concern. Sub-Saharan African countries carry over 95% of the global burden. Unfortunately, there are also major resource constraints that have limited efforts to reduce the burden. Our study sought to estimate efficiency in the use of malaria resources and to identify potential determinants. We used primary data collected from district-level health facilities in three administrative regions in Ghana from 2014 to 2016. The Data Envelopment Analysis technique was used to estimate efficiency. The Malmquist productivity index was estimated and disaggregated to reflect the sources of productivity change. The findings show an average technical efficiency score of 0.61 with private facilities being more efficient. Productivity changes were driven by changes in technology/innovation advancements. Facility revenue mix and ownership type were important determinants of efficiency. The findings highlight the need to improve resource use in the delivery of specific services such as malaria.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"12 2","pages":"198-207"},"PeriodicalIF":1.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208147/pdf/THSS_12_2015251.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10248695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A simulation model to analyse automation scenarios in decontamination centers. 用于分析净化中心自动化场景的仿真模型。

IF 1.8

Health Systems Pub Date : 2023-01-01 DOI: 10.1080/20476965.2021.2004933

Marzieh Ghiyasinasab, Nadia Lahrichi, Nadia Lehoux

引用次数: 0

A generic sustainable performance management system for hospital supply chain: design & analysis. 医院供应链通用可持续绩效管理系统：设计与分析。

IF 1.8

Health Systems Pub Date : 2022-12-29 eCollection Date: 2024-01-01 DOI: 10.1080/20476965.2022.2155256

Anas Ziat, Naoufal Sefiani, Hamid Azzouzi, Kamal Reklaoui

引用次数: 0

Identification of the risk factors of type 2 diabetes and its prediction using machine learning techniques. 2型糖尿病危险因素的识别及其使用机器学习技术的预测。

IF 1.8

Health Systems Pub Date : 2022-11-05 eCollection Date: 2023-01-01 DOI: 10.1080/20476965.2022.2141141

Md Merajul Islam, Md Jahanur Rahman, Md Menhazul Abedin, Benojir Ahammed, Mohammad Ali, N A M Faisal Ahmed, Md Maniruzzaman

{"title":"Identification of the risk factors of type 2 diabetes and its prediction using machine learning techniques.","authors":"Md Merajul Islam, Md Jahanur Rahman, Md Menhazul Abedin, Benojir Ahammed, Mohammad Ali, N A M Faisal Ahmed, Md Maniruzzaman","doi":"10.1080/20476965.2022.2141141","DOIUrl":"10.1080/20476965.2022.2141141","url":null,"abstract":"This study identified the risk factors for type 2 diabetes (T2D) and proposed a machine learning (ML) technique for predicting T2D. The risk factors for T2D were identified by multiple logistic regression (MLR) using p-value (p<0.05). Then, five ML-based techniques, including logistic regression, naïve Bayes, J48, multilayer perceptron, and random forest (RF) were employed to predict T2D. This study utilized two publicly available datasets, derived from the National Health and Nutrition Examination Survey, 2009-2010 and 2011-2012. About 4922 respondents with 387 T2D patients were included in 2009-2010 dataset, whereas 4936 respondents with 373 T2D patients were included in 2011-2012. This study identified six risk factors (age, education, marital status, SBP, smoking, and BMI) for 2009-2010 and nine risk factors (age, race, marital status, SBP, DBP, direct cholesterol, physical activity, smoking, and BMI) for 2011-2012. RF-based classifier obtained 95.9% accuracy, 95.7% sensitivity, 95.3% F-measure, and 0.946 area under the curve.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"12 2","pages":"243-254"},"PeriodicalIF":1.8,"publicationDate":"2022-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208154/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9523971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2