Cancer Surveillance using Data Warehousing, Data Mining, and Decision Support Systems

This article discusses how data warehousing, data mining, and decision support systems can reduce the national cancer burden or the oral complications of cancer therapies, especially as related to oral and pharyngeal cancers. An information system is presented that will deliver the necessary information technology to clinical, administrative, and policy researchers and analysts in an effective and efficient manner. The system will deliver the technology and knowledge that users need to readily: (1) organize relevant claims data, (2) detect cancer patterns in general and special populations, (3) formulate models that explain the patterns, and (4) evaluate the efficacy of specified treatments and interventions with the formulations. Such a system can be developed through a proven adaptive design strategy, and the implemented system can be tested on State of Maryland Medicaid data (which includes women, minorities, and children)

Considerations for choosing appropriate healthcare waste management treatment technologies: a case study from an East Midlands NHS Trust, in England

Through their decision-making processes, organisations can play a key role in addressing global environmental challenges. However, to be effective, these processes need to be based on evidence. This paper aims to evaluate the ‘optimum’ healthcare waste treatment technology, using a National Health Service organisation in the East Midlands region of England, as the case study organisation. Using analytic hierarchy process as the research tool, this research determined that the ‘optimum’ approach was a mix of technologies. However, this result was largely driven by costs considerations. Thus the findings suggest the need for a holistic approach to the decision-making process for the procurement of their healthcare waste management services. The use of analytic hierarchy process generally worked well in informing the decision-making process

A Comprehensive Review of the Novel Weighting Methods for Multi-Criteria Decision-Making

In the realm of multi-criteria decision-making (MCDM) problems, the selection of a weighting method holds a critical role. Researchers from diverse fields have consistently employed MCDM techniques, utilizing both traditional and novel methods to enhance the discipline. Acknowledging the significance of staying abreast of such methodological developments, this study endeavors to contribute to the field through a comprehensive review of several novel weighting-based methods: CILOS, IDOCRIW, FUCOM, LBWA, SAPEVO-M, and MEREC. Each method is scrutinized in terms of its characteristics and steps while also drawing upon publications extracted from the Web of Science (WoS) and Scopus databases. Through bibliometric and content analyses, this study delves into the trend, research components (sources, authors, countries, and affiliations), application areas, fuzzy implementations, hybrid studies (use of other weighting and/or ranking methods), and application tools for these methods. The findings of this review offer an insightful portrayal of the applications of each novel weighting method, thereby contributing valuable knowledge for researchers and practitioners within the field of MCDM.WOS:0009972313000012-s2.0-85160203389Emerging Sources Citation IndexarticleUluslararası işbirliği ile yapılan - EVETHaziran2023YÖK - 2022-2

A framework to support environmentally-based decision-making in the biopharmaceutical industry

The past decade has seen an increasing focus on the issues surrounding climate change and this has triggered governments internationally to develop environmental legislation and policies for the energy-intensive industries (EIIs) that can help reduce their anthropogenic greenhouse gases (GHGs) emissions. The biopharmaceutical industry is a relatively new EII. As the industry matures, the level of environmental scrutiny is increasing. Therefore, there is a need for the development of a framework specific to this industry to help guide the selection of manufacturing and disposal routes that reflect the potential environmental impact. In this doctorate, a framework based on the life cycle assessment (LCA) tool was developed. The application of the framework for evaluating manufacturing and solid waste management alternatives is demonstrated via case studies that focus on production of therapeutic monoclonal antibodies using mammalian cell culture process at 200 L operational scale using either traditional or a hybrid based on a mix of traditional and disposable modes of production. The framework was employed to identify the process (whether traditional or hybrid) that contributes least to environmental impact, and also to identify the most suitable solid waste management method (landfill, incineration and pyrolysis). The life cycle inventory of the manufacturing processes, and the methodology used to obtain the inventory are presented. It is expected that this information will be beneficial for future studies in this area of research. The analysis also utilised sensitivity analysis studies to assess critically the uncertainties in the assumptions made in the case study. Finally, the application of the framework in evaluating the cumulative environmental impact, from manufacture in support of clinical stages up to production was assessed. Here, the focus was not only to evaluate the cumulative environmental impact, but also to explore the benefits of employing single-use technologies during clinical phase manufacture when developing a monoclonal antibody for therapeutic use. The work in this thesis highlights the benefits of adopting a consistent engineering framework to guide process and technology selections in the biopharmaceutical industry by improving the overall quality of decision-making. This in turn will help the industry to predict and to control their environmental performance

A Hybrid Multi-Criteria Analysis Model for Solving the Facility Location–Allocation Problem: a Case Study of Infectious Waste Disposal

Choosing locations for infectious waste disposal (IWD) is one of the most significant issues in hazardous waste management due to the risk imposed on the environment and human life. This risk can be the result of an undesirable location of IWD facilities. In this study a hybrid multi-criteria analysis (Hybrid MCA) model for solving the facility location–allocation (FLA) problem for IWD was developed by combining two objectives: total cost minimization and weight maximization. Based on an actual case of forty-seven hospitals and three candidate municipalities in the northeastern region of Thailand, first, the Fuzzy AHP and Fuzzy TOPSIS techniques were integrated to determine the closeness of the coefficient weights of each candidate municipality. After that, these weights were converted to weighting factors and then these factors were taken into the objective function of the FLA model. The results showed that the Hybrid MCA model can help decision makers to locate disposal centers, hospitals and incinerator size simultaneously. Besides that the model can be extended by incorporating additional selection criteria/objectives. Therefore, it is believed that it can also be useful for addressing other complex problems

A Strong Sustainability Paradigm Based Analytical Hierarchy Process (SSP-AHP) Method to Evaluate Sustainable Healthcare Systems

The recent studies signify the growing concern of researchers towards monitoring and measuring sustainability performance at various levels and in many fields, including healthcare. However, there is no agreed approach to assessing the sustainability of health systems. Moreover, social indicators are less developed and less succinct. Therefore, the authors seek to map sustainable reference values in healthcare and propose a conceptual and structured framework that can guide the measurement of the social sustainability-oriented health systems. Based on a new multi-criteria method called Strong Sustainability Paradigm based Analytical Hierarchy Process, (SSP-AHP), the presented approach opens the availability for systems' comparison and benchmarking. The Strong Sustainability Paradigm incorporated into the multi-criteria evaluation method prevents the exchangeability of criteria by promoting alternatives that achieve good performance values on all criteria, implying sustainability. The research results offer insights into the core domains, sub-domains, and indicators supporting a more comprehensive assessment of the social sustainability of health systems. The framework constructed in this study consists of five major areas: equity, quality, responsiveness, financial coverage, and adaptability. The proposed set of indicators can also serve as a reference instrument, providing transparency about core aspects of performance to be measured and reported, as well as supporting policy-makers in decisions regarding sectoral strategies in healthcare. Our findings suggest that the most socially sustainable systems are Nordic countries. They offer a high level of social and financial protection, achieving very good health outcomes. On the other hand, the most unsustainable systems located in central and eastern European countries.Comment: 34 pages, 13 figures, 16 table

Modelling the Shift in the Balance of Care in the NHS

The concept of Shifting the Balance of Care was first introduced to NHS Scotland in 2005 through the Kerr Report. The key messages from the report were to: ensure sustainable and safe local services, which are supported by the right skills, change the emphasis of care into the community, provide preventative reactive care, and fully integrate the system to tackle the changes, use technology more effectively, and involve the public in finding solutions to change. Following the report, a framework was developed which highlighted and prioritised eight areas of improvement. These areas for improvement are the focus by which this research examines if Operational Research (OR), specifically OR models, can have a positive impact in Shifting the Balance of Care. The research utilises underlying OR methodologies and methods and provides evidence from the literature of the ability of nine selected models to facilitate the Shift in the Balance of Care. A contributing factor to the research is the barriers to implementation of OR models into the NHS. With reference to the literature, the common barriers to implementation of OR models are categorised and used to provide direction to modellers where implementation barriers are more prevalent in some models than in others. The research also provides empirical evidence of three selected models’ (the Lean Methodology, Process Mapping and Simulation, developed over two Case Studies) ability to address and influence the prioritised Improvement Areas, with the addition of a newly developed model: SoApt. The development of SoApt follows the Principles of Model Development derived as a guide to modellers who wish to develop a new model. SoApt is also empirically explored in a Case Study and provides some evidence of the models ability to aid Decision-makers, faced with limited budgets, to choose between options which will Shift the Balance of Care. OR methods and methodologies are examined to ascertain the Roles of Models for each model explored in the Case Studies. Examination of the Roles of Models against the Improvement Areas provided evidence of a models’ ability to address more than one of the priority areas and that models can be used together or sequentially. In addition, with reference to OR methods and methodologies, a theoretical Evaluation Framework is proposed which suggests the User and User Satisfaction is key to the evaluation of a model’s success; positive experiences of the User and Use of the model may help to eliminate some of the barriers to implementation