An integrated approach of AHP-DEMATEL methods applied for the selection of allied hospitals in outpatient service

Nowadays, the citizens are more aware of high-quality medical care than ever. They pay much attention to medical treatment safety, instructions from physicians, and the overall service quality performed by the hospital. To manage a hospital successfully, the important goals are to attract and then retain as many patients as possible by meeting potential demands of various kinds of the patients. In this context the decision making process is important in order to achieve a strategic decision and strategy. When the decision making problem occurs there is usually a limited number of possible alternatives but a large number of criteria according to which the optimal solution is selected. It is important to use an appropriate approach. This study presents a hybrid methodological approach based on the Decision Making Trial and Evaluation Laboratory (DEMATEL) method and Analytic Hierarchy process method to define the best allied hospital for an integrated network of outpatient service. The goal of this paper is to present a methodological approach and a practical application of hybrid method in a real case study

Smart Product Design Process through the Implementation of a Fuzzy Kano-AHP-DEMATEL-QFD Approach

Product design has become a critical process for the healthcare technology industry, given the ever-changing demands, vague customer requirements, and interrelations among design criteria. This paper proposed a novel integration of fuzzy Kano, Analytic Hierarchy Process (AHP), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Quality Function Deployment (QFD) to translate customer needs into product characteristics and prioritize design alternatives considering interdependence and vagueness. First, the customer requirements were established. Second, the fuzzy KANO was applied to calculate the impact of each requirement, often vague, on customer satisfaction. Third,designalternativesweredefined,whiletherequirements’weightswerecalculated usingAHP.DEMATELwaslaterimplementedforevaluatingtheinterdependenceamongalternatives. Finally,QFDwasemployedtoselectthebestdesign. Ahipreplacementsurgeryaiddeviceforelderly people was used for validation. In this case, collateral issues were the most important requirement, while code change was the best-ranked design

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

Application of AHP and DEMATEL Methods in Choosing and Analysing the Measures for the Distribution of Goods in Szczecin Region

Urban areas are centres of business and innovation. Freight transport is indispensable for the proper functioning of any modern urban society. Urban areas cannot function without an appropriate freight transport system, due to the need to replenish stocks of food and other goods in retail shops. The complexity of the decisions concerning implementation of measures to improve the movement of goods in the city requires tools designed to support this process. In this context, a research gap and a research problem occur&mdash how to obtain a reliable set of factors for development of sustainable urban freight transport (UFT). The purpose of this article is to introduce the possibility of applying the Analytic Hierarchy Process (AHP) as well as the Decision Making Trial and Evaluation Laboratory Method (DEMATEL) in choosing a set of measures and in analysing the field of distribution logistics, which will help to solve delivery problems and streamline cargo flow in Szczecin, in the context of sustainable development. This paper presents the findings of a survey in which experts evaluate the main coefficients for sustainable freight transport in the city area. Using both AHP and DEMATEL methods, we have concluded that: (i) all coefficients from administrative, financial, technical and promotional measures are highly interconnected (ii) strategy of freight transport development should take into consideration how these coefficients influence each other (iii) P2&mdash eco-driving trainings, T4&mdash alternative delivery systems and P1&mdash promotional campaigns for sustainable transport are the most important criteria and should be priorities for investments (iv) A1&mdash implementation of loading/unloading and transit restrictions&mdash highly influences other coefficients (v) T2&mdash intelligent route guidance in freight transport is greatly influenced by them. Document type: Articl

Prediciendo reingresos hospitalarios no planificados antes de 15 días: una aplicación de la regresión logística

Hospital readmission is considered a key research area for improving care coordination and achieving potential savings. This is important because hospital readmissions can have negative consequences in terms of good health and recovery for patients. It is thus important to significantly reduce such readmissions. Unfortunately, there isn't a one-size-fits-all solution to preventing hospital readmissions. There are many variables outside of hospitals' direct control, such as social determinants and patient lifestyle factors, impacting readmissions. Although several studies have been undertaken to investigate 30-day readmissions, predicting revisits in shorter intervals (e.g., within 15 days after discharge) is highly needed to capture hospital-attributable returns better and develop more effective improvement plans. Hence, the aim of this paper is three-fold: i) to develop a comprehensive experimental study for identifying factors affecting 15-day readmission risk, ii) to classify patients according to the risk of 15-day readmission using logistic regression, and iii) provide general recommendations to reduce the 15-day readmission risk considering different predictors. To this end, the patients' characteristics were first described. Then, the significance of potential predictors, their interactions, and their effects were assessed. After this, a logistic regression model was derived to predict the likelihood of 15-day readmission in each patient. Finally, general recommendations were provided to reduce 15-day revisits. A real case study in Colombia was considered to validate the proposed methodology

HUMAN FACTOR RISK MANAGEMENT FOR MARITIME PILOTAGE OPERATIONS

In recent years, marine pilotage accidents occurring on a worldwide basis as a result of human error have not ceased to transpire, despite advances in technology and a significant set of international conventions, regulations, and recommendations to reduce them. Existing studies reveal that previous maritime risk and safety assessment findings provide valuable insights, but over the last decade, scarce information in terms of human factor studies specific to pilotage operations can be found. The risks and uncertainties in pilotage operations have yet to be fully explored. As a result, identifying, evaluating, and mitigating the human factor-related risks influencing the safety performance of pilotage operations is essential. The aim of this research project is to investigate the effect of human factors on pilotage operations, and to evaluate the impact of these factors on operators' performance; this last in turn may affect current pilotage operations by ultimately proposing an effective risk management framework, based on a decision-making analysis methodology. Firstly, human-related risk factors (HCFs) identification is conducted through a combination of primary and secondary sourced data. A comprehensive literature review was carried out, and a considerable number of real past case examples and maritime accident/incidents investigation reports have been reviewed. In order to validate the identified risk factors (HCFs) and to explore other contributory factors, survey questionnaires and semi-structured interviews with domain experts have been conducted. An initial structural hierarchy diagram for the identified risk factors (HCFs) has been developed and validated through experienced experts belonging to the maritime sector. In order to assess the human causal factors (HCFs), a novel hybrid MCDM technique based on the combination of the Analytic Hierarchy Process (AHP) and Decision-Making Trial and Evaluation (DEMATEL) methods is applied. The AHP is firstly used to evaluate the weight and rank the importance of the identified human causal factors that affect pilotage operation safety, while the DEMATEL method is applied to determine whether there are relationships among the factors. The key findings of the previous models assist the decision-making process by informing of appropriate measures for mitigating the risks influencing pilotage operations. Risk mitigation measures are identified through literature review, the implemented regulation, rules, and recommendations adopted by IMO and other organizations and via experts’ perspectives, and then evaluated through the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The results of this study are beneficial to the maritime industry, by means of identifying a new database on causal factors contributing to the occurrence of maritime pilotage disasters. In addition, the study provides an effective risk factors assessment tool, and offers a diagnostic instrument to help implement effective risk reduction strategies, in order to prevent or at least mitigate a human error incident/accident from occurring

Accessibility of Health Data Representations for Older Adults: Challenges and Opportunities for Design

Health data of consumer off-the-shelf wearable devices is often conveyed to users through visual data representations and analyses. However, this is not always accessible to people with disabilities or older people due to low vision, cognitive impairments or literacy issues. Due to trade-offs between aesthetics predominance or information overload, real-time user feedback may not be conveyed easily from sensor devices through visual cues like graphs and texts. These difficulties may hinder critical data understanding. Additional auditory and tactile feedback can also provide immediate and accessible cues from these wearable devices, but it is necessary to understand existing data representation limitations initially. To avoid higher cognitive and visual overload, auditory and haptic cues can be designed to complement, replace or reinforce visual cues. In this paper, we outline the challenges in existing data representation and the necessary evidence to enhance the accessibility of health information from personal sensing devices used to monitor health parameters such as blood pressure, sleep, activity, heart rate and more. By creating innovative and inclusive user feedback, users will likely want to engage and interact with new devices and their own data

Diseño de un modelo de categorización del riesgo de reingreso para pacientes egresados de urgencias y hospitalización en clínicas de Barranquilla

Ingeniería IndustrialThe health sector is now more than a global trend; It is a topic of global interest because of its direct link with living conditions, welfare and development of persons(Law 1122 of 2007); however, the system has notorious failures in patient monitoring after care;this generated a high rate of reentry of health care centers. This study was carried out in several stages, where the first time the characterization of the reentry of the patients graduated from the Department of Emergency and hospitalization in the subsector of clinics in the city of Barranquilla through analysis of studies and information on rates of readmissions and their causes; in addition to collecting local information (from staff and patients), studying existing evidence, boosting original research and development; allow in the second stage identify the problems generated by monitoring failures and the logical processes that are executed in order to generate a characterization of the post - care. With the diagnosis of the health system that is currently used for the external monitoring of patients and the characterization of patient readmissions to the aforementioned services, a re-entry risk categorization model will be designed for the graduates of the emergency and hospitalization Department based on the identification of the risk factors that affect their reentry to these services and the correlation risk factors and likelihood of re-entry. The applied methodology consisted in the analysis of the information presented in the SISPRO database (Comprehensive Information System for Social Protection) of the Ministry of Health, followed by the application of a test of randomness in Microsoft Excel to a population of clinics, in order to take a sample for the application of a survey to identify the risk factors that affect in the reentry of patients to the clinics of the city of Barranquilla and for the last time from a clinic in the city. In the findings derived from the results of the surveys, it is evident that operative site infections, as well as those associated with care are factors which increase the likelihood of readmission in the clinics studied. As for the re-entry reduction strategies and the external monitoring of patients by health entities, it is inferred from the results, that these do not perform an optimal follow-up to the evolution of the same after discharge, but are mostly limited to monitoring by telephone contact, thus giving rise to the probability that the patient Reenter the institution. Therefore, there is a need for health entities to implement follow-up processes for the evolution and rehabilitation of patients in a more committed, effective and assertive way to guarantee the continuous care of their health. In this investigation a statistical model was designed to measure the probability of readmissions in the hospitalization departments. The novelty of the research is the proposal of a regression application multivariate logistics to predict re-admissions of 15 days in the hospitalization departments. Our model allows us to classify patients into a category of risk. In this way, prevention plans can be created for each patient in order to reduce the probability of unplanned re-entry.The model provides enough information to analysts who are interested in managing hospital readmissions problem.The model clearly suggests that the simple and accessible parameters are useful for identifying patients at high risk of hospital readmission. Future research should study the behavior of hospital readmission in order to perform comparative analyzes and action under international framework projects.El sector salud en la actualidad más que una tendencia mundial; es un tema de interés global debido a su vinculación directa con las condiciones de vida, bienestar y desarrollo de las personas (Ley 1122 de 2007); sin embargo, el sistema tiene falencias notorias en el monitoreo de los pacientes luego de ser atendidos; lo que genera un alto índice de reingreso de los centros asistenciales.Este estudio se realizará en diversas etapas, dónde la primera involucra la caracterización del reingreso de pacientes egresados del Departamento de Urgencias y hospitalización en el subsector de clínicas de la ciudad de Barranquilla a través del análisis de estudios e información sobre tasas de reingresos y sus causas; además de recopilar información local (de personal y pacientes), estudiar evidencias existentes, impulsar la investigación y desarrollo original; que permita en la segunda etapa identificar la problemática generada por fallas en monitoreo y los procesos lógicos que se ejecutan a fin de generar una caracterización de la post – atención.Con el diagnóstico del sistema de salud que actualmente se utiliza para el monitoreo externo de los pacientes y la caracterización de los reingresos de pacientes a los servicios anteriormente mencionados, se procederá al diseño de un modelo de categorización del riesgo de reingreso para pacientes egresados del Departamento de Urgencias y hospitalización a partir de la identificación de los factores de riesgo que inciden en su reingreso a estos servicios y la correlación existente entre los factores de riesgo y la probabilidad de reingreso.La metodología aplicada consisitió en el análisis de la información expuesta en la base de datos SISPRO (sistema Integral de información de la Protección Social) del Ministerio de Salud, seguido de la aplicación de una prueba de aleatoriedad en Microsoft Excel a una población de clinicas, con el fin de tomar una muestra para la aplicación de una encuesta para identificar los factores de riesgo que inciden en el reingreso de pacientes a las clínicas de la ciudad de Barranquilla y por último se extrajo información mas profunda de ciertos pacientes de una clínica de la ciudad. En los hallazgos derivados de los resultados de las encuestas, se evidencia que las infecciones del sitio operatorio, así como las asociadas al cuidado son factores comunes que aumentan la probabilidad de readmisión en las clínicas estudiadas. En cuanto a las estrategias de reducción de reingreso y a la poca frecuencia de monitoreo externo de pacientes por parte de las entidades de salud, se infiere de los resultados, que estas no realizan un óptimo seguimiento a la evolución del mismo después del egreso, si no que se limitan en su mayoría a realizar un monitoreo mediante contacto telefónico, dando así lugar a la probabilidad de que el paciente reingrese a la institución. Por lo tanto existe la necesidad de que las entidades de salud implementen procesos de seguimiento a la evolución y rehabilitación de los pacientes de una forma más comprometida, efectiva y asertiva para garantizar el cuidado continúo de su salud.En esta investigación se diseñó un modelo estadístico para medir la probabilidad de reingresos en los departamentos de hospitalización. La novedad de la investigación es la propuesta de una aplicación de regresión logística multivariada para predecir reingresos de 15 días en los departamentos de hospitalización. Nuestro modelo permite clasificar a los pacientes en una categoría de riesgo. De esta manera se pueden crear planes de prevención para cada paciente con el fin de reducir la probabilidad de reingreso no planificado. El modelo proporciona suficiente información a los analistas que están interesados en la gestión de reingresos hospitalarios

Fuelling the zero-emissions road freight of the future: routing of mobile fuellers

The future of zero-emissions road freight is closely tied to the sufficient availability of new and clean fuel options such as electricity and Hydrogen. In goods distribution using Electric Commercial Vehicles (ECVs) and Hydrogen Fuel Cell Vehicles (HFCVs) a major challenge in the transition period would pertain to their limited autonomy and scarce and unevenly distributed refuelling stations. One viable solution to facilitate and speed up the adoption of ECVs/HFCVs by logistics, however, is to get the fuel to the point where it is needed (instead of diverting the route of delivery vehicles to refuelling stations) using "Mobile Fuellers (MFs)". These are mobile battery swapping/recharging vans or mobile Hydrogen fuellers that can travel to a running ECV/HFCV to provide the fuel they require to complete their delivery routes at a rendezvous time and space. In this presentation, new vehicle routing models will be presented for a third party company that provides MF services. In the proposed problem variant, the MF provider company receives routing plans of multiple customer companies and has to design routes for a fleet of capacitated MFs that have to synchronise their routes with the running vehicles to deliver the required amount of fuel on-the-fly. This presentation will discuss and compare several mathematical models based on different business models and collaborative logistics scenarios