Non-emergency patient transport services planning through genetic algorithms

Non-emergency Patient Transport Services (PTS) are provided by ambulance companies for patients who do not require urgent and emergency transport. These patients require transport to or from a health facility like a hospital, but due to clinical requirements are unable to use private or public transport. This task is performed nowadays mainly by human operators, spending a high amount of time and resources to obtain solutions that are suboptimal in most cases. To overcome this limitation, in this paper we present NURA (Non-Urgent transport Routing Algorithm), a novel algorithm aimed at ambulance route planning. In particular, NURA relies on a genetic algorithm to explore the solution space, and it includes a scheduling algorithm to generate detailed routes for ambulances. Experimental results show that NURA is able to outperform human experts in several real scenarios, reducing the time spent by patients in ambulances during non-emergency transportations, increasing ambulance usage, while saving time and money for ambulance companies

SafeRNet: Safe Transportation Routing in the era of Internet of Vehicles and Mobile Crowd Sensing

World wide road traffic fatality and accident rates are high, and this is true even in technologically advanced countries like the USA. Despite the advances in Intelligent Transportation Systems, safe transportation routing i.e., finding safest routes is largely an overlooked paradigm. In recent years, large amount of traffic data has been produced by people, Internet of Vehicles and Internet of Things (IoT). Also, thanks to advances in cloud computing and proliferation of mobile communication technologies, it is now possible to perform analysis on vast amount of generated data (crowd sourced) and deliver the result back to users in real time. This paper proposes SafeRNet, a safe route computation framework which takes advantage of these technologies to analyze streaming traffic data and historical data to effectively infer safe routes and deliver them back to users in real time. SafeRNet utilizes Bayesian network to formulate safe route model. Furthermore, a case study is presented to demonstrate the effectiveness of our approach using real traffic data. SafeRNet intends to improve drivers safety in a modern technology rich transportation system.Comment: Paper was accepted at the 14th IEEE Consumer Communications & Networking Conference (CCNC 2017

Tempo de espera, distância e transporte: equidade e desigualdade no acesso aos cuidados de saúde pelo utente hipertenso em Portugal

RESUMO - Introdução: Ao longo dos anos, diversos estudos têm reforçado a premissa de que os fatores socioeconómicos de um individuo, afetam de forma positiva ou negativa o seu acesso aos cuidados de saúde, podendo prolongar ou diminuir o seu tempo de espera. O objetivo do presente trabalho de investigação foi realizar uma análise da equidade e desigualdade no acesso aos cuidados de saúde, no contexto dos tempos de espera, entre utentes adultos e idosos hipertensos em Portugal. Metodologia: Realizou-se um estudo observacional, transversal, analítico com recolha de informação retrospetiva tendo por base os dados recolhidos através do Inquérito Nacional de Saúde de 2019, realizado pelo Instituto Nacional de Estatística. Foram selecionados para análise, todos os participantes residentes em Portugal com idade igual ou superior a 18 anos que sejam hipertensos. Resultados: Foram analisados os dados recolhidos de 4471 participantes no Inquérito Nacional de Saúde de 2019, residentes em Portugal. Após a realização da análise bivariável e análise multivariável, verificou-se que variáveis socioeconómicas como o nível de rendimento, onde os indivíduos do 4º (OR=0,722; p=0,026) e 5º quintil (OR=0,607; p=0,008), tendem a reportar um menor tempo de espera quando comparados com os restantes escalões de rendimento. Estes dois escalões de rendimento surgem novamente como fatores protetores quanto à fundamentação da sua espera, não atribuindo à distância ou acesso a transportes como causa da sua espera. Conclusões: Apesar de existirem diversos estudos nacionais e internacionais de anos passados, que apontam para conclusões semelhantes. Podemos verificar que apesar das medidas tomadas e da universalidade do Serviço Nacional de Saúde, continuamos a verificar que as variáveis socioeconómicas desempenham ainda um papel no acesso aos cuidados de saúde dos adultos e idosos hipertensos, potenciando iniquidades no acesso aos cuidados de saúde nesta população. Torna-se assim imperativo o desenvolvimento deste tipo de estudos não só para utentes portadores de hipertensão arterial, mas também para com outras morbilidades e patologias, beneficiando desta tipologia de análise.ABSTRACT - Introduction: Over the years, several studies have reinforced the premise that an individual's socioeconomic factors can positively or negatively affect their access to health care, extending or reducing their waiting time. The aim of this research work was to carry out an analysis of equity and inequality in health care access, in the context of waiting times, among hypertensive adult and elderly patients in Portugal. Methodology: An observational, cross-sectional, analytical study was carried out with the collection of retrospective information based on data collected through the 2019 National Health Survey, carried out by the Instituto Nacional de Estatística. All participants selected for the analysis resided in Portugal, had an age equal to or over 18 years and were suffering from arterial hypertension. Results: Data collected from 4471 participants in the 2019 National Health Survey, residing in Portugal, were analyzed. After performing the bivariate analysis and multivariate analysis, it was found that socioeconomic variables such as income level, where individuals in the 4th (OR=0.722; p=0.026) and 5th quintile (OR=0.607; p=0.008) tend to report a shorter waiting time when compared to the other income brackets. These two income brackets appear again as protective factors regarding the basis for their waiting, not attributing distance or access to transport as the cause of their waiting. Conclusions: Although there are several national and international studies from past years that point to similar conclusions. We can see that despite the measures taken and the universality of the National Health Service, we continue to see that socioeconomic variables still play a role in the access to health care of hypertensive adults and elderly people, increasing inequities in access to health care in this population. Therefore, it is imperative to develop this type of study, not only for patients with arterial hypertension, but also with other morbidities and pathologies, benefiting from this type of analysis

Program Evaluation of a Hospital Patient Transportation Service

A hospital inpatient transportation process may decrease the time it takes patients to receive care and improve hospital quality and safety outcomes by providing timely and efficient patient handling. Grounded in agency theory, the purpose of this program evaluation was to evaluate the efficacy of the request for transport to measure against hospital objectives. Two specific program goals were to achieve an average 19-minute transport request-to-completion time and a 10-minute response from the time transport request is received when the transporter arrives. Data were collected from a survey, semistructured interviews, focus groups, and archival data analysis. The one sample t-test results indicated that the transportation department transport request-to-completion time was significantly less than the average 19-minute objective, t(62,260) = -302.82, p = .001. However, the time transport request received to the time the transporter arrived results indicated that the transportation department wait time was significantly greater than 10 minutes, t(62,260) = 33.60, p = .001. This result further showed that, on average, patients wait 2 minutes longer than the desired goal of 10 minutes. A key theme emerged from the thematic analysis indicating the lack of coordination caused a hospital staff perception of delay in transporter response. A key recommendation is to develop a structured hospital committee to reduce lab completion and doctor order delays to improve the time it takes to prepare the patient for transportation. The implications for positive social change include the potential for increased patient safety, satisfaction, and quality of care

Mejora del proceso de carga en vehículos eléctricos

El sector del transporte es uno de los mayores consumidores de energía, que en la práctica totalidad proviene de la combustión de los derivados del petróleo, con la consiguiente emisión de gases de efecto invernadero. Esto está provocando que en las ciudades aumenten los niveles de contaminación, llegando a ser en muchos casos altamente nocivos para la salud, y obligando a que las autoridades tengan que tomar medidas restrictivas, controlando el tráfico de vehículos de combustión en el centro de las ciudades, o incluso llegándolo a prohibir. Como solución a este problema nace un concepto, la electromovilidad, o la capacidad de utilizar medios de transporte que usan tecnologías basadas en la electricidad, siendo el vehículo eléctrico su mayor referente. Las ventas de este tipo de vehículos están aumentando año tras año, ya que están comenzando a representar una opción atractiva para muchos conductores. La combinación de Vehículos Eléctricos, con las tecnologías de la información (TIC) y el Internet de las cosas (IoT) será de gran importancia en las Smart Cities. Un objetivo de este tipo de ciudades será el uso eficiente de la energía, ya que satisfacer la gran demanda eléctrica en la red de transporte eléctrico que puede provocar estos vehículos es un reto al que nos tendremos que enfrentar.En el presente trabajo, hemos propuesto una arquitectura que facilita la recarga ordenada de los vehículos y la estimación de la energía necesaria con cierta antelación. Hemos implementado un simulador de recarga de vehículos eléctricos, que permite simular un gran número de vehículos, teniendo en cuenta tanto las características específicas de los mismos, como las tarifas reales de la electricidad en España. Además, se han propuesto nuevos métodos de recarga, con el propósito de maximizar el nivel de carga, reduciendo al máximo el coste de las recargas, basándonos en una solución descentralizada <br /