Who is doing what in home care services?

Background: This paper investigates the distribution of work hours by activity, for the main staff categories in home care services in three rural Norwegian municipalities. In Norway these categories are registered nurses, assistant nurses and assistant health workers. (2) Methods: The three categories of home care staff recorded 20,964 eligible observations over 8 weeks. We identified 19 activities, which were recorded. The majority of staff used a smartphone application for the time measuring, while some staff used a manual form for reporting purposes. (3) Results: The registered nurses (RNs) spent 32% of their time on direct patient work, while driving accounted for 18%. Direct patient work and driving accounted for the majority of activities performed by assistant nurses (48% and 29%, respectively) and assistant health workers (70% and 17%, respectively). (4) Conclusions: The demand for home care services is increasing in terms of both size and complexity. Simultaneously, there is a growing shortage of skilled staff. RNs is the group with the least face-toface time with patients. To meet the patients’ needs, it is necessary to discuss and modify existing home care service systems in order to use resources appropriately and effectively. Keywords: home care, staffing, health care organizations and systemspublishedVersio

Dynamically accepting and scheduling patients for home healthcare

The importance of home healthcare is growing rapidly since populations of developed and even developing countries are getting older and the number of hospitals, retirement homes, and medical staff do not increase at the same rate. We consider the Home Healthcare Nurse Scheduling Problem where patients arrive dynamically over time and acceptance and appointment time decisions have to be made as soon as patients arrive. The objective is to maximise the average number of daily visits for a single nurse. For the sake of service continuity, patients have to be visited at the same day and time each week during their episode of care. We propose a new heuristic based on generating several scenarios which include randomly generated and actual requests in the schedule, scheduling new customers with a simple but fast heuristic, and analysing results to decide whether to accept the new patient and at which appointment day/time. We compare our approach with two greedy heuristics from the literature, and empirically demonstrate that it achieves significantly better results compared to these other two methods

Distribuição dos utentes na Rede Nacional de Cuidados Continuados Integrados do Alentejo

Mestrado em Decisão Económica e EmpresarialEsta pesquisa aborda a Rede Nacional de Cuidados Continuados Integrados (RNCCI) em Portugal, focando-se na especialidade de unidade de cuidados continuados de internamento com o objetivo de criar uma distribuição dos utentes pelas unidades da zona do Alentejo. Após recolha dos dados, disponibilizados na internet, procedeu-se ao seu estudo e tratamento. Seguidamente, num ambiente de planeamento a nível tático, procedeu-se à distribuição dos utentes conforme a área inserida no estudo e a quantidade de camas que cada zona da referida área tem disponível ao ano. Esta distribuição foi feita minimizando o custo total de internamentos nas respetivas zonas, custo este que contabiliza as despesas relacionadas com o transporte e internamento para todas as unidades abrangidas pelo estudo. De modo a aplicar os conhecimentos adquiridos no mestrado, no que toca a Investigação Operacional, utiliza-se neste estudo um modelo de otimização, particularmente, um modelo de tipo de transportes de programação linear.O software utilizado na resolução do problema foi o Solver do Microsoft Office Excel. Com esta abordagem ao problema de planeamento de distribuição de utentes na RNCCI do Alentejo, pretende-se dar ênfase ao progresso da RNCCI em Portugal, disponibilizando uma ferramenta que pode ser usada pelos gestores no âmbito da saúde.This research reports the National Network for Continuous Care (RNCCI), in Portugal, focusing on admission of patients in continuous care units. The intent of this work is to create a distribuition network for users of the Alentejo region. After data collection, available on the internet, we proceeded with the study and treatment of data. Afterwards, in the tactical planning setting, we proceeded with the distribution of users depending on the residential area and the number of beds available per year in each zone. This distribution was performed to reduce the total cost of hospitalization, a cost wich covers expenses related to transport and admission in the units covered by the study. In order to deepen the knowledge acquired in the master degree courses, with respect to operational research, in this study an optimization model is developed a linear programming transportation problem. The software used for solving the problem was the Solver of Microsoft Office Excel. With this approach to the problem of planning the distribution of users in the RNCCI of Alentejo region, we intend to emphasize the progress of the RNCCI in Portugal, and provide a tool that can be used by health policy makers.info:eu-repo/semantics/publishedVersio

Developing service supply chains by using agent based simulation

The Master thesis present a novel approach to model a service supply chain with agent based simulation. Also, the case study of thesis is related to healthcare services and research problem includes facility location of healthcare centers in Vaasa region by considering the demand, resource units and service quality. Geographical information system is utilized for locating population, agent based simulation for patients and their illness status probability, and discrete event simulation for healthcare services modelling. Health centers are located on predefined sites based on managers’ preference, then each patient based on the distance to health centers, move to the nearest point for receiving the healthcare services. For evaluating cost and services condition, various key performance indicators have defined in the modelling such as Number of patient in queue, patients waiting time, resource utilization, and number of patients ratio yielded by different of inflow and outflow. Healthcare managers would be able to experiment different scenarios based on changing number of resource units or location of healthcare centers, and subsequently evaluate the results without necessity of implementation in real life.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Planning the delivery of home-based long-term care: A mathematical programming-based tool to support routes' planning

The adequate planning of home-based long-term care (HBLTC) is essential in the current European setting where long-term care (LTC) demand is increasing rapidly, and where home-based care represents a potential cost-saving alternative from traditional inpatient care. Particularly, this planning should involve proper route planning to ensure visits of health professionals to patients’ homes. Nevertheless, literature in the specific area of HBLTC planning is still scarce. Accordingly, this paper proposes a tool based on a mathematical programming model – the LTCroutes – for supporting the daily planning of routes to visit LTC patients’ homes in National Health Service-based countries. The model allows exploring the impact of considering different objectives relevant in this sector, including the minimization of costs and the maximization of service level. Patients’ preferences, traffic conditions and budget constraints are also considered in the proposed model. To illustrate the applicability of the model, a case study based on the National Network of LTC in Portugal (RNCCI) is analysed.O planeamento adequado de cuidados continuados ao domicílio é essencial na conjuntura atual Europeia em que a procura de cuidados continuados está a aumentar rapidamente, e em que os cuidados ao domicílio representam uma alternativa com potencial de poupança de custos relativamente ao tradicional internamento hospitalar. Particularmente, é necessário haver um planeamento adequado das rotas dos profissionais de saúde às casas dos pacientes. No entanto, a literatura na área específica de planeamento de cuidados continuados ao domicílio ainda é escassa. Nesse sentido, este artigo propõe uma ferramenta baseada num modelo de programação matemática - o LTCroutes - para apoiar o planeamento diário das rotas para visitar as casas dos pacientes com necessidade de cuidados continuados em países com Serviço Nacional de Saúde. O modelo desenvolvido permite explorar o impacto de considerar diferentes objetivos relevantes neste setor, incluindo a minimização de custos e a maximização do nível de serviço. As preferências dos pacientes, condições de trânsito e restrições de orçamento também são consideradas no modelo proposto. Para ilustrar a aplicabilidade do modelo, é analisado um caso de estudo baseado na Rede Nacional de Cuidados Continuados Integrados (RNCCI) em Portugal

O problema de roteamento e escalonamento de profissionais de saúde: The home healthcare routing and scheduling problem

Problema de Roteamento e Escalonamento de Profissionais de Saúde consiste em determinar a melhor rota para profissionais de saúde para atendimento domiciliar. Existem diversas variantes deste problema que diferem nas restrições e funções objetivo. Este artigo apresenta uma revisão da literatura, com o objetivo de identificar os problemas de roteamento utilizados pelos autores, os diferentes tipos de função objetivo, e as técnicas de solução utilizadas

Prise en compte des préférences du décideur pour le problème multi-objectif de tournées de soins à domicile

RÉSUMÉ : Les services de soins à domicile regroupent un ensemble de services sociaux et médicaux dispensés à domicile plutôt que dans un établissement de santé. Ils visent, entre autres, à aider les patients à conserver leur autonomie, à améliorer leur état de santé et à maintenir leur qualité de vie. Au Canada, ce type de soins est apparu dans les années 1970 et a connu une très forte croissance ces dix dernières années. Cela peut être en partie expliqué par le vieillissement de la population, par les progrès dans les domaines de la médecine et des technologies de l’information, mais également par un nombre limité de places dans les hôpitaux et par des économies réalisées comparativement aux mêmes soins prodigués dans des instituts spécialisés. En lien avec cette évolution et d’un point de vue opérationnel, apparaît le problème d’optimisation de tournées de soins à domicile. Il consiste à déterminer les trajets (itinéraires) d’un ensemble de soignants pour chaque jour de travail sur un horizon de planification afin de répondre, le mieux possible, à la demande en soins ou en services des patients. Ce problème a fait l’objet de nombreuses recherches notamment durant cette dernière décennie. En particulier, l’aspect multi-objectif des tournées de soins à domicile constitue le point central de ce mémoire. Il s’agit d’un élément important, mais relativement peu étudié. De fait, lors de la résolution de ce problème, de nombreux critères, souvent contradictoires, sont à considérer simultanément (Ex : temps de trajet, heures supplémentaires, continuité de soins, ...) et à cela s’ajoute la difficulté que pose l’évaluation de la qualité des solutions. En effet, la notion de meilleure solution pour l’optimisation dans le cas d’un objectif unique est remplacée par celle de meilleurs compromis pour l’optimisation dans le cas d’objectifs multiples. Plus spécifiquement, ces meilleurs compromis sont des solutions pour lesquelles il est impossible d’améliorer un objectif sans en détériorer un autre. En ce qui concerne les soins à domicile, plusieurs structures, publiques et privées, gèrent et organisent les ressources de santé. Chacune de ces structures suit sa propre politique et a ses propres priorités. Ainsi, dans cette situation, choisir la solution qui correspond le mieux à chaque utilisateur est une décision complexe. Le projet présenté dans ce mémoire a été réalisé en collaboration avec un partenaire industriel, AlayaCare. La compagnie fournit à ces structures un logiciel aidant à la gestion des ressources. Le but étant d’améliorer l’outil d’optimisation existant, basé sur une métaheuristique, afin qu’il puisse s’adapter plus aisément à la multiplicité des utilisateurs. Pour ce faire, nous avons remplacé la somme pondérée, utilisée pour évaluer les solutions, par une comparaison lexicographique reposant sur un ordre hiérarchique. Cette méthode a l’avantage d’être plus intuitive et plus simple d’utilisation pour le décideur, car elle s’affranchit de la délicate tâche qu’est l’estimation des poids attribués à chaque objectif. Afin d’apporter un meilleur support de décision, nous nous sommes également intéressés aux solutions alternatives suggérées au décideur. En effet, l’ordre hiérarchique établi est stricte, mais l’utilisateur peut trouver acceptable de détériorer légèrement un objectif si cela entraîne une grande amélioration pour un objectif moins bien classé. C’est pourquoi le concept de tolérance a été associé à celui de Pareto-optimalité pour offrir des solutions alternatives, à la fois proches de la meilleure solution du point de vue hiérarchique et à la fois pertinentes, car non-dominées par les solutions générées lors du processus d’optimisation. Cette méthode a été testée sur des instances provenant de notre partenaire industriel. Les résultats montrent que la meilleure solution retournée par la nouvelle méthode (selon l’ordre hiérarchique strict) est proche de celle obtenue avec la somme pondérée, mais, contrairement à celle-ci, ne requiert pas de connaissances en mathématiques ou en optimisation, ce qui présente un avantage certain dans le cadre d’une application réelle. Enfin, nous observons également l’intérêt des modifications apportées pour sélectionner les solutions alternatives, Pareto-optimales du point de vue multi-objectif et parmi lesquelles seul le décideur pourra trancher.----------ABSTRACT : Home health care services offer a wide range of services in patient homes rather than in medical facilities. They serve various purposes as helping individuals cope with long-term medical conditions, illness or injury. In Canada, this type of services started developing around 1970 then quickly grew in popularity during the last decades. This is due to several factors such as aging population, medical developments, progress in information technologies, hospital congestion and reduced cost of home treatments. As a result of these changes, emerged various operational problems, including the Home Health Care Routing and Scheduling Problem (HHCRSP). The HHCRSP is interested in determining the assignment of home visits to a set of caregivers over the course of a planning horizon, and the routing of these caregiver workdays while insuring the best care possible for every patient. A large number of research were interested in solving this difficult problem but few of them tackled its multi-objective aspect. It is however an important and challenging part of the problem. In fact, in the process of assigning routes to home health care workers, schedulers consider simultaneously various conflicting criteria such as skill-set, availabilities, distance traveled, patient-worker relationship. Moreover, in multi-objective optimization, the concept of optimal solution is replaced by the concept of Pareto-optimal solutions. Finding these Pareto-optimal solutions can be a difficult task. Choosing one solution from them is very delicate and implies to express some preferences about the different possible trade-offs. As for the home health care environment, various public and private structures manage health care resources. These home health care structures have their own preferences and their own policies regarding the different objectives involved in the HHCRSP. For this project, we collaborated with the company AlayaCare. It offers an operations management platform for home health care agencies. We will focus in this thesis on the integration of users’ preferences into AlayaCare optimization tool. Our work is centered around the users’ perspective and especially, the method provided should be easily adaptable to their preferences. To do so, we combine a hierarchical optimization technique with a Pareto based approach. Tolerance parameters are introduced in order to display only relevant Pareto-optimal choices to the decision maker. The method is tested on instances provided by our industrial partner. The results show that the best hierarchical solution is similar to the one found with a weighted some approach. The main advantage of this method is that it does not require any optimization background and alleviates from the burden of finding the right weights. Furthermore, it provides interesting alternative solutions

Home care routing and scheduling problem with teams’ synchronization

Funding Information: This work is funded by Portuguese funds through the FCT - Fundação para a Ciência e a Tecnologia , I.P., under the scope of the projects UIDB/00297/2020 (Center for Mathematics and Applications), UIDB/00097/2020 (CEGIST), and the PhD scholarship grant SFRH/BD/148773/2019 . Publisher Copyright: © 2023 The AuthorsThe demand for home care (HC) services has steadily been growing for two main types of services: healthcare and social care. If, for the former, caregivers' skills are of utter importance, in the latter caregivers are not distinguishable in terms of skills. This work focuses social care and models caregivers' synchronization as a means of improving human resources management. Moreover, in social care services, several visits need to be performed in the same day since patients are frequently alone and need assistance throughout the day. Depending on the patient's autonomy, some tasks have to be performed by two caregivers (e.g. assist bedridden patients). Therefore, adequate decision support tools are crucial for assisting managers (often social workers) when designing operational plans and to efficiently assign caregivers to tasks. This paper advances the literature by 1) considering teams of one caregiver that can synchronize to perform tasks requiring two caregivers (instead of having teams of two caregivers), 2) simultaneously modelling daily continuity of care and teams' synchronization, and 3) associating dynamic time windows to teams' synchronizations introducing scheduling flexibility while minimize service and travel times. These concepts are embedded into a daily routing and scheduling MIP model, deciding on the number of caregivers and on the number and type of teams to serve all patient tasks. The main HC features of the problem, synchronization and continuity of care, are evaluated by comparing the proposed planning with the current situation of a home social care service provider in Portugal. The results show that synchronization is the feature that most increases efficiency with respect to the current situation. It evidences a surplus in working time capacity by proposing plans where all requests can be served with a smaller number of caregivers. Consequently, new patients from long waiting lists can now be served by the “available” caregivers.publishersversionpublishe

Planning the delivery of home social services: a mathematical programming-based approach to support routing and scheduling assignments

The increased average lifespan, together with low birth rates, are transforming the European Union's age pyramid. Currently, we are experiencing a transition towards a much older population structure. Given that the institutions that provide care to these population groups are limited by budgetary constraints, it is imperative to optimize several processes, among which route planning and staff scheduling stand out. This dissertation aims to develop a mathematical programming model to support the planning of routes and human resources for providers of Home Social Services. Beyond general Vehicle Routing Problems assumptions, the proposed model also considers the following features: i) working time regulations, ii) mandatory breaks, iii) users' autonomy, and iii) meals' distribution. The present model, implemented using GAMS software, focuses simultaneously on two objective functions: minimization of operating costs, and maximization of equity through the minimization of differences in teams' working times. Chebyshev's method was chosen to solve the developed multiobjective model. The model was built based on a Portuguese Private Institution of Social Solidarity. Through the application of the model, significant improvements are obtained when compared to the current planning of the partner institution, such as it is the case of an improved workload distribution between caregivers and routes that will result in lower costs for the institution. This model is fully enforceable to other institutions that provide services similar or equal to the institution used as a reference.O aumento da esperança média de vida, juntamente com baixas taxas de natalidade, estão a transformar a pirâmide etária da União Europeia. Atualmente, estamos a vivenciar uma transição direcionada para uma estrutura populacional muito mais envelhecida. Dado que as instituições que prestam cuidados a esta fração se encontram limitadas por restrições orçamentais, torna-se imperativo otimizar vários processos, dos quais se destacam planeamento de rotas e escalonamento de funcionárias. Esta dissertação visa introduzir um modelo de programação matemática com a finalidade de apoiar o planeamento de rotas e recursos humanos para prestadores de Serviços de Apoio Domiciliário. O modelo assenta, além dos pressupostos de um "Vehicle Routing Problem", nos seguintes: i) regulações de tempo de trabalho, ii) pausas obrigatórias, iii) autonomia dos utentes, e iv) distribuição de refeições. O modelo, desenvolvido através de software GAMS, foca-se em duas funções objetivo, simultaneamente: minimização dos custos operacionais, e maximização da equidade, através da minimização das diferenças nos tempos de trabalho das equipas. O método de Chebyshev foi o escolhido para desenvolver o modelo multiobjetivo. O modelo foi construído tendo por base uma Instituição Particular de Solidariedade Social em Portugal. Através da aplicação do modelo, obtêm-se melhorias significativas, quando comparado com o atual planeamento da instituição parceira, como é o caso de uma melhor distribuição da carga de trabalho entre as funcionárias e das rotas que resultam da redução dos custos operacionais da instituição. Este modelo é totalmente extensível a outras instituições que prestem serviços semelhantes ou iguais à instituição utilizada como referência