Search Results (8)

Home health care companies provide health care services to patients in their homes. Due to increasing demand, the provision of home health care services requires effective management of operational costs while satisfying both patients and caregivers. In practice, uncertain service times might lead to considerable delays that adversely affect service quality. To this end, this paper proposes a new bi-objective optimization problem to model the routing and scheduling problems under uncertainty in home health care, considering the qualification and workload of caregivers. A mixed-integer linear programming formulation is developed. Motivated by the challenge of computational time, we propose the Adaptive Large Neighborhood Search embedded in an Enhanced Multi-Directional Local Search framework (ALNS-EMDLS). A stochastic ALNS-EMDLS is introduced to handle uncertain service times for patients. Three kinds of metrics for evaluating the Pareto fronts highlight the efficiency of our proposed method. The sensitivity analysis validates the robustness of the proposed model and method. Finally, we apply the method to a real-life case and provide managerial recommendations. Full article

Home care centers face both an increase in demand and many variations during the execution of routes, compromising the routes initially planned; robust solutions are not effective enough, and it is necessary to move on to resilient approaches. We create a close-to-reality use case supported by interviews of staff at home health care centers, where caregivers are faced with unexpected events that compromise their initial route. We model, analyze, and compare two resilient approaches to deal with these disruptions: a distributed collaborative approach and a centralized collaborative approach, where we propose a centralization and sharing of information to improve local decision-making. The latter reduces the number of late arrivals by 11%, the total time of late arrival by 21%, and halves the number of routes exceeding the end of work time (contrary to the distributed collaborative approach due to the time wasted reaching colleagues). The use of a device, such as a smartphone application, to centralize and share information thus, allows better mutual assistance between caregivers. Moreover, we highlight several possible openings, like the coupling of simulation and optimization, to propose a more resilient approach. Full article

The increase in life expectancy has led to a growing demand for Home Health Care (HHC) services. However, some problems can arise in the management of these services, leading to high computational complexity and time-consuming to obtain an exact and/or optimal solution. This study intends to contribute to an automatic multi-criteria decision-support system that allows the optimization of several objective functions simultaneously, which are often conflicting, such as costs related to travel (distance and/or time) and available resources (health professionals and vehicles) to visit the patients. In this work, the HHC scheduling and routing problem is formulated as a multi-objective approach, aiming to minimize the travel distance, the travel time and the number of vehicles, taking into account specific constraints, such as the needs of patients, allocation variables, the health professionals and the transport availability. Thus, the multi-objective genetic algorithm, based on the NSGA-II, is applied to a real-world problem of HHC visits from a Health Unit in Bragança (Portugal), to identify and examine the different compromises between the objectives using a Pareto-based approach to operational planning. Moreover, this work provides several efficient end-user solutions, which were standardized and evaluated in terms of the proposed policy and compared with current practice. The outcomes demonstrate the significance of a multi-criteria approach to HHC services. Full article

The Long-Term Care (LTC) industry mainly comprises networks managed by providers of services other than informal caregivers and government agencies. Among the providers are the local providers of community-based services. The segment still consists of mostly small businesses. As such, it needs many improvements in logistics, information and communication technology (ICT) support, and educational programs, specifically in the ADRION region, where the rural areas require a high percentage of travel time in a working day for service providers. The demand for LTC services must be known early enough for providers to adapt to the growth of these demands, and they also need methods to support decisions on how to optimize the number of care workers to be able to plan the necessary human resources in the long term. The results are based on the authors’ previous studies of sustainable hierarchical spatial systems. The paper presents the achievements of these research activities and policies, governance and financing in the hierarchically organized services and networks of educational programs for human resources and ICT innovations in LTC, which are currently in short supply. Projections of capacities from facilities are necessary. Logistic networks to human resources are based on geo-gerontological projections, such as the multistate transition model, which is a new achievement in this area, and the adequate norms and standards of these services. The optimal number of human resources is based on the combination of the Patterson-Albracht algorithm and Multiple Travelling Salesman Problem (mTSP), as a new Home Health Care Routing and Scheduling Problem (HHCRSP), which helps in ensuring the inclusion of travel time in the concept of norms and standards, to achieve a work balance and care schedule according to the wishes of clients. The proposed approach might help professionals adapt in advance to the coming changes caused by the growing number of seniors and rapid changes in technology, and might also help in considerations as to whether the priorities of clients should be included in the basic national insurance programs or additionally charged as a higher standard of home care services. The aim is to make care and supply networks as sustainable as possible. Full article

In recent years, the management of health systems is a main concern of governments and decision-makers. Home health care is one of the newest methods of providing services to patients in developed societies that can respond to the individual lifestyle of the modern age and the increase of life expectancy. The home health care routing and scheduling problem is a generalized version of the vehicle routing problem, which is extended to a complex problem by adding special features and constraints of health care problems. In this problem, there are multiple stakeholders, such as nurses, for which an increase in their satisfaction level is very important. In this study, a mathematical model is developed to expand traditional home health care routing and scheduling models to downgrading cost aspects by adding the objective of minimizing the difference between the actual and potential skills of the nurses. Downgrading can lead to nurse dissatisfaction. In addition, skillful nurses have higher salaries, and high-level services increase equipment costs and need more expensive training and nursing certificates. Therefore, downgrading can enforce huge hidden costs to the managers of a company. To solve the bi-objective model, an ε-constraint-based approach is suggested, and the model applicability and its ability to solve the problem in various sizes are discussed. A sensitivity analysis on the Epsilon parameter is conducted to analyze the effect of this parameter on the problem. Finally, some managerial insights are presented to help the managers in this field, and some directions for future studies are mentioned as well. Full article

Development of an efficient and effective home health care (HHC) service system is a quite recent and challenging task for the HHC firms. This paper aims to develop an HHC service system in the perspective of long-term economic sustainability as well as operational efficiency. A more flexible mixed-integer linear programming (MILP) model is formulated by incorporating the dynamic arrival and departure of patients along with the selection of new patients and nursing staff. An integrated model is proposed that jointly addresses: (i) patient selection; (ii) nurse hiring; (iii) nurse to patient assignment; and (iv) scheduling and routing decisions in a daily HHC planning problem. The proposed model extends the HHC problem from conventional scheduling and routing issues to demand and capacity management aspects. It enables an HHC firm to solve the daily scheduling and routing problem considering existing patients and nursing staff in combination with the simultaneous selection of new patients and nurses, and optimizing the existing routes by including new patients and nurses. The model considers planning issues related to compatibility, time restrictions, contract durations, idle time and workload balance. Two heuristic methods are proposed to solve the model by exploiting the variable neighborhood search (VNS) approach. Results obtained from the heuristic methods are compared with a CPLEX based solution. Numerical experiments performed on different data sets, show the efficiency and effectiveness of the solution methods to handle the considered problem. Full article

The aggravating trend of the aging population, the miniaturization of the family structure, and the increase of families with empty nesters greatly affect the sustainable development of the national economy and social old-age security system of China. The emergence of home health care or home care (HHC/HC) service mode provides an alternative for elderly care. How to develop and apply this new mobile service mode is crucial for the government. Therefore, the pertinent optimization problems regarding HHC/HC have constantly attracted the attention of researchers. Unexpected events, such as new requests of customers, cancellations of customers’ services, and changes of customers’ time windows, may occur during the process of executing an a priori visiting plan. These events may sometimes make the original plan non-optimal or even infeasible. To cope with this situation, we introduce disruption management to the real-time home caregiver scheduling and routing problem. The deviation measurements on customers, caregivers, and companies are first defined. A mathematical model that minimizes the weighted sum of deviation measurements is then constructed. Next, a tabu search (TS) heuristic is developed to efficiently solve the problem, and a cost recorded mechanism is used to strengthen the performance. Finally, by performing computational experiments on three real-life instances, the effectiveness of the TS heuristic is tested, and the advantages of disruption management are analyzed. Full article

As a new service model, home health care can provide effective health care by adopting door-to-door service. The reasonable arrangements for nurses and their routes not only can reduce medical expenses, but also can enhance patient satisfaction. This research focuses on the home health care scheduling optimization problem with known demands and service capabilities. Aimed at minimizing the total cost, an integer programming model was built in this study, which took both the priorities of patients and constraints of time windows into consideration. The genetic algorithm with local search was used to solve the proposed model. Finally, a case study of Shanghai, China, was conducted for the empirical analysis. The comparison results verify the effectiveness of the proposed model and methodology, which can provide the decision support for medical administrators of home health care. Full article