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Home Care (HC) providers are complex organizations that manage a large number of patients, different categories of operators, support staff and material resources in a context affected by high variability. Hence, robust resource planning is crucial for operations in HC organizations, in order to avoid process inefficiencies, treatment delays, and low quality of service. Under continuity of care, one of the main issues in HC planning is the assignment of a reference nurse to each assisted patient, because this decision has an impact on the workload assigned to the nurse for the entire patient's length of stay. In this paper, we derive an analytical structural policy for solving the nurse-to-patient assignment problem in the HC context under continuity of care. This policy accounts for the randomness that is related to the demands from patients already assigned to nurses and to the demands from new patients who need assignments. The policy is compared to other previously developed approaches, and applied to a relevant real case.

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Twenty years ago, the field of Robotics was defined and galvanized by the creation of an IEEE Journal devoted to the topic. We now have the opportunity to do the same for the field of Automation. The IEEE voted in February 2003 to bifurcate the IEEE Transactions on Robotics and Automation, the top-cited archival publication on robotics. The renamed Transactions on Robotics will gain a sibling: the Transactions on Automation Science and Engineering.T-ASE will publish foundational research on Automation: scientific methods and technologies that improve efficiency, productivity, quality, and reliability, specifically for methods, machines, and systems operating in structured environments over long periods, and the explicit structuring of environments. Its coverage will go beyond Automation's roots in mass production and include many new applications areas, such as Biotechnology, pharmaceutical, and health care; Home, service, and retail; Construction, transportation, and security; Manufacturing, maintenance, and supply chains; and Food handling and processing. Research includes topics related to robots and intelligent machines/systems in structured environments and the explicit structuring of environments, and topics at the Operational/Enterprise levels such as System Modeling, Analysis, Performance Evaluation; Planning, Scheduling, Coordination; Risk Management; and Supply Chain Management. T-ASE will integrate knowledge across disciplines and industries.Details on IEEE's motivation, distinctions between Robotics and Automation, scope statements, and sample application areas are available at: http://www.ieee.org/t-ase. The first issue will appear in July 2004.

Home care service is recognized to be one of the major solutions to contain costs in health care. However delivering this service is not an easy task because of the large number of actors that participate in the process, of the variety of clinical and organizational decisions, and last but not less important, of the difficulty of synchronizing human and material resources at patient's home. In this paper we propose a linear integer scheduling model developed to support human resource short term planning in home care. In particular, the model deals with the problem of deciding (a) which human resource should be used and (b) when to execute the service during the planning horizon, in order to satisfy the care plan for each patient served by the home care providers. The scheduling model has been tested on different real data sets collected from two Italian home care providers. The weekly plans generated by the proposed model have been compared with the real ones. The main result is a significant benefit, in terms of the increase in service quality and in efficiency, obtained by using operations research techniques in the home care short term planning

Home health care services play a crucial role in reducing the hospitalization costs due to the increase of chronic diseases of elderly people. At the same time, they allow us to improve the quality of life for those patients that receive treatments at their home. Optimization tools are therefore necessary to plan service delivery at patients' homes. Recently, solution methods that jointly address the assignment of the patient to the caregiver (assignment), the definition of the days (pattern) in which caregivers visit the assigned patients (scheduling), and the sequence of visits for each caregiver (routing) have been proposed in the scientific literature. However, the joint consideration of these three levels of decisions may be not affordable for large providers, due to the required computational time. In order to combine the strength and the flexibility guaranteed by a joint assignment, scheduling and routing solution approach with the computational efficiency required for large providers, in this study we propose a new family of two-phase methods that decompose the joint approach by incrementally incorporating some decisions into the first phase. The concept of pattern is crucial to perform such a decomposition in a clever way. Several scenarios are analyzed by changing the way in which resource skills are managed and the optimization criteria adopted to guide the provider decisions. The proposed methods are tested on realistic instances. The numerical experiments help us to identify the combinations of decomposition techniques, skill management policies and optimization criteria that best fit with problem instances of different size