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Home healthcare agencies are an alternative to standard medical or paramedical organizations, providing services directly to the beneficiary’s home. The aging of Western populations is accompanied by an increase in the number of vulnerable people and an explosion in demand for home healthcare and associated services (Guinet 2014), to which the organizations concerned must adapt. Service routing and scheduling is usually done by hand by experienced employees but this is time-consuming and extremely complex on a large scale. The design of decision support tools is becoming essential to automate the routing and scheduling process and build schedules that are satisfactory for the employer, the careworkers and the beneficiaries.

Having effective solutions to plan interventions is unfortunately not always sufficient to meet the challenge of routing and scheduling in the home care sector. Indeed, many eventualities can make a theoretically optimal schedule unfeasible. It is thus necessary to update the schedules to compensate for these unforeseen events. We are particularly interested in changes in the configuration of staff and beneficiaries of a home healthcare organization. Over the weeks, a beneficiary’s state of health can deteriorate, which in turn leads to changes in their needs and therefore in the services required, or even bidding farewell to the organization in the event they require hospitalization, for example. When beneficiaries leave, the establishment can, if the number of careworkers is high enough, accept new beneficiaries who will have to be included in the schedules. Likewise, there is a high turnover of staff because the careworkers are often subjected to difficult, stressful working conditions.

From a strategic, decision-making point of view, it would be inappropriate to recalculate optimal routes every time the schedules are disrupted. In a context where the human aspect is essential, it is necessary to take into account the schedule in progress, the assignments of careworkers or even the start time of the interventions, in order to satisfactorily reconstruct disrupted routes. Indeed, continuity is a key factor in patient satisfaction. Consequently continuity of care constraints must be respected by, on the one hand, keeping fixed start and end times (these are also defined contractually) and on the other hand, always assigning the same group of careworkers to the same patients. In order not to aggravate these instabilities, it is also crucial to take careworker satisfaction into account. Schedules that are not satisfactory for the staff increase staff turnover, which impacts the company’s quality of service. In a field where competition is increasingly fierce (Béguin 2018), providing good working conditions is not only a central argument for recruiting qualified careworkers but it also plays a decisive role in limiting turnover.

It is important to note that updating long-term schedules consists of creating new sustainable weekly or monthly schedules, in line with changes to staff and beneficiaries, while short-term rescheduling instead aims to provide a quick fix to the problem; for example, a daily schedule compromised by a one-off disruption, such as the sudden absence of a worker for a day.

In this chapter, we present a prototype developed to respond to a long-term weekly rerouting and rescheduling problem encountered by a home care services company operating in Auvergne Rhône-Alpes, France: Adomni-Quemera. We first offer a brief review of existing work on this theme in the literature, followed by a more specific description of the problem under consideration. In section 1.4, we briefly advance our resolution strategy, before presenting the prototype developed to propose solutions in a practical setting in section 1.5. The experiments carried out on real data are detailed in section 1.6. Finally, we approach avenues of research for future work in section 1.7.