239. Fairness over time for the allocation and scheduling of teams in home healthcare services
Contributed abstract in session FA-4: Home Care /2, stream Regular talks.
Friday, 9:20-10:30Room: Room S3
Authors (first author is the speaker)
| 1. | Alberto Guastalla
|
| Dipartimento di Informatica, Università degli Studi di Torino | |
| 2. | Roberto Aringhieri
|
| Dipartimento di Informatica, Università degli Studi di Torino | |
| 3. | Matteo Di Cunzolo
|
| Dipartimento di Informatica, Università degli Studi di Torino | |
| 4. | Semih Yalçındağ
|
| Yeditepe University | |
| 5. | Mario Bifulco
|
| Computer science, University of Turin | |
| 6. | Franco Sansonetti
|
| Computer science, University of Turin |
Abstract
Home Health Care (HHC) service plays an important role in reducing the hospitalization costs while improving the quality of life of those patients who receive treatments at their home. HHC is one of the important services where the service providers have to deal with various complex operational
problems such as the assignment, scheduling and routing decisions under various objectives and constraints.
In this work, we focus on the long-term assignment and weekly scheduling decisions under full continuity of care. To this end, a new framework have been developed to assign patients to medical teams and to decide their weekly visiting plans, both under fairness considerations. Including fairness within an optimization approach could be a challenging task in terms of metrics and mathematical modeling. We explore the idea of fairness over time that is the unfairness of a single period can be
smoothed in the long run.
The framework has two steps. In the initialization phase a model is formulated in order to assign the patients to the teams according to visit requirements, skill compatibilities and daily team capacities.
In the second phase, an adaptation of the same model assigns new patients to teams matching their need and considering the discharge of ongoing
patients in such a way to keep balanced the workloads of the teams.
We provide some preliminary results on real data provided by Molinette Hospital in Turin, partner of the Circular Health for Industry (CH4I) project.
Keywords
- Home care and Long Term Care
- Workforce planning and scheduling
Status: accepted
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