In recent years, there has been a growing interest in problems related to health facilities. Many authors proposed decision-support approaches to increase efficiency within hospital departments. An efficient use of healthcare resources reduces medical costs and provides better service to users. In this paper, we address patient admission scheduling problems, that consist in deciding which patient to admit, at what time and which room is assigned. Rooms have several characteristics and a limited capacity. These problems are very similar to those addressed in manufacturing process environments. Patients are similar to jobs with a processing time (length of stay), a start date, a due date, and they have to be assigned to an equipped machine (room) in a well-defined planning horizon. Overcrowded rooms are not allowed. Taking into account that a constraint on the maximum number of patients accommodated in every room is imposed, the authors propose an optimization model to make best use of the available resources. The proposed model is based on the initial assumption that the information is available in advance (offline approach). It is tested on a set of instances. Results are represented and discussed.

A decision support service for hospital bed assignment

Conforti, D.;Guido, R.;Mirabelli, G.;Solina, V.
2018

Abstract

In recent years, there has been a growing interest in problems related to health facilities. Many authors proposed decision-support approaches to increase efficiency within hospital departments. An efficient use of healthcare resources reduces medical costs and provides better service to users. In this paper, we address patient admission scheduling problems, that consist in deciding which patient to admit, at what time and which room is assigned. Rooms have several characteristics and a limited capacity. These problems are very similar to those addressed in manufacturing process environments. Patients are similar to jobs with a processing time (length of stay), a start date, a due date, and they have to be assigned to an equipped machine (room) in a well-defined planning horizon. Overcrowded rooms are not allowed. Taking into account that a constraint on the maximum number of patients accommodated in every room is imposed, the authors propose an optimization model to make best use of the available resources. The proposed model is based on the initial assumption that the information is available in advance (offline approach). It is tested on a set of instances. Results are represented and discussed.
Combinatorial Optimization; Healthcare Management; Scheduling; Business and International Management; Management of Technology and Innovation; Organizational Behavior and Human Resource Management; Strategy and Management1409 Tourism, Leisure and Hospitality Management; Management Science and Operations Research; Industrial and Manufacturing Engineering; Safety, Risk, Reliability and Quality; Waste Management and Disposal
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/289022
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact