title: Markov decision process applied to the control of hospital elective admissions.
abstract: OBJECTIVE
  To present a decision model for elective (non-emergency) patient admissions control for distinct specialties on a periodic basis. The purpose of controlling patient admissions is to promote a more efficient utilization of hospital resources, thereby preventing idleness or excessive use of these resources, while considering their relative importance.
  
  
  METHODS
  The patient admission control is modeled as a Markov decision process. A hypothetical prototype is implemented, applying the value iteration algorithm.
  
  
  RESULTS
  The model is able to generate an optimal admission control policy that maintains resource consumption close to the desired levels of utilization, while optimizing the established deviation costs.
  
  
  CONCLUSIONS
  This is a complex model due to its stochastic dynamic and dimensionality. The model has great potential for application, and requires the development of customized solution methods.
authors.affiliation: Sarah Network of Rehabilitation Hospitals, SMHS Quadra 501 Conjunto A, Brasília, DF 70330-150, Brazil. guilherme@sarah.br
authors.forename: Luiz Guilherme Nadal
authors.initials: LG
authors.lastname: Nunes
authors.forename: Solon Venâncio
authors.initials: SV
authors.lastname: de Carvalho
authors.forename: Rita de Cássia Meneses
authors.initials: Rde C
authors.lastname: Rodrigues
mesh_terms: D000465:Algorithms; D006760:Hospitalization; D008390:Markov Chains; D010343:Patient Admission; D013269:Stochastic Processes