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Health Policy. 2018 Apr;122(4):412-421. doi: 10.1016/j.healthpol.2018.02.002. Epub 2018 Feb 15.

No-shows in appointment scheduling - a systematic literature review.

Author information

1
Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rua Marquês de São Vicente, 225, Rio de Janeiro, RJ, 22451-900, Brazil. Electronic address: leilafdantas@aluno.puc-rio.br.
2
Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rua Marquês de São Vicente, 225, Rio de Janeiro, RJ, 22451-900, Brazil. Electronic address: jfleck@puc-rio.br.
3
Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rua Marquês de São Vicente, 225, Rio de Janeiro, RJ, 22451-900, Brazil. Electronic address: cyrino@puc-rio.br.
4
Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rua Marquês de São Vicente, 225, Rio de Janeiro, RJ, 22451-900, Brazil. Electronic address: hamacher@puc-rio.br.

Abstract

No-show appointments significantly impact the functioning of healthcare institutions, and much research has been performed to uncover and analyze the factors that influence no-show behavior. In spite of the growing body of literature on this issue, no synthesis of the state-of-the-art is presently available and no systematic literature review (SLR) exists that encompasses all medical specialties. This paper provides a SLR of no-shows in appointment scheduling in which the characteristics of existing studies are analyzed, results regarding which factors have a higher impact on missed appointment rates are synthetized, and comparisons with previous findings are performed. A total of 727 articles and review papers were retrieved from the Scopus database (which includes MEDLINE), 105 of which were selected for identification and analysis. The results indicate that the average no-show rate is of the order of 23%, being highest in the African continent (43.0%) and lowest in Oceania (13.2%). Our analysis also identified patient characteristics that were more frequently associated with no-show behavior: adults of younger age; lower socioeconomic status; place of residence is distant from the clinic; no private insurance. Furthermore, the most commonly reported significant determinants of no-show were high lead time and prior no-show history.

KEYWORDS:

Appointments; Healthcare; No-show; Statistical analysis; Systematic review

PMID:
29482948
DOI:
10.1016/j.healthpol.2018.02.002
[Indexed for MEDLINE]

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