Validation of a new data-driven SLOSR ICU efficiency measure compared to the traditional SRU

Affiliations

¹ Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rua Marquês de São Vicente, 225, Rio de Janeiro, Rio de Janeiro, 22451-900, Brazil. igor.peres@puc-rio.br.
² Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rua Marquês de São Vicente, 225, Rio de Janeiro, Rio de Janeiro, 22451-900, Brazil.
³ D'Or Institute for Research and Education (IDOR), Rua Diniz Cordeiro, 30, Rio de Janeiro, Rio de Janeiro, 22281-100, Brazil.
⁴ Department of Critical and Intensive Care Medicine, Academic Hospital Fundación Santa Fe de Bogota, Carrera 7 117-15, Bogotá, Colombia.

Igor Tona Peres et al. Intensive Care Med. 2023 Dec.

. 2023 Dec;49(12):1546-1548.

doi: 10.1007/s00134-023-07255-w. Epub 2023 Nov 3.

¹ Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rua Marquês de São Vicente, 225, Rio de Janeiro, Rio de Janeiro, 22451-900, Brazil. igor.peres@puc-rio.br.
² Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rua Marquês de São Vicente, 225, Rio de Janeiro, Rio de Janeiro, 22451-900, Brazil.
³ D'Or Institute for Research and Education (IDOR), Rua Diniz Cordeiro, 30, Rio de Janeiro, Rio de Janeiro, 22281-100, Brazil.
⁴ Department of Critical and Intensive Care Medicine, Academic Hospital Fundación Santa Fe de Bogota, Carrera 7 117-15, Bogotá, Colombia.

No abstract available

References

1. Peres IT, Hamacher S, Oliveira FLC, Bozza FA, Salluh JIF (2021) Prediction of intensive care units length of stay: a concise review. Rev Bras Ter Intensiv 33:183–187 - DOI
1. Quintairos A, Pilcher D, Salluh JI (2023) Icu scoring systems. Intensive Care Med 49(2):223–225 - DOI - PubMed
1. Rothen HU, Stricker K, Einfalt J, Bauer P, Metnitz PG, Moreno RP, Takala J (2007) Variability in outcome and resource use in intensive care units. Intensive Care Med 33:1329–1336 - DOI - PubMed
1. Peres IT, Hamacher S, Oliveira FLC, Bozza FA, Salluh JIF (2022) Data-driven methodology to predict the icu length of stay: a multicentre study of 99,492 admissions in 109 brazilian units. Anaesth Crit Care Pain Med 41(6):101142 - DOI - PubMed
1. Zampieri FG, Soares M, Borges LP, Salluh JIF, Ranzani OT (2017) The epimed monitor icu database®: a cloud-based national registry for adult intensive care unit patients in brazil. Rev Bras Terp Intensiv 29:418–426