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Incidence and predictors of case cancellation within 24 h in patients scheduled for elective surgical procedures.
Wongtangman, Karuna; Azimaraghi, Omid; Freda, Jeffrey; Ganz-Lord, Fran; Shamamian, Peter; Bastien, Alexandra; Mirhaji, Parsa; Himes, Carina P; Rupp, Samuel; Green-Lorenzen, Susan; Smith, Richard V; Medrano, Elilary Montilla; Anand, Preeti; Rego, Simon; Velji, Salimah; Eikermann, Matthias.
Afiliação
  • Wongtangman K; Department of Anesthesiology, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA; Department of Anesthesiology, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand. Electronic address: kwongtangm@montefiore.org.
  • Azimaraghi O; Department of Anesthesiology, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA. Electronic address: oazimaragh@montefiore.org.
  • Freda J; Vice President, Surgical Services, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA. Electronic address: jefreda@montefiore.org.
  • Ganz-Lord F; Department of Medicine, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA. Electronic address: fganzlord@montefiore.org.
  • Shamamian P; Department of Surgery, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA. Electronic address: PSHAMAMI@montefiore.org.
  • Bastien A; Department of Anesthesiology, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA. Electronic address: ABASTIEN@montefiore.org.
  • Mirhaji P; Center for Health Data Innovations, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA. Electronic address: parsa.mirhaji@einsteinmed.edu.
  • Himes CP; Department of Anesthesiology, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA.
  • Rupp S; Department of Anesthesiology, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA. Electronic address: srupp@montefiore.org.
  • Green-Lorenzen S; Operations, Montefiore Health System, USA. Electronic address: SGREEN@montefiore.org.
  • Smith RV; Otorhinolaryngology-Head and Neck Surgery, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA. Electronic address: RSMITH@montefiore.org.
  • Medrano EM; Department of Anesthesiology, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA. Electronic address: emontill@montefiore.org.
  • Anand P; Department of Anesthesiology, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA. Electronic address: pranand@montefiore.org.
  • Rego S; Department of Psychiatry and Behavioral Sciences, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA. Electronic address: SREGO@montefiore.org.
  • Velji S; Department of Psychiatry and Behavioral Sciences, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA. Electronic address: svelji@montefiore.org.
  • Eikermann M; Department of Anesthesiology, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA; Klinik für Anästhesiologie und Intensivmedizin, Universität Duisburg-Essen, Essen, Germany. Electronic address: meikermann@montefiore.org.
J Clin Anesth ; 83: 110987, 2022 12.
Article em En | MEDLINE | ID: mdl-36308990
ABSTRACT

OBJECTIVE:

Avoidable case cancellations within 24 h reduce operating room (OR) efficiency, add unnecessary costs, and may have physical and emotional consequences for patients and their families. We developed and validated a prediction tool that can be used to guide same day case cancellation reduction initiatives.

DESIGN:

Retrospective hospital registry study.

SETTING:

University-affiliated hospitals network (NY, USA). PATIENTS 246,612 (1/2016-6/2021) and 58,662 (7/2021-6/2022) scheduled elective procedures were included in the development and validation cohort. MEASUREMENTS Case cancellation within 24 h was defined as cancelling a surgical procedure within 24 h of the scheduled date and time. Our candidate predictors were defined a priori and included patient-, procedural-, and appointment-related factors. We created a prediction tool using backward stepwise logistic regression to predict case cancellation within 24 h. The model was subsequently recalibrated and validated in a cohort of patients who were recently scheduled for surgery. MAIN

RESULTS:

8.6% and 8.7% scheduled procedures were cancelled within 24 h of the intended procedure in the development and validation cohort, respectively. The final weighted score contains 29 predictors. A cutoff value of 15 score points predicted a 10.3% case cancellation rate with a negative predictive value of 0.96, and a positive predictive value of 0.21. The prediction model showed good discrimination in the development and validation cohort with an area under the receiver operating characteristic curve (AUC) of 0.79 (95% confidence interval 0.79-0. 80) and an AUC of 0.73 (95% confidence interval 0.72-0.73), respectively.

CONCLUSIONS:

We present a validated preoperative prediction tool for case cancellation within 24 h of surgery. We utilize the instrument in our institution to identify patients with high risk of case cancellation. We describe a process for recalibration such that other institutions can also use the score to guide same day case cancellation reduction initiatives.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Agendamento de Consultas / Procedimentos Cirúrgicos Eletivos Tipo de estudo: Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Clin Anesth Assunto da revista: ANESTESIOLOGIA Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Agendamento de Consultas / Procedimentos Cirúrgicos Eletivos Tipo de estudo: Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Clin Anesth Assunto da revista: ANESTESIOLOGIA Ano de publicação: 2022 Tipo de documento: Article