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Simplified risk prediction indices do not accurately predict 30-day death or readmission after discharge following colorectal surgery.
Brauer, David G; Lyons, Sarah A; Keller, Matthew R; Mutch, Matthew G; Colditz, Graham A; Glasgow, Sean C.
Afiliación
  • Brauer DG; Department of Surgery, Washington University School of Medicine, St. Louis, MO.
  • Lyons SA; Department of Surgery, Washington University School of Medicine, St. Louis, MO.
  • Keller MR; Department of Medicine, Washington University School of Medicine.
  • Mutch MG; Department of Surgery, Washington University School of Medicine, St. Louis, MO.
  • Colditz GA; Department of Surgery, Washington University School of Medicine, St. Louis, MO.
  • Glasgow SC; Department of Surgery, Washington University School of Medicine, St. Louis, MO; John Cochran Veteran's Administration Medical Center, St. Louis, MO. Electronic address: glasgows@wustl.edu.
Surgery ; 165(5): 882-888, 2019 05.
Article en En | MEDLINE | ID: mdl-30709587
ABSTRACT

BACKGROUND:

Risk-prediction indices are one category of the many tools implemented to guide efforts to decrease readmissions. However, using fied models to predict a complex process can prove challenging. In addition, no risk-prediction index has been developed for patients undergoing colorectal surgery. Therefore, we evaluated the performance of a widely utilized simplified index developed at the hospital level - LACE (length of stay, acute admission, Charlson comorbidity index score, and emergency department visits) and developed and evaluated a novel index in predicting readmissions in this patient population.

METHODS:

Using a retrospective split-sample cohort, patients discharged after colorectal surgery were identified within the inpatient databases of the Healthcare Cost and Utilization Project for the states of New York, California, and Florida (2006-2014). The primary outcome was death or readmission within 30 days after discharge. Multivariable logistic regression models incorporated patient comorbidities, postoperative complications, and hospitalization details, and were evaluated using the C statistic.

RESULTS:

A total of 440,742 patients met eligibility criteria. The rate of death or readmission within 30 days after discharge was 14.0% (n = 61,757). When applied to surgical patients, the LACE index demonstrated a poor model fit (C = 0.631). The model fit improved significantly-but remained poor (C = 0.654; P < .001)-with the addition of the following variables, which are known to be associated with readmission after colorectal surgery age, indication for surgery, and creation of a new ostomy. A novel, simplified model also yielded a poor model fit (C = 0.660).

CONCLUSION:

Postdischarge death or readmission after colorectal surgery is not accurately modeled using existing, modified, or novel simplified risk prediction models. Payers and providers must ensure that quality improvement efforts applying simplified models to complex processes, such as readmissions following colorectal surgery, may not be appropriate, and that models reflect the relevant patient population.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Complicaciones Posoperatorias / Enfermedades del Recto / Procedimientos Quirúrgicos del Sistema Digestivo / Enfermedades del Colon Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male / Middle aged País/Región como asunto: America do norte Idioma: En Revista: Surgery Año: 2019 Tipo del documento: Article País de afiliación: Macao

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Complicaciones Posoperatorias / Enfermedades del Recto / Procedimientos Quirúrgicos del Sistema Digestivo / Enfermedades del Colon Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male / Middle aged País/Región como asunto: America do norte Idioma: En Revista: Surgery Año: 2019 Tipo del documento: Article País de afiliación: Macao