Cox regression models for intermediate events, with discharge from hospital as an example

Yohanan Wax, Noya Galai, Vincent Carey, Elisheva Simchen

Research output: Contribution to journalArticle

Abstract

In studies of mortality or morbidity of hospitalized patients, discharge from hospital is an intermediate event between hospital experience and disease outcomes, as disease onset may occur after release from hospital. This study explored the role that discharge might have in risk for surgical infections after hernia repair operations, where follow-up continued for 1 month after operation, and 50% of infections occurred at home. Possible direct and interactive effects were evaluated in the presence of two major methodologic difficulties: waiting-time bias, because patients became candidates for home infections only after leaving the hospital, and selective discharge bias, because discharge carried much prognostic information. It was possible, using Cox models, to correct for the waiting-time bias, but the strong protective effect of termination of hospitalization on the risk for infection remained difficult to interpret. The strengths and limitations of various Cox models in dealing with these issues are discussed.

Original languageEnglish (US)
Pages (from-to)120-127
Number of pages8
JournalEpidemiology
Volume4
Issue number2
DOIs
StatePublished - Mar 1993
Externally publishedYes

Keywords

  • Cohort studies
  • Intermediate events
  • Time-dependent covariates

ASJC Scopus subject areas

  • Epidemiology

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