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
StatePublished - 1993
Externally publishedYes

Fingerprint

Proportional Hazards Models
Infection
Patient Discharge
Herniorrhaphy
Hospitalization
Morbidity
Mortality

Keywords

  • Cohort studies
  • Intermediate events
  • Time-dependent covariates

ASJC Scopus subject areas

  • Epidemiology

Cite this

Cox regression models for intermediate events, with discharge from hospital as an example. / Wax, Yohanan; Galai, Noya; Carey, Vincent; Simchen, Elisheva.

In: Epidemiology, Vol. 4, No. 2, 1993, p. 120-127.

Research output: Contribution to journalArticle

Wax, Yohanan ; Galai, Noya ; Carey, Vincent ; Simchen, Elisheva. / Cox regression models for intermediate events, with discharge from hospital as an example. In: Epidemiology. 1993 ; Vol. 4, No. 2. pp. 120-127.
@article{5f8deb6fd883416d9bd56b886f6d673c,
title = "Cox regression models for intermediate events, with discharge from hospital as an example",
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.",
keywords = "Cohort studies, Intermediate events, Time-dependent covariates",
author = "Yohanan Wax and Noya Galai and Vincent Carey and Elisheva Simchen",
year = "1993",
language = "English (US)",
volume = "4",
pages = "120--127",
journal = "Epidemiology",
issn = "1044-3983",
publisher = "Lippincott Williams and Wilkins",
number = "2",

}

TY - JOUR

T1 - Cox regression models for intermediate events, with discharge from hospital as an example

AU - Wax, Yohanan

AU - Galai, Noya

AU - Carey, Vincent

AU - Simchen, Elisheva

PY - 1993

Y1 - 1993

N2 - 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.

AB - 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.

KW - Cohort studies

KW - Intermediate events

KW - Time-dependent covariates

UR - http://www.scopus.com/inward/record.url?scp=0027530215&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0027530215&partnerID=8YFLogxK

M3 - Article

C2 - 8452900

AN - SCOPUS:0027530215

VL - 4

SP - 120

EP - 127

JO - Epidemiology

JF - Epidemiology

SN - 1044-3983

IS - 2

ER -