Literature DB >> 2707011

Interhospital comparisons of patient outcome from intensive care: importance of lead-time bias.

L Dragsted1, J Jörgensen, N H Jensen, E Bönsing, E Jacobsen, W A Knaus, J Qvist.   

Abstract

We studied 432 admissions to two Danish ICUs by using a standard severity of illness classification system to assess utilization and outcome. Substantial differences in utilization were found. The patients in Hospital 2 were younger, had better previous health records, and were admitted significantly more often for active treatment as opposed to monitoring than the patients in Hospital 1. Although their measured severity of illness was similar, patients at Hospital 2 received significantly more therapy and their mortality exceeded that of the patients at Hospital 1. The mortality rate of Hospital 2 also exceeded that predicted from a recent survey of U.S. hospitals. We found, however, that 35% of the patients at Hospital 2 had been transferred to the ICU from other ICUs. This created the possibility of an adverse selection and lead-time bias for the patients at Hospital 2. These findings indicate that although national and international comparisons of intensive care are now possible using common classification systems, this progress has created a new need for more precise measurement of potential confounding biases, such as the duration of intensive care services received before formal ICU admission.

Entities:  

Mesh:

Year:  1989        PMID: 2707011     DOI: 10.1097/00003246-198905000-00008

Source DB:  PubMed          Journal:  Crit Care Med        ISSN: 0090-3493            Impact factor:   7.598


  25 in total

1.  Quantitative quality assurance in a community hospital pediatric intensive care unit.

Authors:  B S Frank; M M Pollack
Journal:  West J Med       Date:  1992-08

Review 2.  Predicting outcome in critical care: the current status of the APACHE prognostic scoring system.

Authors:  D T Wong; W A Knaus
Journal:  Can J Anaesth       Date:  1991-04       Impact factor: 5.063

3.  Admissions to intensive care units from emergency departments: a descriptive study.

Authors:  H K Simpson; M Clancy; C Goldfrad; K Rowan
Journal:  Emerg Med J       Date:  2005-06       Impact factor: 2.740

4.  [Chronic critical disease--what does the long-term patient imply for intensive medicine].

Authors:  Jürgen Graf; Uwe Janssens
Journal:  Wien Klin Wochenschr       Date:  2006-07       Impact factor: 1.704

5.  The changing challenges of critical care.

Authors:  W A Knaus
Journal:  Intensive Care Med       Date:  1989       Impact factor: 17.440

6.  Predictive accuracy of medical transport information for in-hospital mortality.

Authors:  Andrew P Reimer; Jarrod E Dalton
Journal:  J Crit Care       Date:  2017-11-15       Impact factor: 3.425

7.  Proxy-perceived prior health status and hospital outcome among the critically ill: is there any relationship?

Authors:  A Diaz-Prieto; M T Gorriz; X Badia; H Torrado; E Farrero; J Amador; R Abos
Journal:  Intensive Care Med       Date:  1998-07       Impact factor: 17.440

8.  Application of the APACHE III prognostic system in Brazilian intensive care units: a prospective multicenter study.

Authors:  P G Bastos; X Sun; D P Wagner; W A Knaus; J E Zimmerman
Journal:  Intensive Care Med       Date:  1996-06       Impact factor: 17.440

9.  Can a clinician predict the technical equipment a patient will need during intensive care unit treatment? An approach to standardize and redesign the intensive care unit workstation.

Authors:  J Hähnel; W Friesdorf; B Schwilk; T Marx; S Blessing
Journal:  J Clin Monit       Date:  1992-01

10.  Rapid response systems.

Authors:  Ken Hillman
Journal:  Indian J Crit Care Med       Date:  2008-04
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.