Literature DB >> 8099649

Physiological scoring systems and audit.

O Boyd1, R M Grounds.   

Abstract

Scoring systems designed to rate the severity of an illness are being used for comparison of hospital units to identify different standards of care and to allocate resources. One such scoring system is the Acute Physiology and Chronic Health Evaluation (APACHE) system which is designed to assess the severity of illness of patients in intensive care units (ICUs). It is widely assumed that different ICUs can be compared by the ratio of actual mortality to that predicted by the APACHE score. However, we suggest that the use of physiological data that can be influenced by medical and nursing intervention should not be used for audit. For example, by good care a patient may be made less severely ill and, therefore, may have a lower actual mortality while, at the same time, accumulating only a low APACHE score with low predicted mortality. This patient could have, therefore, the same mortality ratio as a patient treated inappropriately, who may have a higher actual mortality and a high APACHE score with greater predicted mortality. Paradoxically, the very accuracy of these scoring systems for assessing the severity of illness precludes their use for comparison and audit.

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Year:  1993        PMID: 8099649     DOI: 10.1016/0140-6736(93)90706-m

Source DB:  PubMed          Journal:  Lancet        ISSN: 0140-6736            Impact factor:   79.321


  10 in total

1.  'End-of-life' decision making within intensive care--objective, consistent, defensible?

Authors:  A J Ravenscroft; M D Bell
Journal:  J Med Ethics       Date:  2000-12       Impact factor: 2.903

2.  The importance of technology for achieving superior outcomes from intensive care. Brazil APACHE III Study Group.

Authors:  P G Bastos; W A Knaus; J E Zimmerman; A Magalhães; X Sun; D P Wagner
Journal:  Intensive Care Med       Date:  1996-07       Impact factor: 17.440

3.  Confidential inquiry into quality of care before admission to intensive care.

Authors:  P McQuillan; S Pilkington; A Allan; B Taylor; A Short; G Morgan; M Nielsen; D Barrett; G Smith; C H Collins
Journal:  BMJ       Date:  1998-06-20

4.  Artificial neural network for risk assessment in preterm neonates.

Authors:  B Zernikow; K Holtmannspoetter; E Michel; W Pielemeier; F Hornschuh; A Westermann; K H Hennecke
Journal:  Arch Dis Child Fetal Neonatal Ed       Date:  1998-09       Impact factor: 5.747

Review 5.  Predicting outcome in ICU patients. 2nd European Consensus Conference in Intensive Care Medicine.

Authors: 
Journal:  Intensive Care Med       Date:  1994-05       Impact factor: 17.440

6.  Surgical mortality score: risk management tool for auditing surgical performance.

Authors:  Vassilis G Hadjianastassiou; Paris P Tekkis; Jan D Poloniecki; Manolis C Gavalas; David R Goldhill
Journal:  World J Surg       Date:  2004-01-08       Impact factor: 3.352

7.  Winter excess mortality in intensive care in the UK: an analysis of outcome adjusted for patient case mix and unit workload.

Authors:  David A Harrison; Panuwat Lertsithichai; Anthony R Brady; James R Carpenter; Kathy Rowan
Journal:  Intensive Care Med       Date:  2004-08-06       Impact factor: 17.440

8.  A comparison of admission and worst 24-hour Acute Physiology and Chronic Health Evaluation II scores in predicting hospital mortality: a retrospective cohort study.

Authors:  Kwok M Ho; Geoffrey J Dobb; Matthew Knuiman; Judith Finn; Kok Y Lee; Steven A R Webb
Journal:  Crit Care       Date:  2006-02       Impact factor: 9.097

9.  Design and Performance of a New Severity Score for Intermediate Care.

Authors:  Félix Alegre; Manuel Fortún Landecho; Ana Huerta; Nerea Fernández-Ros; Diego Martínez-Urbistondo; Nicolás García; Jorge Quiroga; Juan Felipe Lucena
Journal:  PLoS One       Date:  2015-06-29       Impact factor: 3.240

10.  Case mix, outcome and length of stay for admissions to adult, general critical care units in England, Wales and Northern Ireland: the Intensive Care National Audit & Research Centre Case Mix Programme Database.

Authors:  David A Harrison; Anthony R Brady; Kathy Rowan
Journal:  Crit Care       Date:  2004-02-26       Impact factor: 9.097

  10 in total

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