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01-11-2005 | Editorial

Using risk adjustment systems in the ICU: avoid scoring an “own goal”

Authors: Kees H. Polderman, Philipp G. H. Metnitz

Published in: Intensive Care Medicine | Issue 11/2005

Excerpt

Practicing intensive care medicine is associated with major costs, which are increasing at a steady rate due to the expanding use of expensive medical technologies and the increase in average age and number of comorbidities of critically ill patients admitted to the ICU. Depending on ICU size and level of care between 10% and 30% of a hospital budget is currently used for the care of critically ill patients; this adds up to 0.5–1% of a country’s gross domestic product. These developments have led to an increasing interest for cost-effectiveness issues, benchmarking and quality of care in the ICU. …

Pronovost PJ, Angus DC, Dorman T, Robinson KA, Dremsizov TT, Young TL (2002) Physician staffing patterns and clinical outcomes in critically ill patients: a systematic review. JAMA 288:2151–2162CrossRefPubMed

Tarnow-Mordi WO, Hau C, Warden A, Shearer AJ (2000) Hospital mortality in relation to staff workload: a 4-year study in an adult intensive-care unit. Lancet 356:185–189CrossRefPubMed

Iapichino G, Gattinoni L, Radrizzani D, Simini B, Bertolini G, Ferla L, Mistraletti G, Porta F, Miranda DR (2004) Volume of activity and occupancy rate in intensive care units. Association with mortality. Intensive Care Med 30:290–297CrossRefPubMed

Tibby SM, Correa-West J, Durward A, Ferguson L, Murdoch IA (2004) Adverse events in a paediatric intensive care unit: relationship to workload, skill mix and staff supervision. Intensive Care Med 30:1160–1166CrossRefPubMed

Tucker J, UK Neonatal Staffing Study Group (2002) Patient volume, staffing, and workload in relation to risk-adjusted outcomes in a random stratified sample of UK neonatal intensive care units: a prospective evaluation. Lancet 359:99–107CrossRefPubMed

Glance LG, Osler TM, Dick A (2002) Rating the quality of intensive care units: is it a function of the intensive care unit scoring system? Crit Care Med 30:1976–1982CrossRefPubMed

Afessa B, Keegan MT, Gajic O, Hubmayr RD, Peters SG (2005) The influence of missing components of the Acute Physiology Score of APACHE III on the measurement of ICU performance. Intensive Care Med 31 (DOI: 10.1007/s00134-005-2751-9)

Metnitz PG, Vesely H, Valentin A, Popow C, Hiesmayr M, Lenz K, Krenn CG, Steltzer H (1999) Evaluation of an interdisciplinary data set for national intensive care unit assessment. Crit Care Med 27:1486–1491CrossRefPubMed

Engel JM, Junger A, Bottger S, Benson M, Michel A, Rohrig R, Jost A, Hempelmann G (2003) Outcome prediction in a surgical ICU using automatically calculated SAPS II scores. Anaesth Intensive Care 31:548–554PubMed

10.

Perez A, Dennis RJ, Gil JF, Rondon MA, Lopez A (2002) Use of the mean, hot deck and multiple imputation techniques to predict outcome in intensive care unit patients in Colombia. Stat Med 21:3885–3896CrossRefPubMed

11.

Polderman KH, Girbes ARJ, Thijs LG, Strack van Schijndel RJM (2001) Accuracy and reliability of Apache II scoring in two Intensive Care units. Problems and pitfalls in the use of APACHE II and suggestions for improvement. Anaesthesia 56:47–50CrossRefPubMed

12.

Polderman KH, Girbes ARJ, Thijs LG (1999) Inter-observer variation in assessing severity of illness using the APACHE-II scoring system (research letter). Lancet 353:380CrossRef

13.

Chen LM, Martin CM, Morrison TL, Sibbald WJ (1999) Interobserver variability in data collection of the APACHE II score in teaching and community hospitals. Crit Care Med 27:1999–2004CrossRefPubMed

14.

Polderman KH, Christiaans, HMT, Wester JP, Spijkstra JJ, Girbes ARJ (2001) Intra-observer variability in APACHE II scoring. Intensive Care Med 27:1550–1552CrossRefPubMed

15.

Polderman KH, Jorna EMF, Girbes ARJ (2001) Inter-observer variability in APACHE II scoring: Effect of strict guidelines and training. Intensive Care Med 27:1365–1369CrossRefPubMed

16.

Van Keulen JG, Gemke RJB, Polderman KH (2005) Effect of strict guidelines and training on inter-observer variability in PIM and PRISM severity scores. Intensive Care Med 31:1432–1238

17.

Rosenberg AL, Hofer TP, Strachan C, Watts CM, Hayward RA (2003) Accepting Critically Ill Transfer Patients: Adverse Effect on a Referral Center’s Outcome and Benchmark Measures. Ann Intern Med 138:882–890PubMed

18.

Van Zanten AR, Polderman KH (2004) Organizational changes in a single intensive care unit affect benchmarking. Ann Intern Med 140:674–675PubMed

Title: Using risk adjustment systems in the ICU: avoid scoring an “own goal”
Authors: Kees H. Polderman
Philipp G. H. Metnitz
Publication date: 01-11-2005
Publisher: Springer-Verlag
Published in: Intensive Care Medicine / Issue 11/2005
Print ISSN: 0342-4642
Electronic ISSN: 1432-1238
DOI: https://doi.org/10.1007/s00134-005-2750-x

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Using risk adjustment systems in the ICU: avoid scoring an “own goal”

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