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

IntroductionThe present paper describes the methods of data collection and validation employed in the Intensive Care National Audit & Research Centre Case Mix Programme (CMP), a national comparative audit of outcome for adult, critical care admissions. The paper also describes the case mix, outcome and activity of the admissions in the Case Mix Programme Database (CMPD).MethodsThe CMP collects data on consecutive admissions to adult, general critical care units in England, Wales and Northern Ireland. Explicit steps are taken to ensure the accuracy of the data, including use of a dataset specification, of initial and refresher training courses, and of local and central validation of submitted data for incomplete, illogical and inconsistent values. Criteria for evaluating clinical databases developed by the Directory of Clinical Databases were applied to the CMPD. The case mix, outcome and activity for all admissions were briefly summarised.ResultsThe mean quality level achieved by the CMPD for the 10 Directory of Clinical Databases criteria was 3.4 (on a scale of 1 = worst to 4 = best). The CMPD contained validated data on 129,647 admissions to 128 units. The median age was 63 years, and 59% were male. The mean Acute Physiology and Chronic Health Evaluation II score was 16.5. Mortality was 20.3% in the CMP unit and was 30.8% at ultimate discharge from hospital. Nonsurvivors stayed longer in intensive care than did survivors (median 2.0 days versus 1.7 days in the CMP unit) but had a shorter total hospital length of stay (9 days versus 16 days). Results for the CMPD were comparable with results from other published reports of UK critical care admissions.ConclusionsThe CMP uses rigorous methods to ensure data are complete, valid and reliable. The CMP scores well against published criteria for high-quality clinical databases.

[1]  S. Lemeshow,et al.  Mortality Probability Models (MPM II) based on an international cohort of intensive care unit patients. , 1993, JAMA.

[2]  N. Black High-quality clinical databases: breaking down barriers , 1999, The Lancet.

[3]  Turner M. Osler,et al.  Mukamel Using hierarchical modeling to measure ICU quality , 2003 .

[4]  S. Lemeshow,et al.  A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study , 1993 .

[5]  I. Deary,et al.  Consent for transfusion , 1997, BMJ.

[6]  N F de Keizer,et al.  [Intensive care medicine in the Netherlands, 1997-2001. I. Patient population and treatment outcome]. , 2003, Nederlands tijdschrift voor geneeskunde.

[7]  W. Knaus The APACHE III Prognostic System , 1992 .

[8]  C. Goldfrad,et al.  Consequences of discharges from intensive care at night , 2000, The Lancet.

[9]  D. Goldhill,et al.  Outcome of intensive care patients in a group of British intensive care units. , 1998, Critical care medicine.

[10]  Gary B. Smith,et al.  External validation of the SAPS II, APACHE II and APACHE III prognostic models in South England: a multicentre study , 2003, Intensive Care Medicine.

[11]  H. Wunsch,et al.  Hospital mortality associated with day and time of admission to intensive care units , 2004, Intensive Care Medicine.

[12]  W J Sibbald,et al.  Interobserver variability in data collection of the APACHE II score in teaching and community hospitals. , 1999, Critical care medicine.

[13]  J H Kerr,et al.  Intensive Care Society's APACHE II study in Britain and Ireland--II: Outcome comparisons of intensive care units after adjustment for case mix by the American APACHE II method. , 1993, BMJ.

[14]  E. Draper,et al.  APACHE II: A severity of disease classification system , 1985, Critical care medicine.

[15]  N. Black,et al.  Directory of clinical databases: improving and promoting their use , 2003, Quality & safety in health care.

[16]  S. Lemeshow,et al.  A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study. , 1993, JAMA.

[17]  P. Metnitz,et al.  Gender-related differences in intensive care: A multiple-center cohort study of therapeutic interventions and outcome in critically ill patients* , 2003, Critical care medicine.

[18]  H. Wunsch,et al.  Impact of exclusion criteria on case mix, outcome, and length of stay for the severity of disease scoring methods in common use in critical care. , 2004, Journal of critical care.

[19]  J H Kerr,et al.  Intensive Care Society's APACHE II study in Britain and Ireland--I: Variations in case mix of adult admissions to general intensive care units and impact on outcome. , 1993, BMJ.

[20]  R. Moreno,et al.  Outcome prediction in intensive care: results of a prospective, multicentre, Portuguese study , 1997, Intensive Care Medicine.

[21]  C. Goldfrad,et al.  Influence of patient gender on admission to intensive care , 2002, Journal of epidemiology and community health.

[22]  P. Landais,et al.  Evaluation of severity scoring systems in ICUs—translation, conversion and definition ambiguities as a source of inter-observer variability in Apache II, SAPS and OSF , 1995, Intensive Care Medicine.

[23]  K. Polderman,et al.  Inter-observer variability in APACHE II scoring: effect of strict guidelines and training , 2001, Intensive Care Medicine.

[24]  Nicolette F de Keizer,et al.  Training in data definitions improves quality of intensive care data , 2003, Critical care.

[25]  J. Norrie,et al.  Assessment of the performance of five intensive care scoring models within a large Scottish database , 2000, Critical care medicine.

[26]  G. Apolone,et al.  Evaluation of the uniformity of fit of general outcome prediction models , 1998, Intensive Care Medicine.

[27]  van Zanten Ar,et al.  [Intensive care medicine in the Netherlands, 1997-2001]. , 2003 .

[28]  C. Sirio,et al.  A cross-cultural comparison of critical care delivery: Japan and the United States. , 2002, Chest.

[29]  W. Knaus,et al.  Application of the APACHE III prognostic system in Brazilian intensive care units: A prospective multicenter study , 1996, Intensive Care Medicine.

[30]  H. Wunsch,et al.  End-of-life decisions: a cohort study of the withdrawal of all active treatment in intensive care units in the United Kingdom , 2005, Intensive Care Medicine.

[31]  J. Bion,et al.  A comparison of severity of illness scoring systems for intensive care unit patients: results of a multicenter, multinational study. The European/North American Severity Study Group. , 1995, Critical care medicine.

[32]  Duncan Young,et al.  Epidemiology of severe sepsis occurring in the first 24 hrs in intensive care units in England, Wales, and Northern Ireland , 2003, Critical care medicine.

[33]  Rachel Elliott,et al.  Case study eight: outcome comparisions of intensive care units in Great Britain and Ireland using the APACHE II method. , 1996 .

[34]  J. D. Young,et al.  Development and testing of a hierarchical method to code the reason for admission to intensive care units: the ICNARC Coding Method , 2001 .

[35]  W. Knaus,et al.  The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. , 1991, Chest.

[36]  S. Cook,et al.  Project IMPACT: Results from a Pilot Validity Study of a New Observational Database , 2002, Critical care medicine.

[37]  Zoë Kavadas Intensive Care National Audit & Research Centre (ICNARC) , 2004 .

[38]  K. Rowan Intensive Care Society has set up a centre for national audit , 1996, BMJ.

[39]  G. Bonsel,et al.  The added value that increasing levels of diagnostic information provide in prognostic models to estimate hospital mortality for adult intensive care patients , 2000, Intensive Care Medicine.

[40]  O. Boyd,et al.  Physiological scoring systems and audit , 1993, The Lancet.

[41]  G. V. Mata,et al.  Objetivación de la gravedad mediante el sistema APACHE-III aplicado en España , 2001 .