Journal of Critical Care
Volume 25, Issue 2 , Pages 196-204 , June 2010

The effects of critical care outreach services before and after critical care: A matched-cohort analysis

  • David A. Harrison, PhD

      Affiliations

    • Intensive Care National Audit & Research Centre, Tavistock House, Tavistock Square, London WC1H 9HR, UK
    • Corresponding Author InformationCorresponding author. Tel.: +44 20 7388 2856; fax: +44 20 7388 3759.
    • ,
  • Haiyan Gao, PhD

      Affiliations

    • Intensive Care National Audit & Research Centre, Tavistock House, Tavistock Square, London WC1H 9HR, UK
    • Current affiliation: National Institute of Clinical Outcomes Research, University College London, Suite 501, Heart Hospital, Westmoreland Street, London W1G 8PH, UK
    • ,
  • Catherine A. Welch, MSc

      Affiliations

    • Intensive Care National Audit & Research Centre, Tavistock House, Tavistock Square, London WC1H 9HR, UK
    • ,
  • Kathryn M. Rowan, DPhil

      Affiliations

    • Intensive Care National Audit & Research Centre, Tavistock House, Tavistock Square, London WC1H 9HR, UK

References 

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  10. Department of Health and NHS Modernisation Agency . The national outreach report 2003. London: Department of Health; 2003;
  11. Gao H, Harrison DA, Parry GJ, et al. The impact of the introduction of critical care outreach services in England: a multicentre interrupted time-series analysis. Crit Care. 2007;11:R113
  12. Harrison DA, Gao H, Welch CA, Rowan KM. The impact of critical care outreach services on the characteristics and outcomes of admissions to intensive care units: a matched-cohort analysis. Intensive Care Med. 2007;33:S10;(abstr)
  13. Harrison DA, Brady AR, Rowan K. 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. Crit Care. 2004;8:R99–R111
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  15. Young JD, Goldfrad C, Rowan K. Development and testing of a hierarchical method to code the reason for admission to intensive care units: the ICNARC Coding Method. Intensive Care National Audit & Research Centre. Br J Anaesth. 2001;87:543–548
  16. Harrison DA, Parry GJ, Carpenter JR, et al. A new risk prediction model for critical care: the Intensive Care National Audit & Research Centre (ICNARC) model. Crit Care Med. 2007;35:1091–1098
  17. Harrell FE. Relaxing linearity assumption for continuous predictors. In: Regression modeling strategies: with applications to linear models, logistic regression and survival analysis. New York: Springer-Verlag; 2001;p. 16–26
  18. Austin PC, Grootendorst P, Anderson GM. A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study. Stat Med. 2007;26:734–753
  19. Normand ST, Landrum MB, Guadagnoli E, et al. Validating recommendations for coronary angiography following acute myocardial infarction in the elderly: a matched analysis using propensity scores. J Clin Epidemiol. 2001;54:387–398
  20. Cummings P, McKnight B. Analysis of matched cohort data. Stata J. 2004;4:274–281
  21. Dragsted L, Jorgensen J, Jensen NH, et al. Interhospital comparisons of patient outcome from intensive care: importance of lead-time bias. Crit Care Med. 1989;17:418–422
  22. Sacks H, Chalmers TC, Smith H. Randomized versus historical controls for clinical trials. Am J Med. 1982;72:233–240
  23. Green SB, Byar DP. Using observational data from registries to compare treatments: the fallacy of omnimetrics. Stat Med. 1984;3:361–373
  24. National Institute for Health and Clinical Excellence . Acutely ill patients in hospital: recognition of and response to acute illness in adults in hospital. London: NICE; 2007;http://www.nice.org.uk/CG50

☆ All work was carried out at the Intensive Care National Audit & Research Centre, London, United Kingdom.

PII: S0883-9441(10)00119-X

doi: 10.1016/j.jcrc.2009.12.015

Journal of Critical Care
Volume 25, Issue 2 , Pages 196-204 , June 2010

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