Log in | Register

Measuring efficiency in Australian and New Zealand paediatric intensive care units

Lahn D. Straney| Archie Clements| Jan Alexander| Anthony Slater
Pediatric Original
Volume 36, Issue 8 / August , 2010

Pages 1410 - 1416

Abstract

Purpose

To develop a measure of paediatric intensive care unit (PICU) efficiency and compare the efficiency of PICUs in Australia and New Zealand.

Methods

Separate outcome prediction models for estimating clinical performance and resource usage were constructed using patient data from 20,742 admissions between 2005 and 2007. A standardised mortality ratio was calculated using a recalibrated Paediatric Index of Mortality 2 model. A random effects length of stay (LoS) prediction model was used to provide an indicator of unit-level variation in resource use. A modified Rapoport-Teres plot of risk-adjusted mortality versus unit mean LoS provided a visual representation of efficiency. To account for potential differences in admission threshold, the calculation of performance measures was repeated on patients receiving mechanical respiratory support and compared to those estimated for all patients.

Results

The modified plot provides a useful tool for visualising ICU efficiency. Two units were identified as potentially inefficient with higher SMR and risk-adjusted mean LoS at the 95% level. One unit had a significantly lower SMR and significantly higher risk-adjusted mean LoS. The measures for both SMR and risk-adjusted mean LoS showed good agreement between all patients and those who received mechanical respiratory support.

Conclusion

There is significant variation in efficiency among PICUs in Australia and New Zealand. Two units were designated as inefficient and one unit was considered to be effective at the expense of high resource use. Application of these methods may help to identify inefficiencies in units located in other countries or regions.

Keywords

References

  1. Hartwig J (2008) What drives health care expenditure?–Baumol’s model of ‘unbalanced growth’ revisited. J Health Econ 27:603–623
    • View reference on publisher's website
    • View reference on PubMed
  2. Institute of Medicine (IOM) (2006) Performance measurement: accelerating improvement. National Academy Press, Washington DC
  3. Kirton OC, Civetta JM, Hudson-Civetta J (1996) Cost effectiveness in the intensive care unit. Surg Clin N Am 76:175–200
    • View reference on publisher's website
    • View reference on PubMed
  4. Rotondi AJ, Sirio CA, Angus DC, Pinsky MR (2002) A new conceptual framework for ICU performance appraisal and improvement. J Crit Care 17:16–28
    • View reference on publisher's website
    • View reference on PubMed
  5. Ward NS, Levy MM (2007) Rationing and critical care medicine. Crit Care Med 35:S102–105
    • View reference on publisher's website
    • View reference on PubMed
  6. Rapoport J, Teres D, Zhao Y, Lemeshow S (2003) Length of stay data as a guide to hospital economic performance for ICU patients. Med Care 41:386–397
    • View reference on publisher's website
    • View reference on PubMed
  7. Rothen HU, Stricker K, Einfalt J, Bauer P, Metnitz PG, Moreno RP, Takala J (2007) Variability in outcome and resource use in intensive care units. Intensive Care Med 33:1329–1336
  8. Zimmerman JE, Kramer AA, McNair DS, Malila FM, Shaffer VL (2006) Intensive care unit length of stay: benchmarking based on acute physiology and chronic health evaluation (APACHE) IV. Crit Care Med 34:2517–2529
    • View reference on publisher's website
    • View reference on PubMed
  9. Jimenez R, Lopez L, Dominguez D, Farinas H (1999) Difference between observed and predicted length of stay as an indicator of inpatient care inefficiency. J Int Soc Qual Health Care 11:375–384
    • View reference on publisher's website
  10. Straney LD, Clements AC, Slater A, Alexander J (2009) Quantifying variation of paediatric length of stay among intensive care units in Australia and New Zealand. Qual Saf Health Care 19:341–348
  11. Rapoport J, Teres D, Lemeshow S, Gehlbach S (1994) A method for assessing the clinical performance and cost-effectiveness of intensive care units: a multicenter inception cohort study. Crit Care Med 22:1385–1391
    • View reference on publisher's website
    • View reference on PubMed
  12. Rothen HU, Takala J (2008) Can outcome prediction data change patient outcomes and organizational outcomes? Curr Opin Crit Care 14:513–519
    • View reference on publisher's website
    • View reference on PubMed
  13. Domínguez L, Enríquez P, Alvarez P, de Frutos M, Sagredo V, Domínguez A, Collado J, Taboada F, García-Labattut A, Bobillo F, Valledor M, Blanco J (2008) Mortality and hospital stay adjusted for severity as indicators of effectiveness and efficiency of attention to intensive care unit patients. Med Intensiva 32:8–14
    • View reference on publisher's website
    • View reference on PubMed
  14. Nathanson BH, Higgins TL, Teres D, Copes WS, Kramer A, Stark M (2007) A revised method to assess intensive care unit clinical performance and resource utilization. Crit Care Med 35:1853–1862
    • View reference on publisher's website
    • View reference on PubMed
  15. Ruttimann UE, Patel KM, Pollack MM (2000) Relevance of diagnostic diversity and patient volumes for quality and length of stay in paediatric intensive care units. Paediatr Crit Care Med 1:133–139
    • View reference on publisher's website
  16. Ruttimann UE, Patel KM, Pollack MM (1998) Length of stay and efficiency in paediatric intensive care units. J Paediatr 133:79–85
    • View reference on publisher's website
  17. Pollack MM, Getson PR, Ruttimann UE, Steinhart CM, Kanter RK, Katz RW, Zucker AR, Glass NL, Spohn WA, Fuhrman BP et al (1987) Efficiency of intensive care: a comparative analysis of eight paediatric intensive care units. JAMA 258:1481–1486
    • View reference on publisher's website
    • View reference on PubMed
  18. Slater A, Shann F, Pearson G (2003) PIM2: a revised version of the paediatric index of mortality. Intensive Care Med 29:278–285
    • View reference on PubMed
  19. Hosmer DW, Hosmer T, Le Cessie S, Lemeshow S (1997) A comparison of goodness-of-fit tests for the logistic regression model. Stat Med 16:965–980
    • View reference on publisher's website
    • View reference on PubMed
  20. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307–310
    • View reference on PubMed
  21. Lee AH, Wang K, Yau KK, McLachlan GJ, Ng SK (2007) Maternity length of stay modelling by gamma mixture regression with random effects. Biom J 49:750–764
    • View reference on publisher's website
    • View reference on PubMed
  22. Mann HB, Whitney DR (1947) On a test of whether one of two random variables is stochastically larger than the other. Ann Math Stat 18:50–60
    • View reference on publisher's website
  23. Tu JV, Mazer CD (1996) Can clinicians predict ICU length of stay following cardiac surgery? Can J Anesth 43:789–794
    • View reference on publisher's website
    • View reference on PubMed
  24. Mittlbock M, Heinzl H (2002) Measures of explained variation in gamma regression models. Commun Stat Simul Comput 31:61–73
    • View reference on publisher's website

Sign In

Connect with ICM

Top 5 Articles Editors Picks Supplement