Prediction of long-term mortality in ICU patients: Model validation and assessing the effect of using in-hospital versus long-term mortality on benchmarking

Intensive Care Medicine

Volumn 39, Issue 11, 2013, Pages 1925-1931

  Brinkman, Sylvia ^a   Abu Hanna, Ameen ^a   De Jonge, Evert ^b   De Keizer, Nicolette F ^a  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

^b LEIDEN UNIVERSITY MEDICAL CENTER   (Netherlands)

Author keywords

Benchmarking; Critical care; Long term outcome; Mortality; Prognostic models; SMR

Indexed keywords

APACHE; ARTICLE; BOOTSTRAPPING; HEALTH CARE QUALITY; HUMAN; INTENSIVE CARE; INTENSIVE CARE UNIT; MAJOR CLINICAL STUDY; MORTALITY; PREDICTION; QUALITY CONTROL; VALIDATION STUDY;

APACHE; BENCHMARKING; CORONARY ARTERY BYPASS; FEMALE; GLASGOW COMA SCALE; HOSPITAL MORTALITY; HUMANS; INTENSIVE CARE UNITS; LENGTH OF STAY; MALE; MIDDLE AGED; NETHERLANDS; PREDICTIVE VALUE OF TESTS; QUALITY INDICATORS, HEALTH CARE; REGISTRIES;

EID: 84885422821     PISSN: 03424642     EISSN: 14321238     Source Type: Journal    
DOI: 10.1007/s00134-013-3042-5     Document Type: Article

References (22)

1. de Vos M, Graafmans W, Keesman E, Westert G et al (2007) Quality measurement at intensive care units: Which indicators should we use? J Crit Care 22:267-274
2. Sirio CA, Shepardson LB, Rotondi AJ, Cooper GS et al (1999) Community-wide assessment of intensive care outcomes using a physiologically based prognostic measure: Implications for critical care delivery from Cleveland health quality choice. Chest 115:793-801
3. Zimmerman JE, Kramer AA, McNair DS, Malila FM (2006) Acute Physiology and Chronic Health Evaluation (APACHE) IV: Hospital mortality assessment for today's critically ill patients. Crit Care Med 34:1297-1310
4. Brinkman S, de Jonge E, Abu-Hanna A, De Lange DW et al (2012) The use of linked registries to assess long-term mortality of ICU patients. Stud Health Technol Inform 180:230-234
5. Dutch National Intensive Care Evaluation (NICE) foundation (2013). http://www.stichting-nice.nl. Accessed 1 June 2013
6. Vektis (2013). http://www.vektis.nl. Accessed 1 Jan 2013
7. Brinkman S, Bakhshi-Raiez F, Abu-Hanna A, de Jonge E et al (2013) Determinants of mortality after hospital discharge in ICU patients: Literature review and Dutch cohort study. Crit Care Med 41:1237-1251
8. Harrell FE Jr (2001) Regression modeling strategies, with applications to linear models, logistic regression, and survival analysis. Springer, New York
9. Hanley JA, McNeil BJ (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143:29-36
10. Hilden J, Habbema JD, Bjerregaard B (1978) The measurement of performance in probabilistic diagnosis. III. Methods based on continuous functions of the diagnostic probabilities. Methods Inf Med 17:238-246
11. Salter K, Jutai JW, Teasell R, Foley NC et al (2005) Issues for selection of outcome measures in stroke rehabilitation: ICF participation. Disabil Rehabil 27:507-528
12. Biancari F, Vasques F, Mikkola R, Martin M et al (2012) Validation of EuroSCORE II in patients undergoing coronary artery bypass surgery. Ann Thorac Surg 93:1930-1935
13. Efron B (1983) Estimating the error rate of a prediction rule: Improvement on cross-validation. Am Stat Assoc 78:316-331
14. 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
15. Zhu BP, Lemeshow S, Hosmer DW, Klar J et al (1996) Factors affecting the performance of the models in the mortality probability model II system and strategies of customization: A simulation study. Crit Care Med 24:57-63
16. Knaus WA, Harrell FE Jr, Lynn J, Goldman L et al (1995) The SUPPORT prognostic model. Objective estimates of survival for seriously ill hospitalized adults. Study to understand prognoses and preferences for outcomes and risks of treatments. Ann Intern Med 122:191-203
17. Ho KM, Knuiman M, Finn J, Webb SA (2008) Estimating long-term survival of critically ill patients: The PREDICT model. PLoS ONE 3:e3226
18. Brinkman S, Abu-Hanna A, van der Veen A, de Jonge E et al (2012) A comparison of the performance of a model based on administrative data and a model based on clinical data: Effect of severity of illness on standardized mortality ratios of intensive care units. Crit Care Med 40:373-378
19. Bakhshi-Raiez F, Peek N, Bosman RJ, de Jonge E et al (2007) The impact of different prognostic models and their customization on institutional comparison of intensive care units. Crit Care Med 35:2553-2560
20. Lilford R, Pronovost P (2010) Using hospital mortality rates to judge hospital performance: A bad idea that just won't go away. BMJ 340:c2016
21. Brinkman S, Bakhshi-Raiez F, Abu-Hanna A, de Jonge E et al (2011) External validation of acute physiology and chronic health evaluation IV in Dutch intensive care units and comparison with acute physiology and chronic health evaluation II and simplified acute physiology score II. J Crit Care 26:105-108
22. Tromp M, Ravelli AC, Bonsel GJ, Hasman A et al (2011) Results from simulated data sets: Probabilistic record linkage outperforms deterministic record linkage. J Clin Epidemiol 64:565-572