Publication

Statistical process control for monitoring standardized mortality ratios of a classification tree model

Minne, L., Eslami, S., de Keizer, N., De Jonge, E., de Rooij, S. E. & Abu-Hanna, A., 2012, In : Methods of information in medicine. 51, 4, p. 353-358 6 p.

Research output: Contribution to journalArticleAcademicpeer-review

  • Lilian Minne
  • S Eslami
  • N de Keizer
  • E De Jonge
  • S E de Rooij
  • A Abu-Hanna

OBJECTIVES: The ratio of observed to expected mortality (standardized mortality ratio, SMR), is a key indicator of quality of care. We use PreControl Charts to investigate SMR behavior over time of an existing tree-model for predicting mortality in intensive care units (ICUs) and its implications for hospital ranking. We compare the results to those of a logistic regression model.

METHODS: We calculated SMRs of 30 equally-sized consecutive subsets from a total of 12,143 ICU patients aged 80 years or older and plotted them on a PreControl Chart. We calculated individual hospital SMRs in 2009, with and without repeated recalibration of the models on earlier data.

RESULTS: The overall SMR of the tree-model was stable over time, in contrast to logistic regression. Both models were stable after repeated recalibration. The overall SMR of the tree on the whole validation set was statistically significantly different (SMR 1.00 ± 0.012 vs. 0.94 ± 0.01) and worse in performance than the logistic regression model (AUC 0.76 ± 0.005 vs. 0.79 ± 0.004; Brier score 0.17 ± 0.012 vs. 0.16 ± 0.010). The individual SMRs' range in 2009 was 0.53-1.31 for the tree and 0.64-1.27 for logistic regression. The proportion of individual hospitals with SMR >1, hinting at poor quality of care, reduced from 38% to 29% after recalibration for the tree, and increased from 15% to 35% for logistic regression.

CONCLUSIONS: Although the tree-model has seemingly a longer shelf life than the logistic regression model, its SMR may be less useful for quality of care assessment as it insufficiently responds to changes in the population over time.

Original languageEnglish
Pages (from-to)353-358
Number of pages6
JournalMethods of information in medicine
Volume51
Issue number4
Publication statusPublished - 2012
Externally publishedYes

    Keywords

  • Aged, 80 and over, Algorithms, Decision Trees, Female, Hospital Mortality, Humans, Intensive Care Units, Logistic Models, Male, Models, Statistical, Models, Theoretical, Netherlands, Prognosis, Prospective Studies, ROC Curve, Severity of Illness Index, Time Factors, Journal Article

ID: 34346098