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Type: Journal article
Title: Global quantitative indices reflecting provider process-of-care: data-base derivation
Author: Moran, J.
Solomon, P.
Citation: BMC Medical Research Methodology, 2010; 10(1):32-1-32-14
Publisher: BioMed Central Ltd.
Issue Date: 2010
ISSN: 1471-2288
Statement of
John L Moran, Patricia J Solomon and the Adult Database Management Committee (ADMC) of the Australian and New Zealand Intensive Care Society (ANZICS)
Abstract: Background: Controversy has attended the relationship between risk-adjusted mortality and process-of-care. There would be advantage in the establishment, at the data-base level, of global quantitative indices subsuming the diversity of process-of-care. Methods: A retrospective, cohort study of patients identified in the Australian and New Zealand Intensive Care Society Adult Patient Database, 1993-2003, at the level of geographic and ICU-level descriptors (n = 35), for both hospital survivors and non-survivors. Process-of-care indices were established by analysis of: (i) the smoothed time-hazard curve of individual patient discharge and determined by pharmaco-kinetic methods as area under the hazard-curve (AUC), reflecting the integrated experience of the discharge process, and time-to-peak-hazard (TMAX, in days), reflecting the time to maximum rate of hospital discharge; and (ii) individual patient ability to optimize output (as length-of-stay) for recorded data-base physiological inputs; estimated as a technical production-efficiency (TE, scaled [0,(maximum)1]), via the econometric technique of stochastic frontier analysis. For each descriptor, multivariate correlation-relationships between indices and summed mortality probability were determined. Results: The data-set consisted of 223129 patients from 99 ICUs with mean (SD) age and APACHE III score of 59.2(18.9) years and 52.7(30.6) respectively; 41.7% were female and 45.7% were mechanically ventilated within the first 24 hours post-admission. For survivors, AUC was maximal in rural and for-profit ICUs, whereas TMAX (≥ 7.8 days) and TE (≥ 0.74) were maximal in tertiary-ICUs. For non-survivors, AUC was maximal in tertiary-ICUs, but TMAX (≥ 4.2 days) and TE (≥ 0.69) were maximal in for-profit ICUs. Across descriptors, significant differences in indices were demonstrated (analysisof- variance, P ≤ 0.0001). Total explained variance, for survivors (0.89) and non-survivors (0.89), was maximized by combinations of indices demonstrating a low correlation with mortality probability. Conclusions: Global indices reflecting process of care may be formally established at the level of national patient databases. These indices appear orthogonal to mortality outcome.
Keywords: Adult Database Management Committee (ADMC) of the Australian and New Zealand Intensive Care Society (ANZICS)
Length of Stay
Hospital Mortality
Analysis of Variance
Logistic Models
Models, Econometric
Retrospective Studies
Cohort Studies
Databases, Factual
Aged, 80 and over
Middle Aged
Intensive Care Units
New Zealand
Evaluation Studies as Topic
Process Assessment, Health Care
Rights: © 2010 Moran et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI: 10.1186/1471-2288-10-32
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Mathematical Sciences publications

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