Abstract

BackgroundControversy 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.MethodsA 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.ResultsThe 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 (analysis-of-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.ConclusionsGlobal indices reflecting process of care may be formally established at the level of national patient data-bases. These indices appear orthogonal to mortality outcome.

Highlights

  • Controversy has attended the relationship between risk-adjusted mortality and process-of-care

  • The 1986 paper by Knaus et al [3], evaluating outcomes of a cohort of 13 intensive care units (ICU), established the notion of institutional or provider performance within the critical care discipline by way of the nexus between risk-adjusted mortality and processof-care, the latter established through questionnaire, onsite visit and case-note review

  • The data set consisted of 223129 patients from 99 ICUs over an 11 year period

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Summary

Introduction

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. Individual patient ability to maximize output [19], in this case length of stay, for a given set of physiological inputs, the individual patient component variables of the Acute Physiology and Chronic Health Evaluation (APACHE) III severity of illness algorithm [20]. This ability was conceptualised as one of technical production efficiency We determined the degree of correlation, or independence (orthogonality), between these global processof-care indices and mortality

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