title: Global quantitative indices reflecting provider process-of-care: data-base derivation.
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 (>or= 7.8 days) and TE (>or= 0.74) were maximal in tertiary-ICUs. For non-survivors, AUC was maximal in tertiary-ICUs, but TMAX (>or= 4.2 days) and TE (>or= 0.69) were maximal in for-profit ICUs. Across descriptors, significant differences in indices were demonstrated (analysis-of-variance, P <or= 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 data-bases. These indices appear orthogonal to mortality outcome.
authors.affiliation: Department of Intensive Care Medicine, The Queen Elizabeth Hospital, Woodville SA 5011, Australia. john.moran@adelaide.edu.au
authors.forename: John L
authors.initials: JL
authors.lastname: Moran
authors.forename: Patricia J
authors.initials: PJ
authors.lastname: Solomon
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D001315:Australia; D015331:Cohort Studies; D016208:Databases, Factual; D005069:Evaluation Studies as Topic; D005260:Female; D017052:Hospital Mortality; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007362:Intensive Care Units / Q000191:economics / Q000592:standards* / Q000706:statistics & numerical data; D007902:Length of Stay / Q000706:statistics & numerical data; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D017059:Models, Econometric; D009520:New Zealand; D011336:Probability; D017064:Process Assessment, Health Care / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D017741:Survivors / Q000706:statistics & numerical data
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