Triaging patients to the ICU: a pilot study of factors influencing admission decisions and patient outcomes

ObjectiveTo assess the appropriateness of ICU triage decisions.DesignProspective descriptive single-center study.SettingTen-bed, medical-surgical ICU in an acute-care 460-bed, tertiary care hospital.PatientsAll patients triaged for admission were entered prospectively.InterventionsNone.Measurements and main resultsAge, underlying diseases, admission diagnoses, Mortality Probability Model (MPM0) score, information available to ICU physicians, and mortality were recorded. Of the 334 patients (96% medical), 145 (46.4%) were refused. Reasons for refusal were being too-sick-to-benefit (48, 14%) and too-well-to-benefit (93, 28%). Factors independently associated with refusal were patient location, ICU physician seniority, bed availability, patient age, underlying diseases, and disability. Hospital mortality was 23% and 27% for patients admitted to our ICU and other ICUs, respectively, and 7.5% and 60% for patients too well and too sick to benefit, respectively. In the multivariate Cox model, McCabe = 1 [hazard ratio (HR), 0.44 (95% CI, 0.24–0.77), P=0.001], living at home without help (HR, 0.440, 95% CI, 0.28–0.68, P=0.0003), and immunosuppression (HR, 1.91, 95% CI, 1.09–3.33, P=0.02) were independent predictors of hospital death. Neither later ICU admission nor refusal was associated with cohort survival. MPM0 was not associated with hospital mortality.ConclusionsRefusal of ICU admission was related to the ability of the triaging physician to examine the patient, ICU physician seniority, patient age, underlying diseases, self-sufficiency, and number of beds available. Specific training of junior physicians in triaging might bring further improvements. Scores that are more accurate than the MPM0 are needed.

[1]  D. E. Lawrence,et al.  APACHE—acute physiology and chronic health evaluation: a physiologically based classification system , 1981, Critical care medicine.

[2]  T. Noseworthy,et al.  Quality of life measures before and one year after admission to an intensive care unit. , 1995, Critical care medicine.

[3]  J. Hanley,et al.  A method of comparing the areas under receiver operating characteristic curves derived from the same cases. , 1983, Radiology.

[4]  Stanley Lemeshow,et al.  Modeling the Severity of Illness of ICU Patients , 2001 .

[5]  A. Porath,et al.  Rationing critical care -- what happens to patients who are not admitted? , 1994, Theoretical surgery.

[6]  J. le Gall,et al.  Modeling the severity of illness of ICU patients. , 2001, European journal of internal medicine.

[7]  R. Bellomo,et al.  Out of hospital outcome and quality of life in survivors of combined acute multiple organ and renal failure treated with continuous venovenous hemofiltration/hemodiafiltration , 1997, Intensive Care Medicine.

[8]  R. Pearl,et al.  Prediction of poor outcome of intensive care unit patients admitted from the emergency department. , 1997, Critical care medicine.

[9]  P. Levin,et al.  The process of intensive care triage , 2001, Intensive Care Medicine.

[10]  K. Hillman,et al.  Quality of life outcomes after intensive care. Comparison with a community group. , 1997, Intensive care medicine.

[11]  S. Lemeshow,et al.  A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study. , 1993, JAMA.

[12]  S. Keenan,et al.  Intensive care unit admission has minimal impact on long-term mortality. , 2002, Critical care medicine.

[13]  A. Egol Guidelines for intensive care unit admission, discharge, and triage , 1999 .

[14]  K. Hillman,et al.  Quality of life outcomes after intensive care , 1997, Intensive Care Medicine.

[15]  G. Jackson,et al.  Gram-Negative Bacteremia: I. Etiology and Ecology , 1962 .

[16]  A L Brannen,et al.  Prediction of outcome from critical illness. A comparison of clinical judgment with a prediction rule. , 1989, Archives of internal medicine.

[17]  W. Knaus,et al.  The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. , 1991, Chest.

[18]  R W Carlson,et al.  Comparison of clinical assessment with APACHE II for predicting mortality risk in patients admitted to a medical intensive care unit. , 1988, JAMA.

[19]  B. Zarén,et al.  Quality of life among long‐term survivors of intensive care , 1987, Critical care medicine.

[20]  C. Sprung,et al.  Evaluation of triage decisions for intensive care admission. , 1999, Critical care medicine.

[21]  Gavin Joynt,et al.  Prospective evaluation of patients refused admission to an intensive care unit: triage, futility and outcome , 2001, Intensive Care Medicine.

[22]  S. Lemeshow,et al.  Modeling the severity of illness of ICU patients. A systems update. , 1994, JAMA.

[23]  R. Uhlmann,et al.  Perceived quality of life and preferences for life-sustaining treatment in older adults. , 1991, Archives of internal medicine.

[24]  D. Hosmer,et al.  A review of goodness of fit statistics for use in the development of logistic regression models. , 1982, American journal of epidemiology.

[25]  Sylvie Chevret,et al.  Compliance with triage to intensive care recommendations , 2001, Critical care medicine.

[26]  S. Lemeshow,et al.  Mortality Probability Models (MPM II) based on an international cohort of intensive care unit patients. , 1993, JAMA.

[27]  Elizabeth H Bradley,et al.  Understanding the treatment preferences of seriously ill patients. , 2002, The New England journal of medicine.