Review and performance evaluation of aggregate weighted 'track and trigger' systems.

OBJECTIVES There is no up-to-date literature review of physiologically based, aggregate weighted 'track and trigger' systems (AWTTS) and few data on their predictive ability for serious adverse outcomes. The aim of this study was to describe the AWTTS in clinical use and assess their ability to discriminate between survivors and non-survivors of hospital admission, based on an initial set of vital signs. MATERIALS AND METHODS A systematic review of the literature was performed, to describe the AWTTS, their components and their differences. Their ability to discriminate between survivors and non-survivors was evaluated using the area under the receiver-operating characteristics (AUROC) curve, and a database of 9987 vital signs datasets. RESULTS A total of 33 unique AWTTS were identified with AUROC (+/-95% CI) ranging from 0.657 (0.636-0.678) to 0.782 (0.767-0.797). 12 AWTTS (36%) discriminated reasonably well between survivors and non-survivors, the top four performing AWTTS incorporated age as a component (AUROCs ranging from 0.722 to 0.782). The top two systems also incorporated temperature. CONCLUSIONS There is a wide range of unique, but very similar, AWTTS in clinical use. There is no consistency regarding their physiological components, but the majority differ only in minor variations in the weightings for physiological derangement and/or the cut-off points between physiological weighting bands. The performance of most systems tested was poor when used to discriminate between survivors and non-survivors, although 36% discriminated reasonably well. Our results suggest that physiology can be used to predict outcome, but that further work is required to improve the AWTTS models.

[1]  Robert J Oakey,et al.  Physiological observation track and trigger system. , 2006, Nursing standard (Royal College of Nursing (Great Britain) : 1987).

[2]  G. Barlow,et al.  The CURB65 pneumonia severity score outperforms generic sepsis and early warning scores in predicting mortality in community-acquired pneumonia , 2006, Thorax.

[3]  Medical emergency teams: Is there M.E.R.I.T? , 2007, Canadian journal of anaesthesia = Journal canadien d'anesthesie.

[4]  D. Watson.  The impact of accurate patient assessment on quality of care. , 2006, Nursing times.

[5]  D. Harrison,et al.  Systematic review and evaluation of physiological track and trigger warning systems for identifying at-risk patients on the ward , 2007, Intensive Care Medicine.

[6]  O. Boyd,et al.  Criteria for admission to the ICU and scoring systems for severity of illness , 2007 .

[7]  Gary B. Smith,et al.  Calculating early warning scores--a classroom comparison of pen and paper and hand-held computer methods. , 2006, Resuscitation.

[8]  C. Subbe,et al.  Effect of introducing the Modified Early Warning score on clinical outcomes, cardio‐pulmonary arrests and intensive care utilisation in acute medical admissions * , 2003, Anaesthesia.

[9]  N. Beeching,et al.  Laboratory risk factors for hospital mortality in acutely admitted patients. , 2007, QJM : monthly journal of the Association of Physicians.

[10]  A. Glasmacher,et al.  Observation-based early warning scores to detect impending critical illness predict in-hospital and overall survival in patients undergoing allogeneic stem cell transplantation. , 2007, Biology of blood and marrow transplantation : journal of the American Society for Blood and Marrow Transplantation.

[11]  Michael A. DeVita,et al.  Medical Emergency Teams , 2006 .

[12]  Kirsty Challen,et al.  Physiological-social score (PMEWS) vs. CURB-65 to triage pandemic influenza: a comparative validation study using community-acquired pneumonia as a proxy , 2007, BMC Health Services Research.

[13]  M. Chatterjee,et al.  The “OBS” chart: an evidence based approach to re-design of the patient observation chart in a district general hospital setting , 2005, Postgraduate Medical Journal.

[14]  L. Lind,et al.  Rapid Emergency Medicine score: a new prognostic tool for in‐hospital mortality in nonsurgical emergency department patients , 2004, Journal of internal medicine.

[15]  D. Prytherch,et al.  Risk‐adjusted predictive models of mortality after index arterial operations using a minimal data set , 2005, The British journal of surgery.

[16]  R. Morgan,et al.  Early detection of patients at risk (PART) , 2000, Anaesthesia.

[17]  Timothy H. Rainer,et al.  Validation of a Modified Early Warning Score (Mews) in Emergency Department Observation Ward Patients , 2006 .

[18]  M. Carberry.  Implementing the modified early warning system: our experiences. , 2002, Nursing in critical care.

[19]  L. Lind,et al.  Comparison of the rapid emergency medicine score and APACHE II in nonsurgical emergency department patients. , 2003, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[20]  J. McGaughey,et al.  Outreach and Early Warning Systems (EWS) for the prevention of intensive care admission and death of critically ill adult patients on general hospital wards. , 2007, The Cochrane database of systematic reviews.

[21]  N. Cooper.  Early warning scores for emergency admissions , 2005 .

[22]  C. Subbe,et al.  Validation of physiological scoring systems in the accident and emergency department , 2006, Emergency Medicine Journal.

[23]  A F Smith,et al.  Incidence and significance of errors in a patient ‘track and trigger’ system during an epidemic of Legionnaires' disease: retrospective casenote analysis , 2006, Anaesthesia.

[24]  L. Lind,et al.  Rapid Emergency Medicine Score can predict long-term mortality in nonsurgical emergency department patients. , 2004, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[25]  J. Bion,et al.  Clinical review: Outreach – a strategy for improving the care of the acutely ill hospitalized patient , 2003, Critical care.

[26]  J. Gardner-Thorpe,et al.  The value of Modified Early Warning Score (MEWS) in surgical in-patients: a prospective observational study. , 2006, Annals of the Royal College of Surgeons of England.

[27]  R. Crouch,et al.  Physiological observations of patients admitted from A&E. , 2002, Nursing standard (Royal College of Nursing (Great Britain) : 1987).

[28]  An audit of a patient-at-risk trigger scoring system for identifying seriously ill ward patients. , 2002, Nursing in critical care.

[29]  P. Fox.  An acute problem: ACE Chair Peter Fox looks at the vexed question of so-called ‘bedblocking’ , 1991 .

[30]  B. Riley,et al.  Critical care outreach: rationale and development , 2001 .

[31]  M. Parr,et al.  Medical emergency teams: a role for expanding intensive care? , 2006, Acta anaesthesiologica Scandinavica.

[32]  G. Smith,et al.  The effect of lead time bias on severity of illness scoring, mortality prediction and standardised mortality ratio in intensive care — a pilot study , 1998, Anaesthesia.

[33]  B. A. Day.  Early warning system scores and response times: an audit. , 2003, Nursing in critical care.

[34]  M. Odell,et al.  An acute problem? A report of the National Confidential Enquiry into Patient Outcome and Death. , 2005, Nursing in critical care.

[35]  Implementing a nurse-led critical care outreach service in an acute hospital. , 2006, Journal of clinical nursing.

[36]  H. Hancock,et al.  Critical care outreach: the need for effective decision-making in clinical practice (part 2). , 2007, Intensive & critical care nursing.

[37]  L. Lind,et al.  Charlson Comorbidity Index can add prognostic information to Rapid Emergency Medicine Score as a predictor of long-term mortality , 2005, European journal of emergency medicine : official journal of the European Society for Emergency Medicine.

[38]  L. Forni,et al.  Worthing physiological scoring system: derivation and validation of a physiological early-warning system for medical admissions. An observational, population-based single-centre study. , 2007, British journal of anaesthesia.

[39]  A. Pittard,et al.  Out of our reach? Assessing the impact of introducing a critical care outreach service , 2003, Anaesthesia.

[40]  C. Subbe,et al.  Does earlier detection of critically ill patients on surgical wards lead to better outcomes? , 2005, Annals of the Royal College of Surgeons of England.

[41]  M. Tivey,et al.  Prospective evaluation of a modified Early Warning Score to aid earlier detection of patients developing critical illness on a general surgical ward , 2000 .

[42]  C. Mann,et al.  Use of the patient at risk scores in the emergency department: a preliminary study , 2004, Emergency Medicine Journal.

[43]  C J Fisher,et al.  The Rapid Acute Physiology Score. , 1987, The American journal of emergency medicine.

[44]  D. Goldhill,et al.  Intensive care outreach services , 2002 .

[45]  P. C. Weaver,et al.  POSSUM and Portsmouth POSSUM for predicting mortality , 1998 .

[46]  D. Goldhill.  Preventing surgical deaths: critical care and intensive care outreach services in the postoperative period. , 2005, British journal of anaesthesia.

[47]  A. Kapila,et al.  The effect of a critical care outreach service and an early warning scoring system on respiratory rate recording on the general wards. , 2007, Resuscitation.

[48]  Critical care outreach comes to Canada , 2006, Canadian Medical Association Journal.

[49]  T. Hodgetts,et al.  The identification of risk factors for cardiac arrest and formulation of activation criteria to alert a medical emergency team. , 2002, Resuscitation.

[50]  Emma Baines,et al.  Early warning scores , 2008, BMJ.

[51]  Gary B. Smith,et al.  Hospital-wide physiological surveillance-a new approach to the early identification and management of the sick patient. , 2006, Resuscitation.

[52]  K. Hillman,et al.  Findings of the First Consensus Conference on Medical Emergency Teams* , 2006, Critical care medicine.

[53]  H. Montenegro,et al.  Beyond the intensive care unit: a review of interventions aimed at anticipating and preventing in-hospital cardiopulmonary arrest. , 2007, Resuscitation.

[54]  P. C. Weaver,et al.  The use of routine laboratory data to predict in-hospital death in medical admissions. , 2005, Resuscitation.

[55]  L. Hann,et al.  Setting standards for assessment of ward patients at risk of deterioration. , 2004, British journal of nursing.

[56]  F McArthur-Rouse,et al.  Critical care outreach services and early warning scoring systems: a review of the literature. , 2001, Journal of advanced nursing.

[57]  W. S. Dempsey,et al.  A mattress for patients with bowel fistula. , 1949, Surgery.

[58]  Heather Waterman,et al.  Packaging: a grounded theory of how to report physiological deterioration effectively. , 2005, Journal of advanced nursing.

[59]  Nicola Cooper.  Patient at risk! , 2001, Clinical medicine.

[60]  R. Paterson,et al.  Prediction of in-hospital mortality and length of stay using an early warning scoring system: clinical audit. , 2006, Clinical medicine.

[61]  M. Odell,et al.  The critical care outreach service and the early warning system on surgical wards. , 2002, Nursing in critical care.

[62]  Elizabeth A. Hunt,et al.  Rapid response systems: A systematic review* , 2007, Critical care medicine.

[63]  Critical care outreach: creating a safe culture. , 2005, British journal of nursing.

[64]  Arash Rashidian,et al.  Introducing Critical Care Outreach: a ward-randomised trial of phased introduction in a general hospital , 2004, Intensive Care Medicine.

[65]  Kate Allen.  Recognising and managing adult patients who are critically sick. , 2004, Nursing times.

[66]  J Nicholl,et al.  Prediction of mortality among emergency medical admissions , 2006, Emergency Medicine Journal.

[67]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[68]  B. Cuthbertson,et al.  A warning on early-warning scores! , 2007, British journal of anaesthesia.

[69]  R. Morgan,et al.  An early warning scoring system for detecting developing critical illness , 1997 .

[70]  S. Harvey,et al.  Investigating the effectiveness of critical care outreach services: a systematic review , 2006, Intensive Care Medicine.

[71]  D. Harrison,et al.  Reproducibility of physiological track-and-trigger warning systems for identifying at-risk patients on the ward , 2007, Intensive Care Medicine.

[72]  C. Subbe,et al.  Validation of a modified Early Warning Score in medical admissions. , 2001, QJM : monthly journal of the Association of Physicians.

[73]  Julie T Sharpley,et al.  Introducing an early warning scoring system in a district general hospital. , 2004, Nursing in critical care.

[74]  R. McNamee,et al.  Use of a patient information system to audit the introduction of modified early warning scoring. , 2005, Journal of evaluation in clinical practice.

[75]  A. McGinley,et al.  A physiologically‐based early warning score for ward patients: the association between score and outcome * , 2005, Anaesthesia.

[76]  P. C. Weaver,et al.  Towards a national clinical minimum data set for general surgery , 2003, The British journal of surgery.

[77]  G. Barlow,et al.  The CURB 65 pneumonia severity score outperforms generic sepsis and early warning scores in predicting mortality in community-acquired pneumonia , 2007 .

[78]  J. Kellett,et al.  The Simple Clinical Score predicts mortality for 30 days after admission to an acute medical unit. , 2006, QJM : monthly journal of the Association of Physicians.

[79]  J. Laurenson,et al.  Evaluation of Early Warning Systems on a Medical Admissions Unit , 2005 .