title: Monitoring the performance of intensive care units using the variable life-adjusted display: a simulation study to explore its applicability and efficiency.
abstract: OBJECTIVE
  Graphical monitoring tools are needed for real-time quality evaluation in intensive care unit. The variable life-adjusted display (VLAD) provides a directly interpretable assessment indicating whether the overall performance is better or worse than expected on the basis of the predicted risk of failure. The aim of this study is to quantify the ability of VLAD charts to early recognize a worsening in clinical performance.
  
  
  METHODS
  A Monte Carlo experiment simulating the sequence of successes and failures of an intensive care unit is performed; the predicted mortality is calculated by means of the Simplified Acute Physiology Score 3 admission score. From a given position in the admissions sequence, we increased the probability of death; we calculated: (i) the surveillance system delay in responding to the mortality increase; (ii) the percentage of cases where the VLAD has been able to give an alarm within the first 5, 10, 20 and 60 deaths occurred after the increase of probability of death; and (iii) the percentage of false declarations of increase (anticipated alarms).
  
  
  RESULTS
  The frequency distribution of the alarm delays shows VLAD was not always able to early detect mortality increase. Only a very small number of anticipated alarms were given.
  
  
  CONCLUSIONS
  Variable life-adjusted display ability to signal is mild and strictly correlated with the institution volume of activity. Therefore, the use of VLAD seems to be not always advisable, and an integration between VLAD and other well-documented tools as CUSUM charts could be preferable.
authors.affiliation: Department of Surgery, University of Pisa, Pisa, Italy. francescafoltran@libero.it
authors.forename: Francesca
authors.initials: F
authors.lastname: Foltran
authors.forename: Ileana
authors.initials: I
authors.lastname: Baldi
authors.forename: Guido
authors.initials: G
authors.lastname: Bertolini
authors.forename: Franco
authors.initials: F
authors.lastname: Merletti
authors.forename: Dario
authors.initials: D
authors.lastname: Gregori
mesh_terms: D016001:Confidence Intervals; D017052:Hospital Mortality; D007362:Intensive Care Units / Q000592:standards*; D009010:Monte Carlo Method; D017063:Outcome Assessment, Health Care / Q000379:methods; D011785:Quality Assurance, Health Care / Q000379:methods*; D020379:Risk Adjustment