title: The use of benchmarking to identify top performing critical care units: a preliminary assessment of their policies and practices.
abstract: OBJECTIVE
  To describe the policies and practices of intensive care units (ICUs) with good patient survival and highly efficient resource use and to identify relevant variables for future investigation.
  
  
  METHODS
  We used clinical data for 359,715 patients from 108 ICUs to compare the ratios of actual with Acute Physiology and Chronic Health Evaluation (APACHE) III predicted hospital mortality, ICU and hospital stay, and the proportion of low-risk monitor patients. The best performing ICUs (top 10%) were defined by a mortality ratio of 1.0 or less, and either the lowest ratio for ICU stay, hospital stay, or percentage of low-risk monitor patients. The medical and nursing directors of top performing ICUs completed a questionnaire to describe their unit's structure policies and practices.
  
  
  RESULTS
  Among the 108 ICUs, 61 (56%) had a ratio of actual to predicted hospital mortality of 1.0 or less and the best performing units had ICU stay ratios of 0.62 to 0.79, hospital stay ratios of 0.73 to 0.77, and admitted 10% to 38% low-risk monitor patients. ICU structure varied among the best performing ICUs. Units with the shortest ICU and hospital stay had alternatives to intensive care, methods to facilitate patient throughput, used multiple protocols for high-volume diagnoses and care processes, and continuously monitored resource use. Units with the fewest low-risk monitor patients screened potential admissions, had intermediate care areas, extended-stay recovery rooms, and care pathways for high-volume diagnoses.
  
  
  CONCLUSIONS
  Benchmarking can be used to identify ICUs with good patient survival and highly efficient resource use. The combination of policies and practices used by these units might improve resource use in other ICUs.
authors.affiliation: Department of Anesthesiology and Critical Care Medicine, The George Washington University, Washington, DC, USA. jackzimm@erols.com
authors.forename: Jack E
authors.initials: JE
authors.lastname: Zimmerman
authors.forename: Carlos
authors.initials: C
authors.lastname: Alzola
authors.forename: Kathryn T
authors.initials: KT
authors.lastname: Von Rueden
mesh_terms: D018806:APACHE; D019985:Benchmarking / Q000379:methods* / Q000706:statistics & numerical data; D015331:Cohort Studies; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000458:organization & administration* / Q000706:statistics & numerical data; D007902:Length of Stay / Q000706:statistics & numerical data; D011383:Progressive Patient Care; D012189:Retrospective Studies