title: The Effect of Intensive Care Unit Admission Patterns on Mortality-based Critical Care Performance Measures.
abstract: Current mortality-based critical care performance measurement focuses on intensive care unit (ICU) admissions as a single group, conflating low-severity and high-severity ICU patients for whom performance may differ and neglecting severely ill patients treated solely on hospital wards.
  
  
  
  To assess the relationship between hospital performance as measured by risk-standardized mortality for severely ill ICU patients, less severely ill ICU patients, and severely ill patients outside the ICU.
  
  
  
  Using a statewide, all-payer dataset from the Pennsylvania Healthcare Cost Containment Council, we analyzed discharge data for patients with nine clinical conditions with frequent ICU use. Using a validated severity-of-illness measure, we categorized hospitalized patients as either high severity (predicted probability of in-hospital death in top quartile) or low severity (all others). We then created three mutually exclusive groups: high-severity ICU admissions, low-severity ICU admissions, and high-severity ward patients. We used hierarchical logistic regression to generate hospital-specific 30-day risk-standardized mortality rates for each group and then compared hospital performance across groups using Spearman's rank correlation.
  
  
  
  We analyzed 87 hospitals with 22,734 low-severity ICU admissions (mean per hospital, 261 ± 187), 10,991 high-severity ICU admissions (mean per hospital, 126 ± 105), and 6,636 high-severity ward patients (mean per hospital, 76 ± 48). We found little correlation between hospital performance for high-severity ICU patients versus low-severity ICU patients (ρ = 0.15; P = 0.17). There were 29 hospitals (33%) that moved up or down at least two quartiles of performance across the ICU groups. There was weak correlation between hospital performance for high-severity ICU patients versus high-severity ward patients (ρ = 0.25; P = 0.02). There were 24 hospitals (28%) that moved up or down at least two quartiles of performance across the high-severity groups.
  
  
  
  Hospitals that perform well in caring for high-severity ICU patients do not necessarily also perform well in caring for low-severity ICU patients or high-severity ward patients, indicating that risk-standardized mortality rates for ICU admissions as a whole offer only a narrow window on a hospital's overall performance for critically ill patients.
authors.affiliation: 1 Division of Pulmonary, Allergy, and Critical Care Medicine.|2 CRISMA Center, Department of Critical Care Medicine, and.
authors.forename: Ian J
authors.initials: IJ
authors.lastname: Barbash
authors.affiliation: 2 CRISMA Center, Department of Critical Care Medicine, and.|3 Department of Health Policy & Management, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.
authors.forename: Tri Q
authors.initials: TQ
authors.lastname: Le
authors.affiliation: 2 CRISMA Center, Department of Critical Care Medicine, and.
authors.forename: Francis
authors.initials: F
authors.lastname: Pike
authors.affiliation: 2 CRISMA Center, Department of Critical Care Medicine, and.|4 Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; and.|3 Department of Health Policy & Management, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.
authors.forename: Amber E
authors.initials: AE
authors.lastname: Barnato
authors.affiliation: 2 CRISMA Center, Department of Critical Care Medicine, and.|3 Department of Health Policy & Management, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.
authors.forename: Derek C
authors.initials: DC
authors.lastname: Angus
authors.affiliation: 1 Division of Pulmonary, Allergy, and Critical Care Medicine.|2 CRISMA Center, Department of Critical Care Medicine, and.|3 Department of Health Policy & Management, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.
authors.forename: Jeremy M
authors.initials: JM
authors.lastname: Kahn
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003422:Critical Care / Q000592:standards*; D016638:Critical Illness / Q000401:mortality; D003430:Cross-Sectional Studies; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000458:organization & administration*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010343:Patient Admission / Q000706:statistics & numerical data*; D063868:Patient Outcome Assessment; D010414:Pennsylvania; D011336:Probability
keywords: critical care; health care quality assessment; health services; intensive care; patient outcome assessment