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Measuring and Comparing Safety Climate in Intensive Care Units

France, Daniel J. PhD, MPH*; Greevy, Robert A. Jr PhD†; Liu, Xulei MS†; Burgess, Hayley PharmD, BCPP‡; Dittus, Robert S. MD, MPH§; Weinger, Matthew B. MD*; Speroff, Theodore PhD¶

doi: 10.1097/MLR.0b013e3181c162d6
Brief Report

Background: Learning about the factors that influence safety climate and improving the methods for assessing relative performance among hospital or units would improve decision-making for clinical improvement.

Objectives: To measure safety climate in intensive care units (ICU) owned by a large for-profit integrated health delivery systems; identify specific provider, ICU, and hospital factors that influence safety climate; and improve the reporting of safety climate data for comparison and benchmarking.

Research Design: We administered the Safety Attitudes Questionnaire (SAQ) to clinicians, staff, and administrators in 110 ICUs from 61 hospitals.

Subjects: A total of 1502 surveys (43% response) from physicians, nurses, respiratory therapists, pharmacists, mangers, and other ancillary providers.

Measures: The survey measured safety climate across 6 domains: teamwork climate; safety climate; perceptions of management; job satisfaction; working conditions; and stress recognition. Percentage of positive scores, mean scores, unadjusted random effects, and covariate-adjusted random effect were used to rank ICU performance.

Results: The cohort was characterized by a positive safety climate. Respondents scored perceptions of management and working conditions significantly lower than the other domains of safety climate. Respondent job type was significantly associated with safety climate and domain scores. There was modest agreement between ranking methodologies using raw scores and random effects.

Conclusions: The relative proportion of job type must be considered before comparing safety climate results across organizational units. Ranking methodologies based on raw scores and random effects are viable for feedback reports. The use of covariate-adjusted random effects is recommended for hospital decision-making.

From the *Center for Perioperative Research in Quality, Nashville, TN; †Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN; ‡Texas Medical Institute of Technology, Columbia, TN; §Division of General Internal Medicine and Public Health, Nashville, TN; and ¶Division of General Internal Medicine, VA Tennessee Valley Healthcare System, Vanderbilt University Medical Center, Nashville, TN.

Supported by the agency for Healthcare Quality and Research, grant number 1U18HS015934-01 improving safe critical care, Theodore Speroff, PhD, principal investigator.

Reprints: Daniel J. France, PhD, MPH, Center for Perioperative Research in Quality, 1211 21st Ave South, Suite 732, Nashville, TN 37212-1212. E-mail: dan.france@vanderbilt.edu.

© 2010 Lippincott Williams & Wilkins, Inc.