OBJECTIVES: Reviews of patient safety efforts suggest that technical/administrative change must be augmented by global factors such as organizational culture and climate. The objective was to outline a comprehensive model for healthcare climate and test one of its elements, the nursing subclimate, in terms of several patient safety outcomes. DESIGN: Measure organizational climate in nursing units, followed by random sampling of patient safety practices in each unit 6 months later. SETTING: Sixty-nine inpatient units in three hospitals that make up the entire tertiary care system in one metropolitan area. SUBJECTS: A total of 955 nurses. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A two-part Nursing Climate Scale referring to hospital- and unit-level climates, followed by five randomly timed observations of patient safety practices covering routine and emergency care in each unit. Climate scales met the criteria of internal reliability, within-unit agreement, and between-unit variability, using standard statistics of climate research. Both the hospital and unit nursing climates exhibited significant variation, which predicted the routine medication safety scores (Z = 2.65 and 2.93 accordingly, p < .01), with similar results for emergency safety scores. A significant interaction (Z = 2.78, p < .01) indicated that best/worst safety is obtained when the unit and hospital climates are aligned (for better or worse) and that positive unit climate can compensate for the detrimental effect of poor hospital climate. Furthermore, climate's strength increased its predictive power with regard to patient safety practices (Z = 3.64 for medication and 2.28 for emergency safety; p < .01). The small number of participating hospitals limits organization-level analyses. CONCLUSIONS: The nursing climate identifies units where the likelihood of adverse events is greater or lower than the hospital's average. Such information can guide prevention efforts in selected units. These data encourage the development of additional climate subscales subsumed under the healthcare climate model (e.g., physicians subclimate).
OBJECTIVES: Reviews of patient safety efforts suggest that technical/administrative change must be augmented by global factors such as organizational culture and climate. The objective was to outline a comprehensive model for healthcare climate and test one of its elements, the nursing subclimate, in terms of several patient safety outcomes. DESIGN: Measure organizational climate in nursing units, followed by random sampling of patient safety practices in each unit 6 months later. SETTING: Sixty-nine inpatient units in three hospitals that make up the entire tertiary care system in one metropolitan area. SUBJECTS: A total of 955 nurses. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A two-part Nursing Climate Scale referring to hospital- and unit-level climates, followed by five randomly timed observations of patient safety practices covering routine and emergency care in each unit. Climate scales met the criteria of internal reliability, within-unit agreement, and between-unit variability, using standard statistics of climate research. Both the hospital and unit nursing climates exhibited significant variation, which predicted the routine medication safety scores (Z = 2.65 and 2.93 accordingly, p < .01), with similar results for emergency safety scores. A significant interaction (Z = 2.78, p < .01) indicated that best/worst safety is obtained when the unit and hospital climates are aligned (for better or worse) and that positive unit climate can compensate for the detrimental effect of poor hospital climate. Furthermore, climate's strength increased its predictive power with regard to patient safety practices (Z = 3.64 for medication and 2.28 for emergency safety; p < .01). The small number of participating hospitals limits organization-level analyses. CONCLUSIONS: The nursing climate identifies units where the likelihood of adverse events is greater or lower than the hospital's average. Such information can guide prevention efforts in selected units. These data encourage the development of additional climate subscales subsumed under the healthcare climate model (e.g., physicians subclimate).
Authors: Liane R Ginsburg; You-Ta Chuang; Whitney Blair Berta; Peter G Norton; Peggy Ng; Deborah Tregunno; Julia Richardson Journal: Health Serv Res Date: 2010-03-10 Impact factor: 3.402
Authors: Liane Ginsburg; Debra Gilin; Deborah Tregunno; Peter G Norton; Ward Flemons; Mark Fleming Journal: Health Serv Res Date: 2008-09-17 Impact factor: 3.402
Authors: Barbara Hoffmann; Carolin Miessner; Zeycan Albay; Jakob Schröber; Katrin Weppler; Ferdinand M Gerlach; Corina Güthlin Journal: Ann Fam Med Date: 2013 Jul-Aug Impact factor: 5.166