Mark W Friedberg1, Hector P Rodriguez, Grant R Martsolf, Maria O Edelen, Arturo Vargas Bustamante. 1. *RAND Corporation †Department of Medicine, Brigham and Women's Hospital ‡Department of Medicine, Harvard Medical School, Boston, MA §School of Public Health, University of California, Berkeley, CA ∥RAND Corporation, Pittsburgh, PA ¶Department of Health Policy and Management at the UCLA Fielding School of Public Health, University of California, Los Angeles, CA.
Abstract
BACKGROUND: The effectiveness of community clinics and health centers' efforts to improve the quality of care might be modified by clinics' workplace climates. Several surveys to measure workplace climate exist, but their relationships to each other and to distinguishable dimensions of workplace climate are unknown. OBJECTIVE: To assess the psychometric properties of a survey instrument combining items from several existing surveys of workplace climate and to generate a shorter instrument for future use. MATERIALS AND METHODS: We fielded a 106-item survey, which included items from 9 existing instruments, to all clinicians and staff members (n=781) working in 30 California community clinics and health centers, receiving 628 responses (80% response rate). We performed exploratory factor analysis of survey responses, followed by confirmatory factor analysis of 200 reserved survey responses. We generated a new, shorter survey instrument of items with strong factor loadings. RESULTS: Six factors, including 44 survey items, emerged from the exploratory analysis. Two factors (Clinic Workload and Teamwork) were independent from the others. The remaining 4 factors (staff relationships, quality improvement orientation, managerial readiness for change, and staff readiness for change) were highly correlated, indicating that these represented dimensions of a higher-order factor we called "Clinic Functionality." This 2-level, 6-factor model fit the data well in the exploratory and confirmatory samples. For all but 1 factor, fewer than 20 survey responses were needed to achieve clinic-level reliability >0.7. CONCLUSIONS: Survey instruments designed to measure workplace climate have substantial overlap. The relatively parsimonious item set we identified might help target and tailor clinics' quality improvement efforts.
BACKGROUND: The effectiveness of community clinics and health centers' efforts to improve the quality of care might be modified by clinics' workplace climates. Several surveys to measure workplace climate exist, but their relationships to each other and to distinguishable dimensions of workplace climate are unknown. OBJECTIVE: To assess the psychometric properties of a survey instrument combining items from several existing surveys of workplace climate and to generate a shorter instrument for future use. MATERIALS AND METHODS: We fielded a 106-item survey, which included items from 9 existing instruments, to all clinicians and staff members (n=781) working in 30 California community clinics and health centers, receiving 628 responses (80% response rate). We performed exploratory factor analysis of survey responses, followed by confirmatory factor analysis of 200 reserved survey responses. We generated a new, shorter survey instrument of items with strong factor loadings. RESULTS: Six factors, including 44 survey items, emerged from the exploratory analysis. Two factors (Clinic Workload and Teamwork) were independent from the others. The remaining 4 factors (staff relationships, quality improvement orientation, managerial readiness for change, and staff readiness for change) were highly correlated, indicating that these represented dimensions of a higher-order factor we called "Clinic Functionality." This 2-level, 6-factor model fit the data well in the exploratory and confirmatory samples. For all but 1 factor, fewer than 20 survey responses were needed to achieve clinic-level reliability >0.7. CONCLUSIONS: Survey instruments designed to measure workplace climate have substantial overlap. The relatively parsimonious item set we identified might help target and tailor clinics' quality improvement efforts.
Authors: Carlos Roberto Jaén; Benjamin F Crabtree; Raymond F Palmer; Robert L Ferrer; Paul A Nutting; William L Miller; Elizabeth E Stewart; Robert Wood; Marivel Davila; Kurt C Stange Journal: Ann Fam Med Date: 2010 Impact factor: 5.166
Authors: Thomas Bodenheimer; Margaret C Wang; Thomas G Rundall; Stephen M Shortell; Robin R Gillies; Nancy Oswald; Lawrence Casalino; James C Robinson Journal: Jt Comm J Qual Saf Date: 2004-09
Authors: William L Miller; Benjamin F Crabtree; Paul A Nutting; Kurt C Stange; Carlos Roberto Jaén Journal: Ann Fam Med Date: 2010 Impact factor: 5.166
Authors: Leif I Solberg; Mary C Hroscikoski; JoAnn M Sperl-Hillen; Peter G Harper; Benjamin F Crabtree Journal: Ann Fam Med Date: 2006 Mar-Apr Impact factor: 5.166
Authors: Jessica E Graber; Elbert S Huang; Melinda L Drum; Marshall H Chin; Amy E Walters; Loretta Heuer; Hui Tang; Cynthia T Schaefer; Michael T Quinn Journal: Health Serv Res Date: 2008-01-31 Impact factor: 3.402
Authors: Sara J Singer; Anna D Sinaiko; Maike V Tietschert; Michaela Kerrissey; Russell S Phillips; Veronique Martin; Grace Joseph; Hassina Bahadurzada; Denis Agniel Journal: Health Serv Res Date: 2020-12 Impact factor: 3.402
Authors: Kimberly S Hsiung; Jason B Colditz; Elizabeth A McGuier; Galen E Switzer; Helena M VonVille; Barbara L Folb; David J Kolko Journal: J Gen Intern Med Date: 2020-11-02 Impact factor: 5.128
Authors: Susanne M Maassen; Anne Marie J W Weggelaar Jansen; Gerard Brekelmans; Hester Vermeulen; Catharina J van Oostveen Journal: Int J Qual Health Care Date: 2020-11-09 Impact factor: 2.038
Authors: Hector P Rodriguez; Mark W Friedberg; Arturo Vargas-Bustamante; Xiao Chen; Ana E Martinez; Dylan H Roby Journal: BMC Health Serv Res Date: 2018-11-20 Impact factor: 2.655