OBJECTIVES: To examine the association between work hours, work stress, and collaboration among the ward personnel, and the risk of hospital-associated infection among patients. DESIGN: Cross-sectional data on hospital infections were collected between March and June 2004. These data were linked with ward-level responses to a personnel survey collected during the same time period. SETTING: Medical records of patients in 60 non-psychiatric bed wards in 6 Finnish hospitals. PARTICIPANTS: One thousand ninety-two patients and 1159 staff survey responses. MEASUREMENTS: Prevalence surveillance was performed by 4 infection control nurses, using standard criteria. Data on several potential risk factors for infection were collected: sex, age, patient type (surgical vs. other), hospital type (university vs. regional hospital), unit type, number of patients in the ward, exposure to invasive devices, International Classification of Diseases version 10 diagnosis, chemotherapy, radiotherapy, and use of corticosteroids. Staff working conditions were measured by survey scales. RESULTS: Ninety-nine cases (9.1%) of hospital-associated infection were found. Multilevel logistic regression analyses, adjusted for hospital factors and patient-related risk factors, showed that long work hours among staff were associated with increased risk of infection [odds ratio (OR) 2.74, 95% confidence interval (CI): 1.07-7.04]. Other staff-related correlates of infection were high work stress, as indicated by high imbalance between efforts and rewards (OR: 2.47; 95% CI: 1.38-4.42), low trust between work unit members (OR: 2.37; 95% CI: 1.27-4.43), injustice in the distribution of work (OR: 1.81; 95% CI: 1.04-3.16), and poor collaboration between ward supervisors (OR: 2.46; 95% CI: 1.38-4.38). CONCLUSIONS: Long work hours, high work stress, and poor collaboration among the ward staff are associated with hospital-associated infection among patients.
OBJECTIVES: To examine the association between work hours, work stress, and collaboration among the ward personnel, and the risk of hospital-associated infection among patients. DESIGN: Cross-sectional data on hospital infections were collected between March and June 2004. These data were linked with ward-level responses to a personnel survey collected during the same time period. SETTING: Medical records of patients in 60 non-psychiatric bed wards in 6 Finnish hospitals. PARTICIPANTS: One thousand ninety-two patients and 1159 staff survey responses. MEASUREMENTS: Prevalence surveillance was performed by 4 infection control nurses, using standard criteria. Data on several potential risk factors for infection were collected: sex, age, patient type (surgical vs. other), hospital type (university vs. regional hospital), unit type, number of patients in the ward, exposure to invasive devices, International Classification of Diseases version 10 diagnosis, chemotherapy, radiotherapy, and use of corticosteroids. Staff working conditions were measured by survey scales. RESULTS: Ninety-nine cases (9.1%) of hospital-associated infection were found. Multilevel logistic regression analyses, adjusted for hospital factors and patient-related risk factors, showed that long work hours among staff were associated with increased risk of infection [odds ratio (OR) 2.74, 95% confidence interval (CI): 1.07-7.04]. Other staff-related correlates of infection were high work stress, as indicated by high imbalance between efforts and rewards (OR: 2.47; 95% CI: 1.38-4.42), low trust between work unit members (OR: 2.37; 95% CI: 1.27-4.43), injustice in the distribution of work (OR: 1.81; 95% CI: 1.04-3.16), and poor collaboration between ward supervisors (OR: 2.46; 95% CI: 1.38-4.38). CONCLUSIONS: Long work hours, high work stress, and poor collaboration among the ward staff are associated with hospital-associated infection among patients.
Authors: Monika Pogorzelska-Maziarz; Ingrid M Nembhard; Rebecca Schnall; Shanelle Nelson; Patricia W Stone Journal: Am J Med Qual Date: 2015-05-21 Impact factor: 1.852
Authors: Susanne Hartwig; Matti Uhari; Marjo Renko; Perrine Bertet; Maria Hemming; Timo Vesikari Journal: BMC Health Serv Res Date: 2014-12-11 Impact factor: 2.655