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Int J Health Care Qual Assur ; 25(1): 19-40, 2012.
Article in English | MEDLINE | ID: mdl-22455006

ABSTRACT

PURPOSE: This study seeks to investigate doctors' desire to change the hospital where they work to sustain higher quality care. DESIGN/METHODOLOGY/APPROACH: Self-administered questionnaires were sent to doctors in Aichi Prefecture, Japan. Data were analyzed using univariate and logistic regression analysis and recursive partitioning. FINDINGS: Factors related to doctors' desire to change hospitals, according to logistic regression, were interaction between working hours and satisfaction with the hospital, evaluation, local government hospitals versus private ones, small vs large hospitals, ophthalmology versus internal medicine, desire to continue working as a hospital doctor and age. Additionally, working hours were also found to be related, based on recursive partitioning. RESEARCH LIMITATIONS/IMPLICATIONS: The response rate was low and sampling bias was observed--therefore results need careful interpretation. Also, because this was a cross-sectional study, causal relationships could not be identified. Desire to change hospitals, but not actual behavior, was measured. PRACTICAL IMPLICATIONS: Efforts to prevent doctors from changing hospitals should include considering job satisfaction and workload, doctor evaluation methods, support for career progression and organizational management. ORIGINALITY/VALUE: As the hospital doctor shortage in rural areas becomes more serious, exploring doctors' desire to leave their current hospital is meaningful for Japanese hospital managers and hospitals worldwide aiming to provide sustainable and higher quality care.


Subject(s)
Hospital-Physician Relations , Job Satisfaction , Medical Staff, Hospital/psychology , Physicians/psychology , Adult , Aged , Analysis of Variance , Attitude of Health Personnel , Career Mobility , Cross-Sectional Studies , Female , Hospitals/classification , Humans , Japan , Logistic Models , Male , Medical Staff, Hospital/organization & administration , Medical Staff, Hospital/supply & distribution , Middle Aged , Personnel Staffing and Scheduling , Physicians/supply & distribution , Selection Bias , Surveys and Questionnaires , Workload
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