BackgroundSafety activities have been initiated at many hospitals in Taiwan, but little is known about the safety culture at these hospitals. The aims of this study were to verify a safety culture survey instrument in Chinese and to assess hospital safety culture in Taiwan.MethodsThe Taiwan Patient Safety Culture Survey was conducted in 2008, using the adapted Safety Attitude Questionnaire in Chinese (SAQ-C). Hospitals and their healthcare workers participated in the survey on a voluntary basis. The psychometric properties of the five SAQ-C dimensions were examined, including teamwork climate, safety climate, job satisfaction, perception of management, and working conditions. Additional safety measures were asked to assess healthcare workers' attitudes toward their collaboration with nurses, physicians, and pharmacists, respectively, and perceptions of hospitals' encouragement of safety reporting, safety training, and delivery delays due to communication breakdowns in clinical areas. The associations between the respondents' attitudes to each SAQ-C dimension and safety measures were analyzed by generalized estimating equations, adjusting for the clustering effects at hospital levels.ResultsA total of 45,242 valid questionnaires were returned from 200 hospitals with a mean response rate of 69.4%. The Cronbach's alpha was 0.792 for teamwork climate, 0.816 for safety climate, 0.912 for job satisfaction, 0.874 for perception of management, and 0.785 for working conditions. Confirmatory factor analyses demonstrated a good model fit for each dimension and the entire construct. The percentage of hospital healthcare workers holding positive attitude was 48.9% for teamwork climate, 45.2% for perception of management, 42.1% for job satisfaction, 37.2% for safety climate, and 31.8% for working conditions. There were wide variations in the range of SAQ-C scores in each dimension among hospitals. Compared to those without positive attitudes, healthcare workers with positive attitudes to each SAQ dimension were more likely to perceive good collaboration with coworkers, and their hospitals were more likely to encourage safety reporting and to prioritize safety training programs (Wald chi-square test, p < 0.001 for all).ConclusionsAnalytical results verified the psychometric properties of the SAQ-C at Taiwanese hospitals. The safety culture at most hospitals has not fully developed and there is considerable room for improvement.

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This paper presents a new white blood cell classification system for the recognition of five types of white blood cells. We propose a new segmentation algorithm for the segmentation of white blood cells from smear images. The core idea of the proposed segmentation algorithm is to find a discriminating region of white blood cells on the HSI color space. Pixels with color lying in the discriminating region described by an ellipsoidal region will be regarded as the nucleus and granule of cytoplasm of a white blood cell. Then, through a further morphological process, we can segment a white blood cell from a smear image. Three kinds of features (i.e., geometrical features, color features, and LDP-based texture features) are extracted from the segmented cell. These features are fed into three different kinds of neural networks to recognize the types of the white blood cells. To test the effectiveness of the proposed white blood cell classification system, a total of 450 white blood cells images were used. The highest overall correct recognition rate could reach 99.11% correct. Simulation results showed that the proposed white blood cell classification system was very competitive to some existing systems.

Dynamic magnetic resonance imaging (MRI) allows real-time characterization of upper airway collapse in sleeping subjects with obstructive sleep apnea (OSA). The aim of our study was to use sleep MRI to compare differences in upper airway collapse sites between BMI-matched subjects with mild OSA and severe OSA. This is a prospective, nested case-control study using dynamic sleep MRI to compare 15 severe OSA subjects (AHI >40) and 15 mild OSA (AHI <10) subjects, who were matched for BMI. Upper airway imaging was performed on sleeping subjects in a 3.0 T MRI scanner. Sleep MRI movies were used by blinded reviewers to identify retropalatal (RP), retroglossal (RG), and lateral pharyngeal wall (LPW) airway collapse. Mean AHI in the severe OSA group was 70.3 ± 23 events/h, and in the mild group was 7.8 ± 1 events/h (p < 0.001). All mild and severe OSA subjects demonstrated retropalatal airway collapse. Eighty percent in the mild group showed single-level RP collapse (p < 0.001). All subjects in the severe group showed multi-level collapse: RP + LPW (n = 9), RP + RG + LPW (n = 6). All severe OSA subjects showed LPW collapse, as compared with three subjects in the mild group (p < 0.001). LPW collapse was positively associated with AHI in simple regression analysis (β = 51.8, p < 0.001). In conclusion, severe OSA patients present with more lateral pharyngeal wall collapse as compared to BMI-matched mild OSA patients.