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báo cáo khoa học: " Predicting implementation from organizational readiness for change: a study protocol"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Predicting implementation from organizational readiness for change: a study protocol | Helfrich et al. Implementation Science 2011 6 76 http www.implementationscience.eom content 6 1 76 Implementation Science IMPLEMENTATION SCIENCE STUDY PROTOCOL Open Access Predicting implementation from organizational readiness for change a study protocol VI r I S h I_l -J-íVí -P 1 2 D I 11r 3 4 I I c V V I it p 4 6 D A I m - I I 5 I I b h D I_I z t s 7 8 I_I i I r-1 i I_I s z-i o z s. M- L . 9 Christian D Henrich Dean Blevins Jeffrey L Smith P Adam Kelly limothy P Hogan Hildi Hagedorn Patricia M Dubbert10 11 and Anne E Sales12 13 Abstract Background There is widespread interest in measuring organizational readiness to implement evidence-based practices in clinical care. However there are a number of challenges to validating organizational measures including inferential bias arising from the halo effect and method bias - two threats to validity that while well-documented by organizational scholars are often ignored in health services research. We describe a protocol to comprehensively assess the psychometric properties of a previously developed survey the Organizational Readiness to Change Assessment. Objectives Our objective is to conduct a comprehensive assessment of the psychometric properties of the Organizational Readiness to Change Assessment incorporating methods specifically to address threats from halo effect and method bias. Methods and Design We will conduct three sets of analyses using longitudinal secondary data from four partner projects each testing interventions to improve the implementation of an evidence-based clinical practice. Partner projects field the Organizational Readiness to Change Assessment at baseline n 208 respondents 53 facilities and prospectively assesses the degree to which the evidence-based practice is implemented. We will conduct predictive and concurrent validities using hierarchical linear modeling and multivariate regression respectively. For predictive validity the outcome is the change from baseline to follow-up in the use