Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: The Rx for Change database: a first-in-class tool for optimal prescribing and medicines use | Weir et al. Implementation Science 2010 5 89 http content 5 1 89 Implementation Science IMPLEMENTATION SCIENCE METHODOLOGY Open Access The Rx for Change database a first-in-class tool for optimal prescribing and medicines use 12 1 1 2 4 Michelle C Weir Rebecca Ryan Alain Mayhew Julia Worswick Nancy Santesso Dianne Lowe Bill Leslie Adrienne Stevens1 Sophie Hill2 Jeremy M Grimshaw1 5 6 Abstract Background Globally suboptimal prescribing practices and medication errors are common. Guidance to health professionals and consumers alone is not sufficient to optimise behaviours therefore strategies to promote evidence-based decision making and practice such as decision support tools or reminders are important. The literature in this area is growing but is of variable quality and dispersed across sources which makes it difficult to identify access and assess. To overcome these problems by synthesizing and evaluating the data from systematic reviews we have developed Rx for Change to provide a comprehensive online database of the evidence for strategies to improve drug prescribing and use. Methods We use reliable and valid methods to search and screen the literature and to appraise and analyse the evidence from relevant systematic reviews. We then present the findings in an online format which allows users to easily access pertinent information related to prescribing and medicines use. The database is a result of the collaboration between the Canadian Agency for Drugs and Technologies in Health CADTH and two Cochrane review groups. Results To capture the body of evidence on interventions to improve prescribing and medicines use we conduct comprehensive and regular searches in multiple databases and hand-searches of relevant journals. We screen articles to identify relevant systematic reviews and include them if they are of moderate or high methodological quality. Two researchers screen assess quality and extract data on demographic details .
