Integration of evidence based medicine into the clinical years of a medical curriculum

Teaching Evidence Based Medicine [EBM] helps medical students to develop their decision making skills based on current best evidence, especially when it is taught in a clinical context. Few medical schools integrate Evidence Based Medicine into undergraduate curriculum, and those who do so, do it at the academic years only as a standalone [classroom] teaching but not at the clinical years. The College of Medicine at King Saud bin Abdulaziz University for Health Sciences was established in January 2004. The college adopted a four-year Problem Based Learning web-based curriculum. The objective of this paper is to present our experience in the integration of the EBM in the clinical phase of the medical curriculum. We teach EBM in 3 steps: first step is teaching EBM concepts and principles, second is teaching the appraisal and search skills, and the last step is teaching it in clinical rotations. Teaching EBM at clinical years consists of 4 student-centered tutorials. In conclusion, EBM may be taught in a systematic, patient centered approach at clinical rounds. This paper could serve as a model of Evidence Based Medicine integration into the clinical phase of a medical curriculum

Quality of psychiatric referrals in Saudi Arabia. A structural equation modeling approach

This study seeks to model proposed causal relationships between the quality of psychiatric referral letters, and its indicators, linked to the features of the referred patient, referring physician, and practice setting. This study was executed at Buraidah Mental Health Hospital, Saudi Arabia, in the year 2000-2002. Data regarding 18 independent variables underlying 3 latent constructs and one dependent variable represented by quality of psychiatric referral letter score [outcome] was derived from patient files, physician training records, and 540 psychiatric referrals. Structural equation modeling was used to analyze the data for examining proposed causal relationships between the quality of psychiatric referral letters, and its potential predictors. The structural equation modeling analysis revealed a reasonably good fit of the proposed model to the data based on various fit indices. The tested model explained 67% of the variance in the quality of psychiatric referral letters. The referring physician characteristics [experience, education, and psychiatric training] and features of the referral setting [nature of setting and referral letters-administrative information] were highly significant indicators of quality of psychiatric referral letters, which in turn was negatively predicted by patient features including severity of the mental illness. Despite some caveats, the quality of psychiatric referral letters is accurately predicted by 3 latent constructs represented by referring physician skills, nature of the setting, and patient socio-clinical features