Objectives:The study aims to understand the process and factors influencing the implementation of structured oral examination (SOE) for undergraduate medical students; in comparison with conventional oral examination (COE) in pharmacology.Methods:In a randomized, parallel group study, 123 students of pharmacology were divided into two groups, SOE (n = 63) and COE (n = 60). Students of each group were subdivided into two, and four examiners took viva voce individually. Three sets of questionnaires from autonomic nervous system were prepared, each having 15 items with increasing difficulty levels and were validated by subject experts and pretested. Ten minutes were allotted for each student for each viva. Feedback of students and faculty about the novel method was obtained.Results:SOE yielded significantly lower marks as compared to COE. There were significant inter-examiner variations in marks awarded in SOE and COE. Other factors influencing implementation were difficulty in structuring viva, rigid time limits, lack of flexibility in knowledge content, monotony, and fatigue. The students perceived this format not different from COE but felt that it required in-depth preparation of topic. Faculty opined that SOE led to less drift from main topic and provided uniform coverage of topics in given time.Conclusion:Conducting SOE is a resource-intensive exercise. Despite structuring, inter-examiner variability was not completely eliminated. The students’ performance was depended on factors related to examiners such as teaching experience, vernacular language used, and lack of training. Orientation and training of examiners in assessment strategies is necessary. Standardization of questionnaire is necessary before the implementation of SOE for summative assessment.

Purpose To explore the relationship between degree of rurality and glucose (hemoglobin A1c), blood pressure (BP), and lipid (LDL) control among patients with diabetes. Methods Descriptive study; 1,649 patients in 205 rural practices in the United States. Patients’ residence ZIP codes defined degree of rurality (Rural-Urban Commuting Areas codes). Outcomes were measures of acceptable control (A1c <= 9%, BP < 140/90 mmHg, LDL < 130 mg/dL) and optimal control (A1c < 7%, BP < 130/80 mmHg, LDL < 100 mg/dL). Statistical significance was set at P < .008 (Bonferroni’s correction). Findings Although the proportion of patients with reasonable A1c control worsened by increasing degree of rurality, the differences were not statistically significant (urban 90%, large rural 88%, small rural 85%, isolated rural 83%; P = .10); mean A1c values also increased by degree of rurality, although not statistically significant (urban 7.2 [SD 1.6], large rural 7.3 [SD 1.7], small rural 7.5 [SD1.8], isolated rural 7.5 [SD1.9]; P = .16). We observed no differences between degree of rural and reasonable BP or LDL control (P = .42, P = .23, respectively) or optimal A1c or BP control (P = .52, P = .65, respectively). Optimal and mean LDL values worsened as rurality increased (P = .08, P = .029, respectively). Conclusion In patients with diabetes who seek care in the rural Southern US, we observed no relationship between degree of rurality of patients’ residence and traditional measures of quality of care. Further examination of the trends and explanatory factors for relative worsening of metabolic control by increasing degree of rurality is warranted.

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