The association between student characteristics and the development of clinical reasoning in a graduate-entry, PBL medical programme

This study sought to assess the extent to which the entry characteristics of students in a graduate-entry medical programme predict the subsequent development of clinical reasoning ability. Subjects comprised 290 students voluntarily recruited from three successive cohorts of the University of Queensland's MBBS Programme. Clinical reasoning was measured once a year over a period of three years using two methods, a set of 10 Clinical Reasoning Problems (CRPs) and the Diagnostic Thinking Inventory (DTI). Data on gender, age at entry into the programme, nature of primary degree, scores on selection criteria (written examination plus interview) and academic performance in the first two years of the programme were recorded for each student, and their association with clinical reasoning skill analysed using univariate and multivariate analysis. Univariate analysis indicated significant associations between CRP score, gender and primary degree with a significant but small association between DTI and interview score. Stage of progression through the programme was also an important predictor of performance on both indicators. Subsequent multivariate analysis suggested that female gender is a positive predictor of CRP score independently of the nature of a subject's primary degree and stage of progression through the programme, although these latter two variables are interdependent. Positive predictors of clinical reasoning skill are stage of progression through the MBBS programme, female gender and interview score. Although the nature of a student's primary degree is important in the early years of the programme, evidence suggests that by graduation differences between students' clinical reasoning skill due to this factor have been resolved.

General Practitioner Antimicrobial Stewardship Programme Study (GAPS): protocol for a cluster randomised controlled trial

Background There is a strong link between antibiotic consumption and the rate of antibiotic resistance. In Australia, the vast majority of antibiotics are prescribed by general practitioners, and the most common indication is for acute respiratory infections. The aim of this study is to assess if implementing a package of integrated, multifaceted interventions reduces antibiotic prescribing for acute respiratory infections in general practice. Methods/design This is a cluster randomised trial comparing two parallel groups of general practitioners in 28 urban general practices in Queensland, Australia: 14 intervention and 14 control practices. The protocol was peer-reviewed by content experts who were nominated by the funding organization. This study evaluates an integrated, multifaceted evidence-based package of interventions implemented over a six month period. The included interventions, which have previously been demonstrated to be effective at reducing antibiotic prescribing for acute respiratory infections, are: delayed prescribing; patient decision aids; communication training; commitment to a practice prescribing policy for antibiotics; patient information leaflet; and near patient testing with C-reactive protein. In addition, two sub-studies are nested in the main study: (1) point prevalence estimation carriage of bacterial upper respiratory pathogens in practice staff and asymptomatic patients; (2) feasibility of direct measures of antibiotic resistance by nose/throat swabbing. The main outcome data are from Australia’s national health insurance scheme, Medicare, which will be accessed after the completion of the intervention phase. They include the number of antibiotic prescriptions and the number of patient visits per general practitioner for periods before and during the intervention. The incidence of antibiotic prescriptions will be modelled using the numbers of patients as the denominator and seasonal and other factors as explanatory variables. Results will compare the change in prescription rates before and during the intervention in the two groups of practices. Semi-structured interviews will be conducted with the general practitioners and practice staff (practice nurse and/or practice manager) from the intervention practices on conclusion of the intervention phase to assess the feasibility and uptake of the interventions. An economic evaluation will be conducted to estimate the costs of implementing the package, and its cost-effectiveness in terms of cost per unit reduction in prescribing. Discussion The results on the effectiveness, cost-effectiveness, acceptability and feasibility of this package of interventions will inform the policy for any national implementation.

Novel application of a discrete choice experiment to identify preferences for a national healthcare-associated infection surveillance programme: A cross-sectional study

Objective: To identify key stakeholder preferences and priorities when considering a national healthcare-associated infection (HAI) surveillance programme through the use of a discrete choice experiment (DCE). Setting: Australia does not have a national HAI surveillance programme. An online web-based DCE was developed and made available to participants in Australia. Participants: A sample of 184 purposively selected healthcare workers based on their senior leadership role in infection prevention in Australia. Primary and secondary outcomes: A DCE requiring respondents to select 1 HAI surveillance programme over another based on 5 different characteristics (or attributes) in repeated hypothetical scenarios. Data were analysed using a mixed logit model to evaluate preferences and identify the relative importance of each attribute. Results: A total of 122 participants completed the survey (response rate 66%) over a 5-week period. Excluding 22 who mismatched a duplicate choice scenario, analysis was conducted on 100 responses. The key findings included: 72% of stakeholders exhibited a preference for a surveillance programme with continuous mandatory core components (mean coefficient 0.640 (p<0.01)), 65% for a standard surveillance protocol where patient-level data are collected on infected and non-infected patients (mean coefficient 0.641 (p<0.01)), and 92% for hospital-level data that are publicly reported on a website and not associated with financial penalties (mean coefficient 1.663 (p<0.01)). Conclusions: The use of the DCE has provided a unique insight to key stakeholder priorities when considering a national HAI surveillance programme. The application of a DCE offers a meaningful method to explore and quantify preferences in this setting.