PubMed · 15500224
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Mike Hayward. Facing danger.. https://doi.org/10.7748/ns.19.3.20.s33
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BACKGROUND AND PURPOSE: Computer-assisted teaching and learning tools offer new opportunities for improving education and training of medical professionals. CAMPUS represents a software for computer-based, problem-oriented learning. It is a case-based training system which provides the patient's history within a highly realistic, multimedia format. Thus, the interactive design is expected to challenge, test and improve the medical knowledge and the diagnostic skills of the students. The objective of the present study was to introduce CAMPUS as a computer-based learning tool and to present preliminary results with regard to acceptance and user-friendliness. METHODS: CAMPUS was evaluated by 52 students regarding quality and experienced learning success. A tutorial was conducted within separate, small-numbered groups of students, each working on one learning case. The virtual case started with a summary of the patient's leading symptoms. The students independently took the patient history and carried out the physical examination. Then, they were asked to suggest differential diagnoses, refer the patient to appropriate diagnostic examinations and were encouraged to choose adequate therapeutic strategies. Subsequently, the quality of CAMPUS and the subjective learning success were evaluated with a standardized questionnaire. RESULTS: Nearly all students described the user interface as visually attractive (51/52) and clearly structured (52/52). In particular, the students found the use of videos to be advantageous. A marked learning success was described by most students (46/52) and all students considered learning with CAMPUS to be effective. CONCLUSION: CAMPUS offers an innovative training program to improve medical education and to enhance conventional teaching methods efficiently.
BACKGROUND: Case definitions have been recognized to be important elements of public health surveillance systems. They are to assure comparability and consistency of surveillance data and have crucial impact on the sensitivity and the positive predictive value of a surveillance system. The reliability of case definitions has rarely been investigated systematically. METHODS: We conducted a Round-Robin test by asking all 425 local health departments (LHD) and the 16 state health departments (SHD) in Germany to classify a selection of 68 case examples using case definitions. By multivariate analysis we investigated factors linked to classification agreement with a gold standard, which was defined by an expert panel. RESULTS: A total of 7870 classifications were done by 396 LHD (93%) and all SHD. Reporting sensitivity was 90.0%, positive predictive value 76.6%. Polio case examples had the lowest reporting precision, salmonellosis case examples the highest (OR = 0.008; CI: 0.005-0.013). Case definitions with a check-list format of clinical criteria resulted in higher reporting precision than case definitions with a narrative description (OR = 3.08; CI: 2.47-3.83). Reporting precision was higher among SHD compared to LHD (OR = 1.52; CI: 1.14-2.02). CONCLUSION: Our findings led to a systematic revision of the German case definitions and build the basis for general recommendations for the creation of case definitions. These include, among others, that testable yes/no criteria in a check-list format is likely to improve reliability, and that software used for data transmission should be designed in strict accordance with the case definitions. The findings of this study are largely applicable to case definitions in many other countries or international networks as they share the same structural and editorial characteristics of the case definitions evaluated in this study before their revision.
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