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In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another).
We can never make assumptions and the data collection needs to be very carefully managed.
Data collection needs to be revised to reflect this approach.
Given the limitations of BMI as an imperfect measure of body fatness, routine anthropometric data collection needs to be extended to develop more informative measures, such as waist circumference in settings where the gold standard tools remain unaffordable.
More specifically, this means that data collection needs to be sensitive to: (a) reducing biases in specific types of data, (b) the specific data sensitivities with regards to vulnerable groups, (c) processing and analytics in order to remain truthful, and (d) being cautious not to perpetuate or increase the vulnerabilities of groups by emphasizing differences.
Epidemiological data collection needs to be updated and the surveillance system needs to be adapted.
Similar(50)
As the current needs for information about health indicators by the Tanzanian Ministry of Health and development partners are mainly focused on routine service data collection, the potential of MTUHA as a routine service data collection tool needs to be highlighted to encourage its use as such.
The benefits of mobile technology, combined with the improvement that mobile phones offer over PDAs in terms of data loss and uploading difficulties, make mobile phones a feasible method of data collection that needs to be further explored.
The benefits of mobile technology, combined with the improvement that mobile phones offer over PDA's in terms of data loss and uploading difficulties, make mobile phones a feasible method of data collection that needs to be further explored.
The high variability in the data collection is directly related to the issues raised with the data collection process, which needs to be streamlined in the field of geosciences, especially because the methods is being used in numerous areas such as earthquake, volcanic and landslides sciences.
Data collection and analysis needs to be improved along with the shortage of skilled workers.
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