30 We will use advanced survey design techniques that maximise the potential for trading between attributes to enhance the data quality.
In general, there is a need to strike a balance between flexibility and predictability in the data quality evaluation process; it will always include an element of expert judgment, but it is also, in our view, important to continuously seek to increase the predictability and transparency of this process.
155 (Annex I), implementing the European Union Directive 2008/50/EC, ratios between measured and estimated data must be between ±50% in order to consider the data quality as acceptable [ 64, 67].
The study found that the data quality was stable between the two coding systems, although the validity differed between coding versions for some clinical conditions.
Figures 2 and 3 demonstrate the positive/incomplete correlations between these data quality indicators separately.
This paper introduces a topic which is of growing interest in the traffic control and management community, namely the relation between traffic data quality and the efficiency of traffic management.
They raise several important positive points regarding the flexibility of continuous surveys, the use of time-series analyses to evaluate real-world programs in which public health activities cannot be neatly grouped into intervention and control areas, and the ability of I-Q to address the gap between data, quality, and action at the national and local level.
In order further to understand the relationship between data quality and performance of the standard dispersal-based algorithm, we compared the performance of the standard dispersal-based algorithm with the results of hand-identified fixations.
The second major reason that the authors use to explain the discrepancy between data quality and predictive ability is lack of definitions and recording of operation-specific outcomes.
However, additional studies with larger sample sizes are needed to further investigate the value of the PRISM instruments in exploring the linkages between RHIS data quality and use, and health systems performance.
