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Observed time-date values are not admissible according to the allowed time and date ranges.
This indicator checks for violations of admissibility ranges for time and date values.
Based on the study design and conduct such ranges can normally precisely be defined to identify inadmissible codings of processual aspects of a study.
Another point of application may be related to study outcomes, e.g. responses of participants on the year of some treatment.
It is known that data collection in a study started on June 1st 2015 and ended March 16th 2016. Yet, a subset of data appears with dates ranging from April to May 2015. A closer inspection reveals that those dates belong to a pre-study and related observations should not be counted with the main study.
Any violation of an admissibility rule triggers a data cleaning process with the intention to replace the wrong value by the correct one. If this is not possible affected observations should at least be flagged to be adequately handled during analyses.
The higher the number or percentage of inadmissible time-date values, the lower the data quality.
Nonnemacher M, Nasseh D, Stausberg J. Datenqualität in der medizinischen Forschung: Leitlinie zum Adaptiven Datenmanagement in Kohortenstudien und Registern. Berlin: TMF e.V..; 2014.
Stausberg, J., D. Nasseh and M. Nonnemacher (2015). “Measuring data quality: A review of the literature between 2005 and 2013.” Stud Health Technol Inform 210: 712-716.