Run-time | DAQCORD

Study phase:

Dimension:

Individual data elements should be checked for missingness. This should be done against pre-specified skip-logic / missingness masks. This should be performed throughout the study data acquisition period to give accurate ‘real time’ feedback on completion status.

Examples

1: Rules in place to check whether the apparently missing element should be completed or not for a particular study stratum or time point.

Study phase:

Run-time

Dimension:

Completeness

There is centralized monitoring of the completeness and consistency of information during data collection.

Study phase:

Run-time

Dimension:

Representation

Automated variable transformations are documented and tested before implementation and if modified.

Examples

1: For example, testing is carried out if fields such as ‘years of education’ and ‘level of education’ are automatically combined into a new variable summarising educational status.

2: Coding is tested on a subset of data, ideally by multiple members of the study team.

3: There is a centralised log / version management of all transformations used.

Study phase:

Run-time

Dimension:

Completeness

Proxy responses for factual questions (such as employment status) are allowed in order to maximize completeness.

Examples

1: Protocol is designed to allow for surrogate to respond to selected questions when patient is too impaired to respond. CRF indicates when surrogate is responding.