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One of the most common features in clinical trials is missing data particularly when follow-up is over a long period of time. What is the best approach in handling it without biasing results with regards to both ITT and PP analysis?
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Dear All,
It is an important issue. I would want to agree with Ednah that tools like PDAs could be employed to help.
This is the challenge of trials and proactive management is called for.A clear data management plan should address issues at various points:
1. At design: The documentation and systems employed should deliberately be tailored to collect only relevant data onto CRF. Training should therefore ensure that there are no blank spaces on completed forms; so provide fields for "missing data" already to avoid queries.
2. During implementation, the data manager and field teams should proactively manage the study rather than react to gaps and missing information. So schedule the visits,ahead of time and immediately follow up any missing information with the field teams.
3. Systematic checks: Data managers should be able to understand their system fully, probe for systematic errors and take corrective actions. The problem is that managers generally tend to be reactive to problems rather than go ahead to avoid them.
4. Some times it might be that more/or better qualified staff are needed in the data management team.Regards,
Roma
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I think this is a very important issue and an experience that I too share. I do not know the answer but just wanted to support your request and I am interested to see whether we can get some answers here. Thanking you for this important point.
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I concur with you.It is the biggest headache any data manager could have.i have programmed PDA's giving the next visit date then merged the collected data in an excel sheet to be able to know the participants due for next followup and the delays to allow for followup before they get out of window.this has reduced my burden by about 80%