In: Nursing
Minimizing missing data: Here are some types of missing data that you might encounter when implementing a clinical trial. Pick two, and briefly describe a study procedure you could use to minimize the chance of that type of missing data occurring.
1. A participant does not show up for a study visit.
2. A participant does not bring important information (for example, a list of current medications or a pain diary that was supposed to be filled out).
3. Inadequate physical exam done by study staff (for example, pulse not taken).
4. Lab mishap (for example, serum sample lost by lab or in transit to lab).
5. Careless form completion by study staff (for example, a few questions not answered).
6. Careless data entry (for example, the data collection form recorded a diastolic blood pressure of 84, but the study database shows no value was recorded).
7. Participant has an in-office survey to fill out but doesn't complete all questions.
MISSING DATA:-
-it is defined as the data value that is not stored for a variable
in the observation of interest.
-This problem of missing data is very common in all research and
can have a significant effect on the conclusions that can be drawn
from the data.
CHOOSED VARIABLES ARE-
1. A participant does not show up for a study visit.
2. A participant does not bring important information.
HANDLING MISSING DATA:-
1. Study design should limit the collection of data to those who
are participating in the study.
- This can be achieved by minimizing the number of follow-up
visits, collecting only the essential information at each visit,
and developing the userfriendly case-report forms.
2. A detailed documentation of the study should be developed in
the form of the manual of operations before the beginning of the
clinical research.
3. A training should be conducted to instruct all personnel related
to the study on all aspects of the study before the start of the
participant enrollment.
4. A small study should be performed before the start of the main
trial, it may help to identify the unexpected problems.