Saranath

Thanks all for the fruitful discussion.

Thanks everyone for sharing your experience. Many of you have used Google form. Google form is a good tool for collect data. However, for a real clinical study, the google form may not fit the standard requirements.

Great! Yes, edit check programming would be very helpful to prevent human error in data input. Data backup on monthly basis seems to be too long- but it would depend on the activities and amount of data input into the system.

It’s cool that your work has remote data backup to the CDC server. I’m sure the data security will be very strong.

Yes. HIS, HosXP are good examples of clinical database. Because these software are intended to collect large number of data from routine services. The database design would play an important role in this case.

There are many software available. There is no right or wrong when choosing the software. But the selected one should fit with the requirements of your work.

You will learn another CDMS- OpenClinica, which has functions similar to REDCap. Both programs are opensource, you can use them for free- but require some setup steps.

Thanks for sharing. Collecting data at a large scale, such as public health surveillance is always a challenge. Particularly when collecting data originally collected for a routine service.

It’s good that you monitor the performance of data collection and tried to solve the problems during the implementation.

Keeping the data in a locked computer is acceptable (although it might not be the best standard practice). As it might be a risk of data loss (data integrity)— you may consider backing up the data in other sources as well.

Yes! Data security is an important step in data management process. The data should be securely kept even after the study was closed.

Thanks! Getting feedback from the users during study implementation is also crucial. This should potentially help to improve the data collection process and data quality of the project.

Thanks for sharing! Sometimes, we also need periodically training over the study period. You should continue monitor data quality during data collection period. If there are some sites or interviewers that show poor data quality, the refresh training should be required.

Thanks for pointing this issue out. In data management process, we should have user acceptant test (UAT) that let the end user to test the system before launching. Many times, this step is ignored, but as the end-users this should be a must-do process.

I totally agree that data validation process is such a time-consuming work. A good system design would help to reduce the time- and workload.

Qualitative data collection methods require well-experienced interviewers and moderators to acquire data from participants. The questionnaire design is also a heart of the questionnaire survey that it must be tested before use. Most of the time, even the questionnaire was well tested, there are still many problems occurred during the implementation.

Wow! You must get a lots of work to do. Implementing an online survey form to a large scale is such a challenge. I’m sure you will do better in the next project if you can design the data management for the project. Are you working at the Department of Livestock now?

Using and handling secondary data are not easy, especially the data from 43 files. Integrity of the information is very important as these data will be used to support prevention and control programs.

Great! You got lots of lessons learned from the project. I’m sure that your future project would be able to collect qualitied data with less workload.

Thanks! A well-planned data management process would definitely make the researcher work on the project easily.