Tanyawat Saisongcroh

Your dashboard is nice. It is simple and very informative.I like the color and choice of data visualization and its arrangement in the dashboard. The “compact number” style could be used for the large number of cases.

Here is my dashboard

Hi Zarni, sorry for late reply.
You can now download full article from BHI platform course of 546/week5/4.3 Seminar3. or I will send pdf via line account.

Best,
Tanyawat

https://snipboard.io/lIwRhT.jpg

This is Covid19 Dashboard of City of El Paso,Texas,USA
Main link resource : https://www.epstrong.org/

Nice work. Your CRF is very detailed. All the important variables and values are included and relatively grouped. The pattern, font size and format work very well.

I would like to point out few issues that could be adjusted,
– Demographic; Race/Ethnic could be added. Since study sites are in Bangkok and Chiangmai which are quite diversity…[Read more]

One of the studies that I experienced, it was retrospective study that collect the data from EHR. We used a web application called REDCap to capture the data and create database. eCRF was developed there and assigned access to specific data collectors (me and another colleague). This REDCap has a built-in audit trail that logs all user activity,…[Read more]

I couldn’t agree more. Imagine that if we have to combine several silo dataset, that will be a lot of work and very confusing and also increasing the error.

Note that if this study conduct in Thailand, people may familiar with year in B.E. (Buddhist Era), however, some participants might be foreigners, so, I think for the year should be in A.D.

Date of Birth variable;
Date of birth here might be unnecessary and it is also one of the indirect identifiable data. We could check the participants’ ages in the screening visit whether they are in 18 to 60 years old or not. Also, we can just put “year of birth (yyyy)” instead of full date of birth.

With the data standards in clinical research, the data set will be in universal language for all the researchers and associated staffs. All members can see and understand everything in that data set in the same way.

Thanks for sharing. As you mentioned about enforcing database access control as the study grows, this is so important point of concern, in reality, we might get loose in authentication over time especially in long-period study.

Thanks for sharing an experience in real clinical trial. Self-administered diary especially in this study, about AEs is kind of open question and there are various symptoms that could happen whether related or not, this might prone to missing data due to too much details and misunderstanding the instruction.

Consider of data management workflow, 60-70% were done, the steps that have not done or incomplete and need improvement;
For the project initiation;
CRF/DMP development/ Edit checks programming; we don’t have a full completion of instruction manual and official DMP. It’s just a final draft use among investigators. We don’t have edit check progr…[Read more]

I would like to share fun experience of data collection from the group projects that I’d joined. Since we had a couple research studies related the pediatric orthopedic diseases and their risks (such as ADHD, obesity, joint hyperlaxity, limb unequal and deformity, Perthes disease) that need information for control group of healthy children s…[Read more]