4 things to think about for data management

As part of the Emas Pharma series ‘4 things to think about’, Senior Data Manager Tracie Lavery outlines key areas that data managers working with or within a CRO environment should consider.

1. It is all about the data

The most important thing about a clinical trial is the data. As a data manager it is our responsibility to ensure the collection, integration and availability of the data is high-quality, reliable, and statistically sound for any end stage reporting or Clinical Study Report (CSR). Understanding the data you are collecting is also key as this ensures that the data required for the trial is being collected. Primary and secondary endpoints outlined in the protocol happen to be the most important pieces of the data as without them you are unable to prove the trial is successful. BIG Data: Now that we collect so much data electronically we can analyse more. This is starting to effect the planning process now too as we start to think more about linking data from all sorts of source’s from databases, spreadsheets, media and even images.

2. Standards

A significant cost and time saving aspect of data management is the implementation of standard forms and processes. By standardising or using CDISC standards in the planning, collection and analysis in your study design means that each phase or cohort uses the same standard data content throughout the whole research process. Standard data is typically demographics, medical history, concomitant medications, adverse events, etc. and uses the SDTM naming conventions which make is easier to understand when producing datasets. Over the years standard procedures/items used in most therapy areas have also created a base line when designing the study.

3. Metrics

One thing I have learnt over the years is that study metrics are needed for the study team to gather a picture of where the study is. As most of the data is now collected on Electronic Data Capture (EDC) systems it is so easy to provide metrics such as number of pages entered, pages missing, queries outstanding and most importantly number of patients enrolled vs those still in treatment. Some systems now have dashboards built in to show status of the study when the user logs in.

4. Technology

As I mentioned above with the push for big data analysis new technology needs to be able to provide this link. Databases are becoming ‘Cloud based’. Devices such as smart phones are being used by patients to upload their responses. Apps are being created to see study metrics at any time. This makes for very exciting times as I do love a bit of technology.

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About the Author

Tracie Lavery is a Senior Data Manager at Emas Pharma. Tracie has over 20 years’ experience working within the pharmaceutical industry. Tracie is experienced in a number of dierent EDC and database systems such as Rave, Inform and Oracle and more recently Trial Master and eClincial OS.

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