Spreadsheets have become part of our daily lives now. Take Excel, for example, a common spreadsheet utilized daily by many from schools, workplace and even in our homes. From personal budgeting to complex calculations and large data-driven business reports, Excel enables us to perform various day to day tasks. For the lion's share of us, Excel is a familiar tool and almost ubiquitous on any Windows computer. Other widely used data collection tools include online surveys like SurveyMonkey and Google Forms. All things considered, these are not made for electronic case report forms (CRFs) building and clinical data collection. In spite of the innovative advances in software solutions, spreadsheets and online surveys when doing data collection for clinical research.
TL;DR: Never use Excel for data collection. Google Forms or Survey Monkey are OK for anonymous cross-sectional studies, for anything else, go with a validated EDC.
In this blog, we summarize the main risks of these platforms and why we recommend, clinical researchers always to use validated Electronic Data Capture (EDC) systems.
In our previous blog post, the importance of clinical studies to comply with Good Clinical Practice is explained in detail. One of the core components of a validated EDC is its ability to assure research data has not been tampered or unintentionally modified. General survey tools do not create audit trails or a revision history of data creation and changes. Although researchers can get close to achieving this by creating subversions of their data files, this is prone to mistake.
With EDC, this is conceivable with audit trails. Rather than depending on uncertain measures, researchers can benefit from choosing a verified tool like Teamscope that complies with the set regulations. Viewing audit trails on Teamscope is simple and straightforward. A study administrator at any moment can see all the changes to research data and electronic Case Report Forms (eCRFs).
Spreadsheets have constrained permission controls with regards to accessing data for multiple users. A researcher can assign a password to open an Excel workbook and also a password to modify the data in it, but there are important considerations:
This absence of protection can prompt data exposure and manipulation. Since it is not possible to create granular permissions on Excel, this makes it difficult to control who accesses the data. Also, since you can’t track audit trails, there’s no way to know when or who accessed the data.
Validated EDCs like Teamscope support permissions-based access management. This feature allows a principal investigator to grant limited access and rights to team members within a clinical study.
On Teamscope users have a unique username and password to access the platform and their sessions time out after a limited time of inactivity. Data-at-rest and in-transit are always encrypted and backed up on redundant servers.
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One of the main challenges that collaborative clinical studies face is how to efficiently and safely centralize their data. At a specific moment, the data from multiple sites has to be centralized into one database. Often various locations in a study will use different systems for data collection; some may use Excel, others Microsoft Access, while some of the data may be collected with paper CRFs. The use of different data collection methods creates data fragmentation and a logistical overhead for the team responsible for centralizing and conducting statistical analysis of the data.
Data fragmentation is entirely avoided with a cloud-based Electronic Data Capture system.
With Teamscope, data is centralized from the get-go, and everyone is on the same page. Whenever a team member adds a data entry or modifies previously stored record, that change synchronizes across all authorized team members. This way valuable time is saved, data is centralized, and collaboration is made easy.
Study types can be broadly divided into two categories: cross-sectional and longitudinal. In cross-sectional studies since there is no need to follow-up on study subjects, they tend to be anonymous. Longitudinal research, on the other hand, subjects are surveyed across time. Ensuring that the data is accurately associated with the corresponding study subject is paramount in longitudinal analysis.
General survey tools like SurveyMonkey and Google Forms may get the job done in studies where no identifiable data is collected. However, these tools are not designed to create cases thus making it complicated to associate multiple entries with the same study subject. A researcher may be able to hack their way around this, but it will be a headache and not fail-proof.
EDCs like Teamscope make longitudinal research possible through a functionality called case management. Cases in a clinical study are subjects or patients, that move along defined stages. On each step the researchers can collect data from those patients, creating thus a longitudinal history of those patients during the clinical trial.
Excel is inexpensive and easy to use. We often hear from researchers that they are using it for data collection in clinical research. Another widely used option for data collection are online surveying tools like SurveyMonkey or Google Forms; researchers prefer them over paper-based forms because they are inexpensive and seem to be technically capable.
Although these tools may seem technically capable, researchers must understand the risks they involve. Data integrity is essential, and for this to be achieved, researchers should be able to view the revision history of any data created or changed. Besides, all data should be protected from unauthorized parties to prevent data exposure and manipulation. Lastly, ensuring that there are no mistakes in associating data from study subjects across time is paramount.
Electronic Data Capture systems are specially designed for the collection of research data, optimizing your clinical study workflow and mitigating data exposure and integrity risks.
Robust tools like Teamscope enable researchers to safely aggregate data, create ad-hoc reports and collaborate in real time. Researchers can collect and store accurate research data, leading them to faster and reliable results. With the accessibility of real-time data, researchers benefit from quicker insights, easier collaboration across sites and shorter study time.
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