Spreadsheets are an important, powerful and versatile business tool, and can provide and store valuable information. They can hold as little or as much information as necessary, and without having to rely on IT.
However, it is not optimal for storing sensitive data, like biomarkers, genetic data or health information. New privacy regulation such as GDPR put high demands on software and how they are built and used. Using a spreadsheet for storing sensitive personal data could be considered breaking the law.
There are a few reasons why researchers use Excel:
Excel is popular due to a lack of better alternatives. Current research software is made for clinical trials, However, trials only account for 10% of all clinical research
Microsoft Excel is one of the most widespread software out there, with 750 million users. A lot of people simply know how to use it
Excel is flexible, easy to use and efficient working with big datasets
Excel data workflow does not meet GDPR requirements
If stored on a shared drive, only one researcher can view the file at any given time, not to mention what happens if the files are not closed after use
Spreadsheets lack remote access, causing users to email them selfs a copy of the databases or putting it on USB sticks to be able to work from home. Creating multiple versions of each database
Does not allow for different user roles and data traceability
Modern research has become very collaborative, on-premise spreadsheets lack collaboration features.
People participating in clinical studies allow researchers to handle sensitive personal data about their health and genetics. That’s a big responsibility and the reason why data management should be stricter than ever — Which is why we created Sensivo.
We have reconstructed the spreadsheet so it can securely store sensitive personal data in the cloud. Saving researchers valuable time and helping them stay GPDR compliant.
We had two missions when we were building Sensivo. The software had to be simple, easy to use and improve the speed of data entry. The typical healthcare worker does not need another complicated system that takes up all their time. On the opposite, she should be able to do her data entry work at the fraction of the time it takes in legacy research software. Additionally, it had to be built from the ground up around privacy, security and data protection.