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January 2017

Moving from Manual Processes to New Research Methodologies

By | Data Sheets


Spreadsheets are a great tool for collecting data on patients within the context of clinical research, as well as being familiar and free.  But do Spreadsheets truly address the needs of the modern researcher?

Medical innovations and technological breakthroughs are attributed, to a large degree, to the accumulation and use of data.  As the amount of data and its complexity increase, Spreadsheets begins to exhibit shortcomings.  These gaps are filled by Cloud Data Management Systems (CDMA), which bring with them a set of tools that accommodate large data quantities, comply with regulatory constraints and provide useful insight.

When Spreadsheets No Longer Delivers

While Spreadsheets are a great tool for many purposes, they have some significant shortcomings in the area of clinical research – particularly when the amount of data collected increases beyond a few hundred records.

  • Spreadsheets are two-dimensional products, which makes it difficult to create and view depth of data. In contrast, CDMAs are multi-dimensional products that allow you to dig deep into any field to view additional detail through the use of hyperlinks.
  • Researchers that work in groups find it difficult to share spreadsheet databases since spreadsheets, by definition, are not collaborative products. CDMAs are designed for groups of researchers working across the room from each other, or across the globe.  They are housed in a secure Cloud, allowing multiple users to access and modify data at any given time, based on a set of administrator-controlled permissions.
  • Researchers and the organizations in which they live could greatly benefit from the sharing of information between clinical research and care systems. Interoperability between EHR systems, for example, and spreadsheets is non-existent and manual data sharing is extremely cumbersome and time consuming.  Most CDMAs interface clinical care systems that contain APIs and enable the simple migration of data with alerts that identify errors and inconsistancies.
  • Creating a form or questionnaire in a spreadsheet is far more cumbersome and time-consuming than with CDMAs, and ultimately contains a far more limited set of built-in abilities.
  • An important element of clinical research is the integrity of the data collected. Data entered into spreadsheets could contain errors and inconsistencies, which are difficult to identify and correct.  CDMAs often have built-in data validation tools that alert users about errors and inconsistencies.
  • Of critical importance in clinical research is data security. CDMAs typically comply with HIPPA rules, employing a series of security measures around their cloud, and have built data protection mechanisms into their solution such as two-factor access authentication, methods for detecting the potential sharing of PHI, and more.  Spreadsheets offer no security measures beyond password protection.
  • Most spreadsheets enable the use of sophisticated queries but require deep understanding of the product and often of the use of formulas. CDMAs include filtering and query tools that can be performed in seconds or minutes.

These are just a few examples of the shortcomings of spreadsheets for clinical research.  CDMAs, by contrast, are robust solutions that provide researchers with advanced data-entry and data management and insight tools.  It is really like comparing a go-kart with no engine to an S-Class Mercedes Benz!