Creation and use of a database in clinical and translational research.

Often data collection for clinical studies is an afterthought. The results of such an approach are incomplete or confusing data that can, as a worst case, result in scrapping and restarting the entire study. We discuss the planning process for data collection and storage to include encounter form development; data flow and capture; data checking, verification, and validation; advantage of relational databases over spreadsheets; data security; and aspects of a complete data system.

Preparing data for analysis using microsoft Excel.

A critical component essential to good research is the accurate and efficient collection and preparation of data for analysis. Most medical researchers have little or no training in data management, often causing not only excessive time spent cleaning data but also a risk that the data set contains collection or recording errors. The implementation of simple guidelines based on techniques used by professional data management teams will save researchers time and money and result in a data set better suited to answer research questions. Because Microsoft Excel is often used by researchers to collect data, specific techniques that can be implemented in Excel are presented.