Data that is collected for both clinical and research purposes must be handled with care and according to the standards associated with each process. Both methods can result in the improvement of life for humans, and are supported by a host of professionals with a variety of specialties. However, clinical and research data ultimately serve different purposes. Clinical information is directly and (ideally) immediately applied to the consideration of treatment options for patients, while research data serves to test scientific hypotheses that can then be published. Accordingly, each type of data requires a different approach to handling.
Experimental research is governed by the scientific method, requiring a lengthy process including stages such as design, testing, calculations, and interpretation (Shoshani & Rotem, 2009). Research methods demand that certain assumptions are met by the data set, usually involving sample size and normality of the distribution. The information may then be analyzed using a variety of statistics, which in turn determine the effect of the independent variable(s). If a significant (mathematically) finding is observed, then the results may be interpreted using associated theories, followed by a written report, and finally be submitted for potential publication (while no significant result usually means the data and study are discarded).
In contrast, clinical data is most desirably integrated into the healthcare process as soon as the data is available. There are structural guidelines for handling clinical information (Richesson & Nadkarni, 2011) but they do not stand up to the rigorous demands of the scientific method. Most design considerations are given to the accuracy of measurement tools (lab machines, monitoring devices, etc.) and the ability to quickly analyze the obtained data. Once obtained from measurement, the information does not typically need to be further analyzed other than determining what it means regarding the patient’s health.
Richesson, R. L., & Nadkarni, P. (2011). Data standards for clinical research data collection forms: current status and challenges. Journal of the American Medical Informatics Association, 18(3), 341-346.
Shoshani, A., & Rotem, D. (2009). Scientific Data Management: Challenges, Existing Technology, and Deployment (Vol. 3). Chapman & Hall/CRC.