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REVIEW ARTICLE
Year : 2017  |  Volume : 1  |  Issue : 1  |  Page : 10-14

How i do it: A practical database management system to assist clinical research teams with data collection, organization, and reporting


1 Department of Radiology, King Faisal Specialist Hospital and Research Center, Body Interventional Unit, Riyadh, Kingdom of Saudi Arabia
2 King Faisal Specialist Hospital and Research Center, Body Interventional Unit, Riyadh, Kingdom of Saudi Arabia

Correspondence Address:
Amr Maged Elsaadany
Department of Radiology, King Faisal Specialist Hospital and Research Center, Body Interventional Unit, P.O. Box 3354, Riyadh 11211
Kingdom of Saudi Arabia
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2542-7075.199567

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With the growing amount of research projects in the field of interventional radiology, storing and organizing the patients' data and information effectively is becoming more difficult. Existing hospital electronic medical record and archiving systems store patient information in the form of reports which put the physicians and researchers in a situation where they have to use time-consuming manual search through reports for suitable patients for different clinical researches. Spreadsheet programs such as Microsoft Excel® (Microsoft, Washington, USA) are often used as a data storage, which has limitations in both organization and the quality of the data. Higher risk of incorrect data entry and introducing duplicates are associated with data input and analysis without a database system. Furthermore, selection, as well as calculation of data, is time-consuming. This article aims to provide interventionists with an efficient data collection tool optimized for interventional oncology clinical research. The implementation of the current database and interface allows a much faster and more detailed retrospective analysis of patient cohorts. The database management system with an interface is a very time-efficient and robust tool that provides a significant edge over the manual retrieval of patient records by filtering data and assisting statistical analysis in a study-relevant fashion.


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