Secondary Data Analysis Tutorial

The Journal of General Internal Medicine has published a very nice introduction and tutorial on Secondary Data Analysis. It specifically mentions the SGIM Compendium of Datasets which is referenced on this blog's homepage on the right under "Handy Resources for Doing CTS."

Conducting High-Value Secondary Dataset Analysis: An Introductory Guide and Resources

Alexander K. Smith, John Z. Ayanian, Kenneth E. Covinsky, Bruce E. Landon, Ellen P. McCarthy, Christina C. Wee and Michael A. Steinman

Abstract

Secondary analyses of large datasets provide a mechanism for researchers to address high impact questions that would otherwise be prohibitively expensive and time-consuming to study. This paper presents a guide to assist investigators interested in conducting secondary data analysis, including advice on the process of successful secondary data analysis as well as a brief summary of high-value datasets and online resources for researchers, including the SGIM dataset compendium (www.sgim.org/go/datasets). The same basic research principles that apply to primary data analysis apply to secondary data analysis, including the development of a clear and clinically relevant research question, study sample, appropriate measures, and a thoughtful analytic approach. A real-world case description illustrates key steps: (1) define your research topic and question; (2) select a dataset; (3) get to know your dataset; and (4) structure your analysis and presentation of findings in a way that is clinically meaningful. Secondary dataset analysis is a well-established methodology. Secondary analysis is particularly valuable for junior investigators, who have limited time and resources to demonstrate expertise and productivity.