Systematically Tabulated Outcomes Research Matrix (STORM): A methodology to generate research hypotheses

Authors

Joseph G. Crompton, University of California-Los Angeles, Los Angeles
Tolulope A. Oyetunji, Howard University College of Medicine, Washington
Elliott R. Haut, Johns Hopkins University School of Medicine, Baltimore
Edward E. Cornwell, Howard University College of Medicine, Washington
Adil H. Haider, Johns Hopkins Bloomberg School of Public Health, BaltimoreFollow

Document Type

Article

Department

General Surgery

Abstract

Background: Here we describe the Systematically Tabulated Outcomes Research Matrix (STORM) method to generate research questions from pre-existing databases with the aim of improving patient outcomes.
Materials and methods: STORM can be applied to a database by tabulating its variables into a matrix of independent variables (y-axis) and dependent variables (x-axis) and then applying each unique pairing of an independent and dependent variable to a patient population to generate potentially meaningful research questions.
Results: To demonstrate this methodology and establish proof-of-principle, STORM was applied on a small scale to the National Trauma Data Bank and generated at least seven clinically meaningful research questions.
Conclusion: When coupled with rigorous clinical judgment, the STORM approach complements the traditional method of hypothesis formation and can be generalized to outcomes research using registry databases across different medical specialties.

Comments

This work was published before the author joined Aga Khan University

Publication (Name of Journal)

Surgery

Recommended Citation

Crompton, J. G., Oyetunji, T. A., Haut, E. R., Cornwell, E. E., Haider, A. H. (2014). Systematically Tabulated Outcomes Research Matrix (STORM): A methodology to generate research hypotheses. Surgery, 155(3), 541-544.
Available at: https://ecommons.aku.edu/pakistan_fhs_mc_surg_gen/295