Related Experiment Video
Updated: May 9, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
[Case-crossover studies. Research into risk factors with the patient as his or her own control]
Rachel E J Roach1, Bob Siegerink, Willem M Lijfering
1Leids Universitair Medisch Centrum, afd. Klinische Epidemiologie, Leiden, the Netherlands.
Abstract:
The case-crossover study is a relatively unknown way of identifying short-term transient risk factors for acute-onset diseases. In patients with the disease of interest, the frequency of exposure to a certain risk factor is compared between two time periods. If the exposure is more common in the period directly preceding disease onset than in an earlier period, the control period, it is likely that the exposure contributes to the development of the disease. The problem of confounding is minimized in case-crossover studies since the patient serves as his or her own control. A potential disadvantage is that sufficient biological knowledge of the clinical picture is needed to provide a good estimate of the risk period. As administrative databases are now commonly used for research purposes, future use of case-crossover methods is likely to increase. We illustrate the case-crossover study with the question of whether antibiotic use increases the risk of unwanted pregnancy in women who use the contraceptive pill.
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Crossover Experiments
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
Case Studies
Longitudinal Research
Causality in Epidemiology
Introduction to Epidemiology