You could not recruit enough patients in a single-center study. Or the external validity of your findings is being questioned: "Are these results specific only to your institution?" Multicenter studies solve these problems, but they are far more complex than single-center studies in terms of planning and coordination.
Advantages of a Multicenter Study
Larger sample: In rare diseases or low-prevalence conditions, a single center may not be able to recruit enough patients. Multiple centers naturally solve this problem.
External validity: Findings obtained from different patient populations, different clinicians, and different institutional practices are more generalizable.
Publication strength: Multicenter studies signal higher methodological quality to journals.
For AI and data studies: For the external validation of machine learning models, independent data from different centers is mandatory.
The Planning Phase: The Most Critical Step
In multicenter studies, the biggest mistakes are made during the planning phase. Before starting data collection, the following questions should be answered:
Center selection: Which institutions will be included? A similar patient population, or is diversity deliberately targeted? Whether the centers have sufficient patient volume should be determined through preliminary assessment.
Coordinator assignment: Who will be the local research coordinator at each center? How will communication be conducted between central coordination (the sponsor institution) and local coordination?
Funding and incentives: What will be provided in exchange for center participation? Authorship in publications, or financial incentives?
Data Standardization: The Biggest Technical Challenge
For data collected at different centers to be comparable, standardization is mandatory.
Common case report form (CRF): It is essential that all centers use the same form. Every field must be defined; for example, which criterion is used for "hypertension"? Diagnosis alone, or medication use?
Training: Having local researchers receive common training increases consistency. Video training materials and a written protocol guide should be prepared.
Data quality control: The central data manager should periodically review the data from each center. Outliers and inconsistencies should be detected early.
Electronic data capture system (EDC): REDCap (Research Electronic Data Capture) is a free platform widely used for multicenter studies. Each center enters data through its own interface, and the data are merged in a central database.
The Ethics Approval Process
In multicenter studies, the ethics approval process may need to be carried out separately for each center, and this process can be long and complex.
Coordinating institution (sponsor): The ethics committee approval of the main institution that designed and conducts the study is obtained. This approval may serve as a reference for the other centers.
Local approvals: In Turkey, each institution has its own ethics committee. While some institutions consider the coordinating institution's approval sufficient, others require a separate application. Each institution's policy should be clarified in advance.
KVKK and data sharing agreement: For sharing patient data between centers, an inter-institutional data processing agreement is mandatory.
Statistical Analysis Plan
In multicenter studies, statistical analysis involves different requirements than single-center studies.
Center effect: The results of different centers may differ systematically. This effect should be controlled as a covariate in a multivariate model, or a mixed-effects model should be used.
Heterogeneity analysis: Heterogeneity between centers should be investigated. Is the effect seen at one center also seen at the others?
Sample size: The expected number of patients for each center and the total power analysis should be performed during the planning phase. Centers may not contribute equally, and the analysis plan should be prepared taking this into account.
Data Management with REDCap
REDCap (redcap.org) is a secure web-based data collection platform designed for multicenter clinical studies. Many university hospitals in Turkey hold a REDCap license.
Core features:
- Role-based access control (each center enters only its own data)
- Automatic data validation and alert system
- Audit trail (who changed what and when is recorded)
- KVKK-compliant data storage
- Connection to statistical software via API
To set up multicenter research infrastructure, request a free consultation.
Where Do People Get Stuck Most in This Analysis?
- Each center uses a different format, and data merging is inconsistent and time-consuming.
- Local ethics committee approvals have not come through for months, and some centers request different requirements.
- You do not know how to control for the center effect in the statistical model.