Once a study’s design has been completed and the foundation is in place, the building blocks—data, need to come in next. Gathering high quality data is essential to create valid, reproducible results, and to make informed decisions.
We know how important the quality of data is for the rest of your study. Our holistic approach to study management helps to ensure the collection process aligns seamlessly with the protocol’s established rules and is optimized for subsequent analysis.
Whether it is an online survey including standardized or complicated in-depth interviews demanding nuanced responses, the method of collection has a huge impact on the quality of the data. Surveys, online or on paper, are always thoroughly (pilot) tested, and interviewers receive professional training.
We employ data monitoring practices throughout the data collection phase, ensuring the accuracy of the data being collected. This includes real-time oversight to detect and address any potential issues, and to check whether all previously established rules are being followed and quotas are met.
During data collection, incoming data is undergoing regular quality checks, with deviations from the pre-determined rules (e.g. an interview having a max length of 10 minutes long) being flagged. In addition, we review audio recordings of interviewers so that we can optimize our interview techniques and language use, as well as make other quality improvements.
After all data have been collected, we clean the data set by identifying participants with excessive missing values, data entry errors, inconsistencies and outliers in order to minimize bias and improve accuracy of data analysis. After this step, numbers are ready to be crunched.
We (co-)handled the data collection of multiple observational and real-world evidence studies, collecting both quantitative and qualitative data.
A digital observational population study in 8 countries among the general population, to document EQ-5D-5L and HUI3 population norms, and to conduct psychometric analyses on EQ-5D bolt-on instruments (with support from EuroQoL).
A digital study among patients suffering from Myasthenia Gravis, in collaboration with Vitaccess Ltd to document the HRQoL, utilities, productivity losses and medical resource utilization of patients.
Clinical data collection among patients and their neurologist to validate the proxy versus self-measurement of the main MG clinical outcome measure MG-ADL.
Observational data collection among patients and caregivers to document the burden that caregivers experience and whether this burden is associated with disease severity.