SHE Consulting

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Data Collection

Value Collecting

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.

SHE employee explaining the data collection process
SHE employees talking about study design


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.

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Our Data Collection Process

Optimizing the Collection

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.

Monitoring the Data

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.

Controlling the Quality

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.

Cleaning the Data Set

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).


National valuation study for a youth value set for Belgium: collection of TTO and DCE data among the Belgian general population, with support from the EuroQoL and the KCE in Belgium.


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.

MG-ADL Proxy study

Clinical data collection among patients and their neurologist to validate the proxy versus self-measurement of the main MG clinical outcome measure MG-ADL.

Caregiver Burden - MG study

Observational data collection among patients and caregivers to document the burden that caregivers experience and whether this burden is associated with disease severity.

Other Services

Economic Modelling
Gain valuable evidence-based knowledge through our budget impact, cost-minimization, and cost-effectiveness modeling techniques in Excel and in R
Empower your staff with a course on health economics, on statistics or on the importance of including PROMs from one of our senior health economists or statisticians
Curious about our past endeavors? Dive into some of our academic writing