In our work we are highly involved in the Observational Health Data Sciences and Informatics (OHDSI) community that builds analytical pipelines on top of the OMOP Common Data Model (OMOP-CDM) to generate reliable evidence to improve patient health. For example, we are co-leading the patient-level prediction working group in OHDSI that develops a framework for patient-level prediction on top of the OMOP-CDM together with Jenna Reps from Janssen Research & Development:
www.github.com/OHDSI/PatientLevelPrediction
- Jenna M Reps, Martijn J Schuemie, Marc A Suchard, Patrick B Ryan, Peter R Rijnbeek; Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data, Journal of the American Medical Informatics Association, Volume 25, Issue 8, 1 August 2018, Pages 969–975, https://doi.org/10.1093/jamia/ocy032
- Jenna M Reps, Ross D Williams, Seng C You, Thomas Falconer, ... Peter R Rijnbeek; Feasibility and evaluation of a large-scale external validation approach for patient-level prediction in an international data network: validation of models predicting stroke in female patients newly diagnosed with atrial fibrillation, BMC Medical Research Methodology, Volume 20, Issue 1, 6 May 2020, Pages 1-10, https://doi.org/10.1186/s12874-020-00991-3
Ongoing Research Topics
Our group is currently working on many topics, including:
- Heterogeneity of Treatment Effect (Alexandros Rekkas)
- Learning curve analyses to assess bias and variance and sample size requirements (Henrik John)
- Predictive modelling in dementia (Henrik John)
- Explainable artificial intelligence to improve adoption of models in clinical practice (Aniek Markus)
- Treatment pattern analysis in asthma patients (Aniek Markus)
- Use of unstructured text data to improve patient-level prediction models (Tom Seinen)
- Class imbalance problems (Cynthia Yang)
- Review of prediction literature (Cynthia Yang)
- Disease trajectories (Solomon Ioannou)
- Frequent pattern mining (Solomon Ioannou)
- Predictive modelling in COVID-19 (Ross Williams, Aniek Markus)
- Ensemble training (Ross Williams)
- Large-scale external validation of patient-level prediction models (Ross Williams)
- Clinical characterisation methods and visualisation (Anthony Sena)
- Clinical characterisation in COVID-19 patients (Anthony Sena)
- Negative control selection methods (Erica Voss)
- ETL process development (Erica Voss)
- Analysis of European summary of product characteristics (Luis Pinheiro)
- ETL quality control mechanism (Clair Blacketer)
- Mapping of drug coding systems (Marcel de Wilde, Mees Mosseveld)
Furthermore, we are currently involved in many clinical studies to improve patient care within OHDSI and EHDEN.
For a full list of our pre-prints and peer-reviewed publications see here.
In the Showcase below you can find a selection of posters from our group.
