PIL related projects

Funded by SURF grant

Development and validation of de-identification algorithm for clinical narratives 

In this project led by the Department of Research Data Management of Amsterdam UMC, we contribute by providing our expertise on de-identification tooling and will organise the annotation process of clinical narratives by medical experts as part of the validation of the developed de-identification algorithm. Such algorithm is needed to remove mentions of directly identifying information about patients from the clinical narratives. Directly identifying information includes for example: surnames, birth dates, social security numbers or home addresses. This directly identifying information must be removed in order to preserve patient privacy while reusing clinical narratives for research. 

Involved team members : Joanna Klopotowska, Ameen Abu-Hanna, Hemmik Leopold and Martijn Schut

Evaluation of the quality of antibiotics prescribing by reusing real-world data from EHRs of ICU patients

In this project led by dr. Jeroen Schouten (intensive care physician at Radboud UMC), we contribute by providing our expertise on real-world data and real-world data analytics. In this project, the SIMPLIFY database (containing real-world data from electronic hospital records (EHRs) of ICU patients) and data from the National Intensive Care Registry are used to gain insight into the extent and quality of antibiotics prescribing in Dutch ICU patients.

Involved team members: Joanna Klopotowska, Izak Yasrebi-de Kom, Nicolette de Keizer and Dave Dongelmans

Investigating food-drug interactions prevalence and types in hospitalised patients

In this project led by dr. Pauline Bollen (hospital pharmacist at Gelderse Vallei Hospital), we contribute by providing our expertise on reusing real-world data from electronic hospital records, data analytics and computerised decision support systems. Concomitant intake of food and medications may increase or decrease drug absorption and subsequently affect clinical health outcomes.

 Involved team members: Joanna Klopotowska