About INTERPOLAR
Reducing medication problems and improving medication safety
Especially older people often take multiple medications at the same time. This can lead to medication-related problems such as adverse drug interactions and side effects. Consequences can be additional disease patterns and further need for treatment. Medication-related problems are often underestimated and are often the cause of morbidity and mortality in hospitalized patients. In the cross-consortium use case INTERPOLAR, the four medical informatics consortia DIFUTURE, HiGHmed, MIRACUM and SMITH are working together to develop IT solutions to improve medication safety. The project is coordinated by the SMITH Consortium Office.
INTERPOLAR Use Case
Development of IT-supported methods to identify clinically relevant medication-related problems
Harmonization of routine documentation of medication analyses across multiple university hospitals
Investigation of cause–effect relationships of medication-related problems using routine care data
Cross-consortium project of the Medical Informatics Initiative involving 20 partners from science, research and healthcare, including 15 university hospitals and one associated partner
Identifying and systematically analyzing high-risk medication
The INTERPOLAR Use Case investigates how IT-supported methods can assist hospital pharmacists in identifying clinically relevant and potentially avoidable medication-related problems. To this end, the project uses the IT infrastructure established during the development and networking phase of the Medical Informatics Initiative from 2018 to 2022.
For the first time, INTERPOLAR establishes a harmonized, cross-site routine documentation of medication analyses and the medication-related problems identified in the process. This makes it possible to standardize previously heterogeneous documentation practices across hospitals and to evaluate them systematically in a multicenter setting. The IT-supported analyses are based on an expert-curated list of clinically relevant contraindications for 700 commonly prescribed medications. A contraindication refers to a factor (e.g., age, pre-existing conditions, pregnancy, concomitant medication) that speaks against the use of a particular drug. Based on the contraindication list developed in the project, potential medication-related problems can be identified algorithmically.
The identified cases are retrospectively assessed by ward pharmacists as part of the INTERPOLAR study. This includes both a patient-specific evaluation of clinical relevance and a structured documentation of the decision-making and assessment process. The aim is to investigate in which situations IT-supported analyses can reveal additional clinically relevant medication-related problems and meaningfully complement the work of ward pharmacists. The structured documentation of this clinical evaluation process also serves as a basis for further developing algorithms to support clinical decision-making. In particular, AI-based methods such as large language models (LLMs) are to be improved so that pharmacological expert knowledge can be represented more systematically and clinical decision-making can be better supported in the future.
The INTERPOLAR study is conducted in several phases. First, the technical requirements for integrating, analyzing, and evaluating patient and medication data are established at the participating data integration centers. This is followed by a multicenter study at university hospitals involving several wards and a large cohort of inpatients. Over the course of the project, routine data from approximately 70,000 inpatient treatment cases will be analyzed.
The collected longitudinal data are used to improve algorithms, better understand risk patterns, and systematically analyze relationships between medications, contraindications, and clinical events.
Improving drug safety with data analysis
The foundation for INTERPOLAR was laid by the cross-consortium use case POLAR. From February 2020 to December 2022, POLAR developed and applied methods to capture person-level medication data from routine care as well as pharmacy prescription data.
A selected range of polypharmacy cases was classified with regard to potentially inappropriate medication (PIM) using available methods. In addition, POLAR made a significant contribution to the representation of medication and laboratory information in the MII core dataset. The aim of POLAR was to better understand the occurrence of adverse drug reactions and their consequences. INTERPOLAR builds on these results and uses them for analyses in clinical practice. This helps support ward pharmacists and enables more targeted care for patients.
INTERPOLAR is funded by the German Federal Ministry of Research, Technology and Space (BMFTR) with more than eight million Euros from January 1, 2023 to December 31, 2026.
Participating consortia of the Medical Informatics Initiative
