Polypharmacy, Drug Interactions and Risks
The Use Case “Polypharmacy, Drug Interactions and Risks” (POLypharmazie, Arzneimittelwechselwirkungen und Risiken), which includes all four consortia of the Medical Informatics Initiative, aims to contribute to the detection of health risks in patients with polymedication by using methods and processes of the Medical Informatics Initiative.
PPolymedication occurs particularly in older patients with multimorbidity. This can lead to drug interactions that either reduce or enhance the desired effect of individual active ingredients or lead to undesired effects due to pharmacological interactions. These can trigger additional clinical pictures and additional need for therapy, which, however, would be avoidable with better drug management.
In the POLAR_MI Use Case, medical computer scientists, biometricians, epidemiologists, pharmacists, clinical pharmacologists and health researchers from 21 institutions, including 13 university hospitals, work together to
1) develop and implement methods to collect prospectively and retrospectively available personal data on prescribed drugs (e.g. medication plans) as well as on prescriptions and drug dispensations from pharmacies at several sites of the four MII consortia,
2) classify a selected range of polymedications according to available methods regarding Potentially Inadequate Medication (PIM) and a selected range of drugs as high-risk prescriptions,
3) electronically map score systems for identifying high-risk patients for relevant drug-related problems, and
4) identify the occurrence of adverse drug reactions and their consequences at an early stage or to avoid them completely (e.g. new diagnoses/interventions, intensive care, re-introduction, new (approved) medications)
Although a core program covering the above-mentioned objectives has been designed for all participating sites, additional specific sub-projects are planned to prepare future follow-up projects. One subproject deals with record linkage with 1-year mortality and, in cooperation with health insurance companies, with the linking of data on drug use and adverse drug events (ADE) in outpatient care. A further subproject is working on a text body for Natural Language Processing (NLP) with regard to adverse drug reactions.
The use case POLAR_MI will
- obtain data on drugs in Germany in the vicinity of university hospitals,
- demonstrate that effective use of these health data from MII centers in all four MII consortia can be made, and
- provide and validate a set of algorithms for classifying high-risk drugs and PIMs that can be used prospectively to improve drug safety.
- Friedrich-Alexander-Universität Erlangen-Nürnberg
- University Hospital Erlangen
- University Hospital Freiburg
- University Hospital Gießen
- University Heidelberg, Medical Faculty Mannheim