Institute of General Practice and Family Medicine
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Use Case POLAR_MI

  • POLAR_MI: The use case "POLypharmacy, drug interactions and risks", which comprises all four consortia of the Medical Informatics Initiative, aims to contribute to the detection of health risks in patients with polymedication using methods and processes of the Medical Informatics Initiative (MII).

    Polymedication is particularly common in older patients with multimorbidity. This can lead to drug interactions, which either reduce or increase the desired effect of individual active ingredients or lead to undesirable effects due to pharmacological interactions. These can trigger additional clinical pictures and additional therapy requirements, which could be avoided with better medication management.

    Objectives of the POLAR_MI use case

    In the POLAR_MI use case, medical informaticians, biometricians, epidemiologists, pharmacists, clinical pharmacologists and health researchers from 21 institutions, including 13 university hospitals, are working together to

    1. develop and implement methods to prospectively and retrospectively collect available personal data on prescribed medications (e.g. medication plans) as well as on prescriptions and drug dispensing from pharmacies at several sites of the four MII consortia,
    2. to classify a selected range of polymedications according to available methods with regard to potentially inadequate medication (PIM) and a selected range of medications as high-risk prescriptions,
    3. electronically map scoring systems to identify 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 avoid them altogether (e.g. new diagnoses/interventions, intensive medical care, readmission, new (approved) medications).

    Although a core program has been designed for all participating sites that covers the above-mentioned objectives, additional special sub-projects are planned with the aim of preparing future follow-up projects. One sub-project is working on record linkage with 1-year mortality and, in collaboration with health insurance companies, record linkage on medication use and adverse drug events (ADEs) in outpatient care. Another sub-project is developing a text corpus for natural language processing (NLP) with regard to adverse drug reactions.

    The POLAR_MI use case will

    • obtain data on drugs in Germany in the context of university hospitals,
    • demonstrate that effective use can be made of this health data from MII centers in all four MII consortia, and
    • provide and validate a set of algorithms for the classification of high-risk drugs and PIMs that can be used prospectively to improve drug safety.
Originally translated with DeepL