2026-05-13T16:17:25.700Z http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai

ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:2:7242 2024-06-29T21:34:54Z 2

The development and appraisal of a tool designed to find patients harmed by falsely labelled, falsified (counterfeit) medicines 2017 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/2/7242 M. Andjelkovic E. Björnsson V. De Bono K. Devue N. Dikić D. Ferlin M. Hanževački F. Jónsdóttir M. Shakaryan S. Walser Background: Falsely labelled, falsified (counterfeit) medicines (FFCm’s) are produced or distributed illegally and can harm patients. Although the occurrence of FFCm’s is increasing in Europe, harm is rarely reported. The European Directorate for the Quality of Medicines & Health-Care (EDQM) has therefore coordinated the development and validation of a screening tool. Methods: The tool consists of a questionnaire referring to a watch-list of FFCm’s identified in Europe, including symptoms of their use and individual risk factors, and a scoring form. To refine the questionnaire and reference method, a pilot-study was performed in 105 self-reported users of watch-list medicines. Subsequently, the tool was validated under “real-life conditions” in 371 patients in 5 ambulatory and in-patient care sites (“sub-studies”). The physicians participating in the study scored the patients and classified their risk of harm as “unlikely” or “probable” (cut-off level: presence of ≥2 of 5 risk factors). They assessed all medical records retrospectively (independent reference method) to validate the risk classification and documented their perception of the tool’s value. Results: In 3 ambulatory care sites (180 patients), the tool correctly classified 5 patients as harmed by FFCm’s. The positive and negative likelihood ratios (LR+/LR-) and the discrimination power were calculated for two cut-off levels: a) 1 site (50 patients): presence of two risk factors (at 10% estimated health care system contamination with FFCm’s): LR + 4.9/LR-0, post-test probability: 35%; b) 2 sites (130 patients): presence of three risk factors (at 5% estimated prevalence of use of non-prescribed medicines (FFCm’s) by certain risk groups): LR + 9.7/LR-0, post-test probability: 33%. In 2 in-patient care sites (191 patients), no patient was confirmed as harmed by FFCm’s. The physicians perceived the tool as valuable for finding harm, and as an information source regarding risk factors. Conclusions: This “decision aid” is a systematic tool which helps find in medical practice patients harmed by FFCm’s. This study supports its value in ambulatory care in regions with health care system contamination and in certain risk groups. The establishment of systematic communication between authorities and the medical community concerning FFCm’s, current patterns of use and case reports may sustain positive public health impacts. article 17 419 430 1472-6963 BMC HEALTH SERVICES RESEARCH