[The similarity of drug names as a possible cause of confusion: Analysis of data from outpatient care]. / Die Ähnlichkeit von Medikamentennamen als mögliche Ursache von Verwechslungen ­ eine Untersuchung von Daten aus der ambulanten Versorgung.

BACKGROUND: The incidence of adverse drug events (ADE) described in the literature varies between 6.5 and 20 %. Furthermore, it is assumed that up to 29 % of ADE are due to medication errors as a result of confusion because of similarities in spelling (sound alike) or in name, physical appearance or packaging (look alike). Studies dealing with the so-called "LASA" issue were mostly carried out in inpatient care. As far as we know, no systematic investigations into this subject have been carried out for the outpatient sector where patients themselves take care of the application of their medication. In addition, there is no documentation about medication errors in the home setting. The aim of the present study is to describe the importance of the LASA issue in the home setting where medication errors are likely to occur due to similarity of drug names. METHODS: In this context, the similarity of names of prescription drugs was systematically analyzed. We examined in detail how often prescription drug pairings showing orthographic and phonetic similarity were dispensed in the investigation period to an individual patient at the same time. Orthographic similarity was defined as relevant at a Levenshtein index value of ≤ 0.4. This corresponds to the similarity measures of the drugs listed in the LASA public lists and means that the similarity in the lettering of two drug names amounts to at least 60 %. Phonetic similarity was analysed using the Cologne Phonetic ("Kölner Phonetik") for the German language. RESULTS: A total of 255,770 prescriptions were included in the analysis. In 11.4 %, drug pairings were detected that fall below the critical orthographic similarity threshold (Levenshtein index value ≤ 0.4), which represents an increased likelihood of medication error due to the critical similarity of drug names in this fraction. Within this group of "LASA drugs" different degrees of similarity were identified. Even drug pairings with very high orthographic similarity (Levenshtein index value from ≤ 0.1 and 0.1 to ≤ 0.2, 12.4 % and 3.6 % of the drug pairings, respectively) were detected. These drug pairings were mostly different in strength while active ingredients, manufacturer name and pharmaceutical form were the same. For the majority of drug pairings (84 %), the orthographic similarity was lower and showed a Levenshtein index value of ≥ 0.2 to 0.4. Despite different active ingredients, there is a degree of similarity resulting from both identical manufacturer name and pharmaceutical form appearing as part of the drug name. At the phonetic level, the analysis shows comparable frequency of similarity of drug pairings that are subject to potential medication error. DISCUSSION: For the first time, a study was carried out in the outpatient setting recording the incidence of drug pairings that carry a risk for medication errors resulting from patients' confusion over too similar drug names. In the light of the age structure of the patients to whom these look- or sound-alike drugs are prescribed, we can assume that there is a considerable risk of ADE. The conceivable consequences of such medication errors on a pharmacological level range from relatively harmless to potentially highly dangerous. CONCLUSION: There is a major need to fully inform patients about this risk of confusion and subsequent medication errors with certain drug combinations. The similarity structures of drug pairings identified in this study could serve as a basis for developing an appropriate information routine.

Network and Systems Medicine: Position Paper of the European Collaboration on Science and Technology Action on Open Multiscale Systems Medicine.

Introduction: Network and systems medicine has rapidly evolved over the past decade, thanks to computational and integrative tools, which stem in part from systems biology. However, major challenges and hurdles are still present regarding validation and translation into clinical application and decision making for precision medicine. Methods: In this context, the Collaboration on Science and Technology Action on Open Multiscale Systems Medicine (OpenMultiMed) reviewed the available advanced technologies for multidimensional data generation and integration in an open-science approach as well as key clinical applications of network and systems medicine and the main issues and opportunities for the future. Results: The development of multi-omic approaches as well as new digital tools provides a unique opportunity to explore complex biological systems and networks at different scales. Moreover, the application of findable, applicable, interoperable, and reusable principles and the adoption of standards increases data availability and sharing for multiscale integration and interpretation. These innovations have led to the first clinical applications of network and systems medicine, particularly in the field of personalized therapy and drug dosing. Enlarging network and systems medicine application would now imply to increase patient engagement and health care providers as well as to educate the novel generations of medical doctors and biomedical researchers to shift the current organ- and symptom-based medical concepts toward network- and systems-based ones for more precise diagnoses, interventions, and ideally prevention. Conclusion: In this dynamic setting, the health care system will also have to evolve, if not revolutionize, in terms of organization and management.