Development of an algorithm to detect and reduce complexity of drug treatment and its technical realisation
The increasing complexity of current drug therapies jeopardizes patient adherence. While individual needs to simplify a medication regimen vary from patient to patient, a straightforward approach to integrate the patients’ perspective into decision making for complexity reduction is still lacking. W...
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| Hauptverfasser: | , , , , , , , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
08 July 2020
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| In: |
BMC medical informatics and decision making
Year: 2020, Jahrgang: 20, Pages: 1-14 |
| ISSN: | 1472-6947 |
| DOI: | 10.1186/s12911-020-01162-6 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1186/s12911-020-01162-6
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| Verfasserangaben: | Viktoria S. Wurmbach, Steffen J. Schmidt, Anette Lampert, Eduard Frick, Michael Metzner, Simone Bernard, Petra A. Thürmann, Stefan Wilm, Achim Mortsiefer, Attila Altiner, Lisa Sparenberg, Joachim Szecsenyi, Frank Peters-Klimm, Petra Kaufmann-Kolle, Walter E. Haefeli and Hanna M. Seidling |
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| 520 | |a The increasing complexity of current drug therapies jeopardizes patient adherence. While individual needs to simplify a medication regimen vary from patient to patient, a straightforward approach to integrate the patients’ perspective into decision making for complexity reduction is still lacking. We therefore aimed to develop an electronic, algorithm-based tool that analyses complexity of drug treatment and supports the assessment and consideration of patient preferences and needs regarding the reduction of complexity of drug treatment. | ||
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