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Development of an algorithm to detect and reduce complexity of drug treatment and its technical realisation

Authors :
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
Hanna M. Seidling
Source :
BMC Medical Informatics and Decision Making, Vol 20, Iss 1, Pp 1-14 (2020)
Publication Year :
2020
Publisher :
BMC, 2020.

Abstract

Abstract Background 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. Methods Complexity factors were selected based on literature and expert rating and specified for integration in the automated assessment. Subsequently, distinct key questions were phrased and allocated to each complexity factor to guide conversation with the patient and personalize the results of the automated assessment. Furthermore, each complexity factor was complemented with a potential optimisation measure to facilitate drug treatment (e.g. a patient leaflet). Complexity factors, key questions, and optimisation strategies were technically realized as tablet computer-based application, tested, and adapted iteratively until no further technical or content-related errors occurred. Results In total, 61 complexity factors referring to the dosage form, the dosage scheme, additional instructions, the patient, the product, and the process were considered relevant for inclusion in the tool; 38 of them allowed for automated detection. In total, 52 complexity factors were complemented with at least one key question for preference assessment and at least one optimisation measure. These measures included 29 recommendations for action for the health care provider (e.g. to suggest a dosage aid), 27 training videos, 44 patient leaflets, and 5 algorithms to select and suggest alternative drugs. Conclusions Both the set-up of an algorithm and its technical realisation as computer-based app was successful. The electronic tool covers a wide range of different factors that potentially increase the complexity of drug treatment. For the majority of factors, simple key questions could be phrased to include the patients’ perspective, and, even more important, for each complexity factor, specific measures to mitigate or reduce complexity could be defined.

Details

Language :
English
ISSN :
14726947
Volume :
20
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Medical Informatics and Decision Making
Publication Type :
Academic Journal
Accession number :
edsdoj.4add812f40fe4c2b8c656dd9ffa52e18
Document Type :
article
Full Text :
https://doi.org/10.1186/s12911-020-01162-6