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Review
. 2020 Oct;86(10):2000-2007.
doi: 10.1111/bcp.14045. Epub 2019 Jul 25.

Medication management needs information and communications technology-based approaches, including telehealth and artificial intelligence

Alphons Eggerth  1   2 , Dieter Hayn  1 , Günter Schreier  1   2
Affiliations
Review

Medication management needs information and communications technology-based approaches, including telehealth and artificial intelligence

Alphons Eggerth et al. Br J Clin Pharmacol. 2020 Oct.

Abstract

Life expectancy is rising in most parts of the world as is the prevalence of chronic diseases. Suboptimal adherence to long-term medications is still rather the norm than the exception, although it is well known that suboptimal adherence compromises the therapeutic effectiveness. Information and communications technology provides new concepts for improving adherence to medications. These so-called telehealth concepts or services help to implement closed-loop healthcare paradigms and to establish collaborative care networks involving all stakeholders relevant to optimising the overall medication therapy. Together with data from Electronic Health Records and Electronic Medical Records, these networks pave the way to data-driven decision support systems. Recent advances in machine learning, predictive analytics, and artificial intelligence allow further steps towards fully autonomous telehealth systems. This might bring advances in the future: disburden healthcare professionals from repetitive tasks, enable them to timely react to critical situations, and offer a comprehensive overview of the patients' medication status. Advanced analytics can help to assess whether patients have taken their medications as prescribed, to improve adherence via automatic reminders. Ultimately, all relevant data sources need to be collated into a basis for data-driven methods, with the goal to assist healthcare professionals in guiding patients to obtain the best possible health status, with a reasonable resource utilisation and a risk-adjusted safety and privacy approach. This paper summarises the state-of-the-art of telehealth and artificial intelligence applications in medication management. It focuses on 3 major aspects: latest technologies, current applications, and patient related issues.

Keywords: adherence; artificial intelligence; machine learning; medication; telehealth.

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Conflict of interest statement

There are no competing interests to declare.

Figures

Figure 1
Figure 1
Data collection via near‐field communication (NFC). Left top: medication packaging with attached NFC tag; left bottom: collecting data from a smart blister; right: collecting data via NFC by touching a blood pressure meter and the fields of a chart, which are equipped with NFC tags. (© AIT Austrian Institute of Technology GmbH)
Figure 2
Figure 2
Closed‐loop healthcare paradigm in the heart failure scenario. Clockwise: Coordinator, clinician, nurse, general practitioner, relatives, helpdesk. (© AIT Austrian Institute of Technology GmbH)
Figure 3
Figure 3
Common methods for quantification of adherence to medications. Top: calculating the percentage of pills taken; middle: calculating the fraction of adherent time intervals (e.g. days); bottom left: calculating the fraction of time, when the concentration of the drug was on an appropriate level; bottom right: evaluating a questionnaire, which was answered by a patient
Figure 4
Figure 4
Combining all available data sources into a comprehensive dataset
See this image and copyright information in PMC

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