Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Mar 28:13:761787.
doi: 10.3389/fphar.2022.761787. eCollection 2022.

Identifying Potential Drug-Related Problems Among Geriatric Patients With Use of an Integrated Clinical Decision Support Tool

Veera Bobrova  1 , Daniela Fialová  2   3 , Shane Desselle  4 , Jyrki Heinämäki  1 , Daisy Volmer  1
Affiliations

Identifying Potential Drug-Related Problems Among Geriatric Patients With Use of an Integrated Clinical Decision Support Tool

Veera Bobrova et al. Front Pharmacol. .

Abstract

Background: Drug-related problems (DRPs) which arise from potentially inappropriate medications (PIMs) are a common problem in older people with multi-morbidity and polypharmacy. Aim: To develop an integrated PIM clinical decision support tool for identification of DRPs in geriatric multi-morbid polypharmacy patients, using the EU(7)-PIM and EURO-FORTA lists, with a focus on high-risk medications. Methods: The integrated PIM tool used the information on PIMs in both databases-the EU(7)-PIM and EURO-FORTA. PIMs were classified into four color groups based on risk profile: high-risk PIMs (should be avoided in older patients) as red, moderate-risk PIMs (require dose and/or treatment duration adjustment) as yellow, low-risk PIMs (low DRP risk) as green, and questionable PIMs (incomplete/missing information) as grey. Results: The summarized list of the high-risk (red and some grey) PIMs contained 81 active substances and medication classes. According to the ATC classification, most of the high-risk PIMs (n = 60, 74.1%) belong to the A, C, and N medication groups and 50.6% (n = 41) of the high-risk PIMs have currently marketing authorization in Estonia. The preliminary list of the moderate- and low-risk (yellow, green, and other grey) PIMs contained 240 active substances and medication classes, but sub-classification of this category into one or another group depends mainly on an individual patient´s clinical characteristics in a concrete analyzed study sample and needs further research. Conclusion: The integrated clinical decision support tool based on the EU(7)-PIM and EURO-FORTA criteria addresses the need for more efficient identification of DRPs. It can be applied to identify PIMs and geriatric prescribing problems in different health care settings, and also in a context of little clinical information available.

Keywords: Estonia; clinical decision support tool; drug related problems; multi-morbidity; older adults; polypharmacy; potentially inappropriate medications.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
The classification of potential inappropriate medications (PIMs) according to the integrated screening PIM tool based on the EU(7)-PIM and EURO-FORTA lists.
FIGURE 2
FIGURE 2
Proportion of the high-, moderate- and low-risk PIMs in the integrated screening tool based on the EU(7)-PIM and EURO-FORTA criteria.
See this image and copyright information in PMC

References

    1. Alldred D. P., Kennedy M. C., Hughes C., Chen T. F., Miller P. (2016). Interventions to Optimise Prescribing for Older People in Care Homes. Cochrane Database Syst. Rev. 2, CD009095. 10.1002/14651858.cd009095.pub3 - DOI - PMC - PubMed
    1. Bala S., Chen T., Nishtala P. (2019). Reducing Potentially Inappropriate Medications in Older Adults: a Way Forward. Can. J. Aging/La Revue Canadienne Du Vieillissement 38. 10.1017/s0714980819000084 - DOI - PubMed
    1. Botev N. (2012). Population Ageing in Central and Eastern Europe and its Demographic and Social Context. Eur. J. Ageing 9, 69. 10.1007/s10433-012-0217-9 - DOI - PMC - PubMed
    1. Cheen M. H. H., Tan Y. Z., Oh L. F., Wee H. L., Thumboo J. (2019). Prevalence of and Factors Associated with Primary Medication Non‐adherence in Chronic Disease: A Systematic Review and Meta‐analysis. Int. J. Clin. Pract. 73, e13350. 10.1111/ijcp.13350 - DOI - PubMed
    1. Crealey G. E., Sturgess I. K., McElnay J. C., Hughes C. M. (2012). Pharmaceutical Care Programmes for the Elderly: Economic Issues. PharmacoEconomics 21, 455–465. 10.2165/00019053-200321070-00001 - DOI - PubMed