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A systematic review of substandard, falsified, unlicensed and unregistered medicine sampling studies: a focus on context, prevalence, and quality
  1. Dominic McManus1,
  2. Bernard David Naughton2,3
  1. 1School of Pharmacy (Formerly of), University College London, London, UK
  2. 2Saïd Business School, University of Oxford, Oxford, UK
  3. 3Pharmacy Department, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
  1. Correspondence to Bernard David Naughton; bernard.naughton{at}sbs.ox.ac.uk

Abstract

Substandard and falsified (SF) medicines are a global issue contributing to antimicrobial resistance and causing economic and humanitarian harm. To direct law enforcement efficiently, halt the spread of SF medicines and antimicrobial resistance, academics, NGOs and government organisations use medicine quality sampling studies to estimate the prevalence of the problem. A systematic review of medicine quality studies was conducted to estimate how the methodological quality of these studies and SF prevalence has changed between 2013 and 2018. We also aimed to critique medicine sampling study methodologies, and the systematic review process which generates prevalence estimates. Based on 33 studies, the overall estimated median (Q1–Q3) prevalence of SF medicines appears to have remained high at 25% (7.7%–34%) compared with 28.5% in 2013. Furthermore, the methodological quality of prevalence studies has improved over the last 25 years. Definitive conclusions regarding the prevalence of SF medicines cannot be drawn due to the variability in sample sizes, consistency of design methods, and a lack of information concerning contextual factors affecting medicine quality studies. We contend that studies which present cumulative average prevalence figures are useful in a broad sense but could be improved to create more reliable estimates. We propose that medicine quality studies record the context of the study environment to allow systematic reviewers to compare like with like. Although, the academic rigour of medicine quality studies is improving, medicine sampling study limitations still exist. These limitations inhibit the accurate estimation of SF medicine prevalence which is needed to support detailed policy changes.

  • systematic review
  • health policy
  • public health
  • health systems evaluation
  • health services research
http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Footnotes

  • Handling editor Seye Abimbola

  • Twitter @bernard_naughton

  • Collaborators Oksana Pyzik Senior Teaching Fellow UCL School of Pharmacy and Founder of UCL Fight the Fakes.

    Michael Munday, Professor of Pharmaceutical Biochemistry at UCL School of Pharmacy.

  • Contributors BDN proposed the research project idea and design. DMcM gathered the data and analysed the data. The data analysis was checked by BDN. BDN and DMcM wrote the manuscript. BDN made revisions. BDN and DMcM reviewed the paper before submission and resubmission.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Disclaimer The opinions expressed are those of the authors and do not necessarily represent the opinion of their employers.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting or dissemination plans of this research.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information. Please see supplementary file for study data.

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