Substandard and falsified medicines: Proposed methods for case finding and sentinel surveillance

Elizabeth Pisani*, Amalia Hasnida, Mawaddati Rahmi, Maarten Olivier Kok, Steven Harsono, Yusi Anggriani

*Corresponding author for this work

Research output: Contribution to journalReview articleAcademicpeer-review

5 Citations (Scopus)
90 Downloads (Pure)

Abstract

The World Health Organization and others warn that substandard and falsified medicines harm health and waste money, especially in low- and middle-income countries. However, no country has measured the market-wide extent of the problem, and no standardized methods exist to estimate the prevalence of either substandard or falsified medicines. This is, in part, because the task seems overwhelming; medicine markets are huge and diverse, and testing medicines is expensive. Many countries do operate some form of postmarket surveillance of medicine, but their methods and goals differ. There is currently no clear guidance on which surveillance method is most appropriate to meet specific public health goals. In this viewpoint, we aimed to discuss the utility of both case finding and risk-based sentinel surveillance for substandard and falsified medicines, linking each to specific public health goals. We posit that choosing the system most appropriate to the goal, as well as implementing it with a clear understanding of the factors driving the production and sale of substandard and falsified medicines, will allow for surveillance resources to be concentrated most efficiently. We adapted principles used for disease outbreak responses to suggest a case-finding system that uses secondary data to flag poor-quality medicines, proposing risk-based indicators that differ for substandard and falsified medicines. This system potentially offers a cost-effective way of identifying “cases” for market withdrawal, enhanced oversight, or another immediate response. We further proposed a risk-based sentinel surveillance system that concentrates resources on measuring the prevalence of substandard and falsified medicines in the risk clusters where they are most likely to be found. The sentinel surveillance system provides base data for a transparent, spreadsheet-based model for estimating the national prevalence of substandard and falsified medicines. The methods we proposed are based on ongoing work in Indonesia, a large and diverse middle-income country currently aiming to achieve universal health coverage. Both the case finding and the sentinel surveillance system are designed to be adaptable to other resource-constrained settings.

Original languageEnglish
Article numbere29309
JournalJMIR Public Health and Surveillance
Volume7
Issue number8
DOIs
Publication statusPublished - Aug 2021

Bibliographical note

Funding Information:
AH’s work was supported through a fellowship from the United States Pharmacopeia Quality Institute, which also provided support for supervision to EP and MOK. MOK’s work was also supported by the Netherlands Research Excellence Initiative (REI). These funders have had no part in preparing this manuscript.

Funding Information:
AH’s work on risk-based surveillance was supported by a research fellowship from the United States of Pharmacopeial Convention (USP) Quality Institute; USP Quality Institute also provided supervision support for EP and MK. In addition, EP, YA, AH, and MR currently receive research funding from UK National Institute for Health Research (GHPSR Project: NIHR131145) to develop and trial sentinel surveillance and estimation methods related to medicine quality. MOK receives research support from the Netherlands Research Excellence Initiative. SH is an employee of the public health division of health care data science firm IQVIA. IQVIA provides data and insights on pharmaceutical market dynamics in over 100 countries. The company contributed research and staff time for exploration of the ideas proposed in this paper at no cost.

Publisher Copyright:
© Elizabeth Pisani, Amalia Hasnida, Mawaddati Rahmi, Maarten Olivier Kok, Steven Harsono, Yusi Anggriani. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 16.08.2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on https://publichealth.jmir.org, as well as this copyright and license information must be included.

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