[e-drug] Toolkit for medicine quality studies

e-drug
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E-DRUG: Toolkit for medicine quality studies
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Dear colleagues,

Greetings from Universitas Pancasila in Jakarta, where the Center for Pharmaceutical Policy and Service Studies has been busy conducting a survey of medicine quality in randomly selected outlets. We collected over 1200 samples of five medicines in pharmacies; public and private hospitals and health centres; and informal markets (including the internet), in five provinces of Indonesia.

We learned a lot in the process (including about what NOT to do!). We also developed a number of software-based tools, field forms, standard operating procedures and data management processes and code. We thought it might be useful to share these with other researchers and regulators who are, or are considering, undertaking similar surveys, in case they wish to download and adapt them for their own use, or simply to have examples from another setting.

The Guide can be downloaded (for free, of course!) at https://dataverse.harvard.edu/api/access/datafile/6880882

  The whole Toolkit (including the Guide) is available online at https://doi.org/10.7910/DVN/OBIDHJ

All the forms, data examples and code are available in adaptable soft-copy. Please do share with anyone who might find this useful.

This toolkit is not intended to replace existing advice on how to conduct medicine quality surveys (for example those provided here: https://digicollections.net/medicinedocs/#d/s22404en

and here:
https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000052

It simply provides practical tips for a single type of study based on recent experience, and examples of the tools that we wish we had had access to when we started fieldwork a year ago.

We know that there is a lot of experience out there, and many other approaches to studying medicine quality, and we warmly welcome comments and suggestions for additions to text and tools, and other improvements.

We look forward to 'live peer review', and plan to modify and improve the toolkit with input from others (with appropriate credits), so please don't hold back!

We would also gladly be involved in any future discussions about more formal guidelines that include mystery shopping and other sampling designs or survey methods looking at medicine quality.

We thank advisors and collaborators at the Indonesian medicine regulator BPOM and the Indonesian statistics bureau BPS, as well as at Imperial College London and Erasmus University, for their support in this process.

We are grateful to UK taxpayers, and the UK's Department of Health and Social Care, for funding the work through a National Institute for Health HPSR grant.

With best regards,

Yusi Anggriani and Elizabeth Pisani,
for the STARmeds team
(especially Jenny Pontoan, Mawaddati Rahmi, Ayu Rahmawati, Hesty Utami, Esti Mulatsari, William Nathanial, Yunita Nugrahani and Stanley Saputera, who worked unreasonably hard to generate the experience encapsulated here.)
Elizabeth Pisani <pisani@ternyata.org>

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Glad to see more tools developed and become part of the medicines quality surveillance toolkit. Congrats Elizabeth and the STARmeds team!

The compilation of those tools in a resource centre is a great idea. The MedRS tool we developed for risk-based post marketing surveillance and deployed in dozens of countries by the Promoting the Quality of Medicines Plus (PQM+) Program belongs right there as well. I would like to take you up on the “live peer review” to learn more about this particular Indonesia work and compare that to our experiences at PQM+.

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Hi Jude,
Thanks for your interest. Yes, we absolutely agree that the USP/PQM MedRS tool providing guidance on risk-based surveillance is a useful resource and belongs in any surveillance toolkit (for e-druggers who are not already familiar with it, you can find the pdf document here: https://www.usp.org/sites/default/files/usp/document/our-work/global-public-health/rbpms-resources-english.pdf).

On the subject of concepts of “risk” in medicine quality, I’d love to see more conversations about if, how and when to distinguish between two quite different aspects of risk when planning surveillance:

  1. Risk that a particular medicine may be substandard (e.g. linked to complexity of manufacturing, volatility of molecules involved, therapeutic index, short-term supply chain disruptions) or falsified (e.g. linked to legal status of medicine, demand for off-label use, therapeutic urgency, cost and coverage status);
    and
  2. Risk to patients and public health if a particular medicine is substandard or falsified (influenced by therapeutic use and class, consuming patient profile, disease prevalence etc.)

We’ve had useful comments on the STARmeds toolkit from several colleagues who have faced similar challenges in the field, and who have found solutions appropriate for different settings; we haven’t yet got around to integrating them into an updated document, nor yet advanced the idea of a collective repository for these sorts of tools, but if you send us your thoughts on the current version that will likely provide the prompt we need to take the next steps in improving our own doc and creating an expanded repository of tools.

Meanwhile, for those who are interested in the topic, the STARmeds data, covering source and price for 1333 samples of five medicines sampled from four regions of Indonesia as well as the internet, with detailed laboratory test results for 1274 of them, are available in the STARmeds study repository at https://dataverse.harvard.edu/dataverse/STARmeds. We have listed the papers we are currently working on at the end of our preprint paper on estimating the prevalence of poor quality medicines (currently under revision) at https://medrxiv.org/cgi/content/short/2023.10.08.23296708v1, but there are many other interesting analyses that could be undertaken with these data, so please, all e-druggers, feel free to unleash your creativity on them (after reading the terms of use!)
Best regards,
Team STARmeds