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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2312.05678 |
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| _version_ | 1866910807609049088 |
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| author | Wickett, Eugene Plumlee, Matthew Smilowitz, Karen Phanouvong, Souly Nwogu, Timothy |
| author_facet | Wickett, Eugene Plumlee, Matthew Smilowitz, Karen Phanouvong, Souly Nwogu, Timothy |
| contents | Ensuring product quality is critical to combating the global challenge of substandard and falsified medical products. Post-marketing surveillance is a central quality-assurance activity in which products from consumer-facing locations are collected and tested. Regulators in low-resource settings use post-marketing surveillance to evaluate product quality across locations and determine corrective actions. Part of post-marketing surveillance is developing a sampling plan, which specifies where to test and the number of tests to conduct at a location. With limited resources, it is important to base decisions on the utility of the samples tested. We propose a Bayesian approach to generate a comprehensive utility metric for sampling plans. This sampling plan utility integrates regulatory risk assessments with prior testing data, available supply-chain information, and valuations of regulatory objectives. We develop an efficient method for calculating sampling plan utility. We illustrate the value of the utility metric with a case study based on de-identified post-marketing surveillance data from a low-resource setting. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_05678 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Measuring sampling plan utility in post-marketing surveillance of medical products Wickett, Eugene Plumlee, Matthew Smilowitz, Karen Phanouvong, Souly Nwogu, Timothy Applications Ensuring product quality is critical to combating the global challenge of substandard and falsified medical products. Post-marketing surveillance is a central quality-assurance activity in which products from consumer-facing locations are collected and tested. Regulators in low-resource settings use post-marketing surveillance to evaluate product quality across locations and determine corrective actions. Part of post-marketing surveillance is developing a sampling plan, which specifies where to test and the number of tests to conduct at a location. With limited resources, it is important to base decisions on the utility of the samples tested. We propose a Bayesian approach to generate a comprehensive utility metric for sampling plans. This sampling plan utility integrates regulatory risk assessments with prior testing data, available supply-chain information, and valuations of regulatory objectives. We develop an efficient method for calculating sampling plan utility. We illustrate the value of the utility metric with a case study based on de-identified post-marketing surveillance data from a low-resource setting. |
| title | Measuring sampling plan utility in post-marketing surveillance of medical products |
| topic | Applications |
| url | https://arxiv.org/abs/2312.05678 |