JOURNAL ARTICLE
Toward Advancing Women's Health in Least Developed Countries: Evaluating Contraceptive Distribution Models in Senegal.
Published In: Manufacturing & Service Operations Management (M&SOM) (INFORMS), 2024, v. 26, n. 3. P. 873 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Karimi, Amir; Mishra, Anant; Natarajan, Karthik V.; Sinha, Kingshuk K. 3 of 3
Abstract
This article evaluates the transition from the pull distribution model, where frontline health workers manage contraceptive inventory, to the informed push distribution model, which delegates inventory management to external logistics providers, in Senegal's public health supply chain. Using novel field data and a triple differences estimation, the study finds that the informed push model significantly reduces contraceptive stock-outs, decreases frontline health worker workload, and improves client satisfaction, contraceptive prevalence, and maternal and newborn health outcomes—especially in health facilities with less mature logistics management information systems (LMIS) and less developed road infrastructure. A cost–benefit analysis reveals that transitioning severely disadvantaged facilities (those with both less mature LMIS and poorer road access) to the informed push model is cost-efficient and yields substantial public health benefits, whereas upgrading LMIS practices is a more cost-effective alternative for moderately disadvantaged facilities. These findings provide actionable insights for policymakers in least developed countries to prioritize resource allocation for improving last-mile access to reproductive health commodities.
Additional Information
- Source:Manufacturing & Service Operations Management (M&SOM) (INFORMS). 2024/05, Vol. 26, Issue 3, p873
- Document Type:Article
- Subject Area:Geography and Cartography
- Publication Date:2024
- ISSN:1523-4614
- DOI:10.1287/msom.2021.0488
- Accession Number:177184347
- Copyright Statement:Copyright of Manufacturing & Service Operations Management (M&SOM) (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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