Hospital Systems

Evidence brief: Barriers of last mile supply chain management and reproductive, maternal, new born, and child health product availability in Ethiopia

A sourced PLOS One study, published 2026-05-14. Read the researchers’ findings, methods and context, with links to connected African health evidence.

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Illustrative stock photograph from Unsplash. It does not depict the reported event, study participants or a confirmed Kenyan facility. Source: https://images.unsplash.com/photo-1582750433449-648ed127bb54

Published in PLOS One on 2026-05-14, this study is presented as an attributed evidence briefing. The excerpts below are the original researchers’ words, reproduced under their Creative Commons Attribution licence. Health Signal has selected the abstract and, where needed, opening background paragraphs; the complete methods, results, limitations and references remain in the linked paper.

Original authors: Welelaw Necho Mulatu, Danielson K. Onyango, Happiness Mberesero, Gizachew Tadelle, Dessalew Emaway, Bezawit Mesfin, Tsegaye Shewangizaw, Chala Tesfaye, Andualem Ababu, Biruk Bogale, Kerubo Mogesi

Source: PLOS One • DOI 10.1371/journal.pone.0346924

Read the complete primary study ↗ · Creative Commons Attribution licence

From the researchers

Abstract

Despite notable advancements in Ethiopia’s health supply chain, critical bottlenecks persist at the last mile, particularly within health centres and health posts. This study aimed to identify barriers affecting the availability of reproductive, maternal, new-born, and child health commodities and to explore barriers, and constraints that hinder effective data use for supply chain decision-making.

This qualitative study employed key informant interviews with 23 participants, including logisticians, pharmacists, store managers, health extension workers, and health program experts. Data were analysed using Braun and Clarke’s thematic analysis framework.

Six key bottlenecks emerged: [1] inconsistent delivery systems; [2] poor data quality and limited use of Logistic Management Information System (LMIS); [3] inadequate inventory management; [4] weak quantification system; [5] staffing shortages; and [6] infrastructure barriers. In pastoral areas, poor road access, limited cold storage, and low eLMIS coverage hinder direct deliveries. Agrarian regions benefit from more direct delivery coverage, but they still face challenges, including aging vehicles and poor rural roads. Across both settings, health posts, the lowest level health facility, often experience inconsistent supply and resort to self-product collection. Indirect delivery via an added layer of woreda (district) offices poses delivery delays. Broader infrastructure issues, such as inadequate storage space, unreliable power, and weak internet connectivity, compound these problems. Data management system weaknesses, including poor reporting quality, limited interoperability, and minimal data use for decision-making, persist in both contexts. Human resource constraints such as shortages of skilled personnel, high turnover, and limited training further undermine supply chain performance.

This assessment highlights interrelated bottlenecks affecting last-mile RMNCH product availability in both pastoral and agrarian areas of Ethiopia, though the severity and context-specific barriers vary. Addressing these issues requires coordinated, system-wide strategies that are tailored to regions with a focus on transportation, strengthening infrastructure, data systems, and workforce capacity.

Background

To enhance health service delivery and ensure consistent product availability, the Ministry of Health (MOH) in Ethiopia has undertaken significant efforts to strengthen logistics integration, last-mile delivery, and the use of electronic Logistics Management Information Systems (eLMIS) at the facility level. The Ethiopian Pharmaceutical Supply Service (EPSS) plays a central role in managing the national health supply chain through the Integrated Pharmaceutical Logistics System (IPLS), working to ensure a continuous and reliable supply of health commodities to the last mile. Collaborative efforts have introduced tools to enhance data visibility and support informed decision-making. However, challenges such as limited system interoperability, capacity barriers, transportation issues, and inadequate data use continue to affect supply chain performance. A multi-country assessment in Sub-Saharan Africa further highlighted common bottlenecks in the availability of lifesaving health commodities, including insufficient staff training, weak supply chain systems, and stock-outs of priority commodities in approximately 40% of facilities on average [1–3].

Reading this evidence

Use the full paper to check the study design, participant selection, comparator and outcome definitions before drawing a practical conclusion. An association does not by itself show cause and effect. A reported performance measure needs its denominator and uncertainty. A finding from a particular facility, sample or time period should retain that scope when it is discussed elsewhere.

This briefing makes the source accessible within the wider hospital systems desk. It does not assess an individual patient or certify a product. When considering relevance to another health system, examine the original authors’ account of context and limitations, then seek local implementation evidence. The related reporting below provides other studies to read alongside this one; it is a topic connection, rather than a claim that their results are directly comparable.

© 2026 Welelaw Necho Mulatu, Danielson K. Onyango, Happiness Mberesero, Gizachew Tadelle, Dessalew Emaway, Bezawit Mesfin, Tsegaye Shewangizaw, Chala Tesfaye, Andualem Ababu, Biruk Bogale, Kerubo Mogesi. Excerpts reproduced under CC BY. Selection, formatting and contextual notes by Health Signal. The researchers are the authors of the source study, not members of Health Signal’s staff.

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Health Signal Editorial Desk

Health Signal’s publication desk curates source-based health analysis and attributed research briefings. Study authors and originating institutions are credited within each article. Preparation used AI assistance; source and licence checks do not constitute independent replication or clinical endorsement.

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