Published in PLOS One on 2025-11-07, 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: Mary Cronin, Lucy Munishi, Gaudensia A. Olomi, Modesta Mitao, Blandina T. Mmbaga, Jackline Somi, Jairy Khanga, Ali S. Khashan, Francis M. Pima, Simon Woodworth
Source: PLOS One • DOI 10.1371/journal.pone.0335644
Read the complete primary study ↗ · Creative Commons Attribution licence
From the researchers
Abstract
Quality health data is essential to improve delivery and outcomes of healthcare. This study explores the experiences of healthcare staff in Kilimanjaro, Tanzania, using a hybrid paper and digital Health Management Information System, and their perspectives on transitioning to a fully digital system. It aims to understand current practices of perinatal data collection and utilisation and gather recommendations regarding the possible introduction of a fully digital HMIS (DHMIS). A case study design was employed; individual semi-structured interviews were undertaken with staff from four professions directly involved in data generation and use (n = 29), working in a range of healthcare settings. Thematic analysis was conducted using NVivo 12 software; it identified findings under four major themes, along with a series of recommendations on the implementation of the DHMIS. We found that while in theory the hybrid paper and digital system facilitates standardised data management, in practice it presents inefficiencies in manual data entry leading to challenges with data accuracy, loss, retrieval, storage and flow. These challenges contribute to the strongly positive attitude among healthcare staff towards adopting a DHMIS which they believe would improve data accuracy, reduce workload, and enhance clinical and policy decision-making. To achieve a successful DHMIS, participants recommended effective training for all users. Additionally, they proposed an integrated system to avoid data redundancy. The importance of robust infrastructure to ensure sustainability, and of reliable internet and electricity supply, were also highlighted. In conclusion, this study provides valuable insights into the shortcomings of paper-based perinatal data recording, and the potential benefits and challenges of implementing a DHMIS in low-resource settings. It underscores the necessity of strategic planning, investment in infrastructure, and capacity building to achieve successful digital transformation in healthcare. The findings align with global health strategies promoting digitalisation to enhance health outcomes and support data-driven decision-making in healthcare systems.
Introduction
Quality health data is essential to monitor, evaluate, prioritise, and improve the delivery of healthcare services [1]. In 2018, the World Health Organisation (WHO) 71st World Health Assembly passed a resolution on digital health exhorting member states to prioritise adoption and implementation of digital health technologies to support achievement of national targets, the Sustainable Development Goals and Universal Health Care [2]. Furthermore, for Low- and Middle-Income Countries it is considered important to develop an organisational culture which emphasises data-informed decision-making [3]. The WHO Global Strategy on Digital Health 2020–2025 [4] emphasises health data should be categorized as sensitive personal data; this calls for extremely high standards of security and necessitates cybersecurity, building trust, accountability and governance, ethics, equity, capacity building, and literacy, as well as ensuring high-quality data are gathered [5].
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 technology & industry 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.
© 2025 Mary Cronin, Lucy Munishi, Gaudensia A. Olomi, Modesta Mitao, Blandina T. Mmbaga, Jackline Somi, Jairy Khanga, Ali S. Khashan, Francis M. Pima, Simon Woodworth. 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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