ArticleHealth policy and planning2026
Can innovation strengthen resilient, just and sustainable health systems in disaster-prone settings? Insights from HSR2024.
Article in Health policy and planning, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Changing health systems-advancing justice and sustainability through research, policy and practice.Health policy and planning · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Health systems in disaster-prone settings face recurrent shocks that expose and often deepen existing inequities. Increasingly, innovation, particularly digital technologies and artificial intelligence (AI), is positioned as a pathway to strengthen resilience, responsiveness, and accountability. Drawing on insights from innovation-focused sessions at the 8th Global Symposium on Health Systems Research, this commentary examines whether and under what conditions innovation can contribute to resilient, just and sustainable health systems. We define disaster-prone settings as contexts repeatedly exposed to acute shocks and chronic stressors, such as climate events, outbreaks, and displacement, where service delivery is periodically disrupted and recovery shapes long-term system trajectories. Across diverse examples, including digital dashboards, interoperable data systems, AI-supported decision tools, and community-driven innovations, the symposium highlighted how innovations can improve detection, coordination, and service continuity, particularly during crisis conditions. These approaches can make populations previously invisible to the health system visible, strengthen real-time decision-making, and support anticipatory action. However, the analysis shows that innovation does not inherently produce equitable outcomes. Digital and AI-enabled tools may reproduce or even intensify existing exclusions if they rely on unrepresentative data, lack interoperability, or operate without transparent governance and accountability. Many technologies remain at an early stage, with evolving evidence on effectiveness and equity impacts, placing policymakers in a position of making decisions in uncertainty. In disaster contexts, where rapid decisions and weakened oversight are common, these risks are amplified. We argue that innovation strengthens resilience and justice primarily when accompanied by institutional readiness and governance capacity. This includes clear mandates, regulatory frameworks, ethical safeguards, and mechanisms for iterative learning that translate evidence into practice. Equally important are participatory approaches that ensure communities shape design and decision-making, rather than being passive data sources.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.