ArticlePloS one2026
Exploring the potential impact of medical errors research on population health.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Estimating scientific coherence using population-level indicators and research production data: a longitudinal analytical proof-of-concept study.Frontiers in research metrics and analytics · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWhile most research on medical errors has focused on reducing these events within clinical settings, little is known about whether this scientific research translates into improvements in population-level health or system indicators. This study aimed to explore the potential impact of medical errors research on population health, health system, and research and development indicators.
methodsA longitudinal analysis was conducted using global data from 1995 to 2024. Annual publication counts on medical errors were matched with 18 global population and structural indicators across four domains: mortality, health systems, research and development, and financial risk. Countries were stratified into income groups, and associations were analysed using fixed-effects, negative binomial, and hierarchical mixed-effects models.
resultsHigher research output on medical errors was associated with reductions in neonatal, infant, under-5, and adult mortality, particularly in high-income countries and upper-middle-income countries (UMICs). Significant associations were also found with reduced risk of catastrophic and impoverishing surgical expenditures in UMICs and low- and middle-income countries. Modest links were observed with hospital bed density and intellectual property flows. However, no consistent associations were found in low-income countries or in hierarchical models adjusting for income-level heterogeneity. CONCLUSIONS AND IMPLICATIONS: Scientific research on medical errors shows potential to influence key population health- and structural-level indicators, particularly in countries with developing research ecosystems. These findings address a critical knowledge gap by providing quantitative evidence of research relevance beyond academic metrics. Promoting equitable research capacity and translation may enhance the real-world impact of patient safety efforts globally.
Indexed as
Identifiers
What OpenQuestion holds
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.