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June 3, 2026PLOS Digital Health0 citationsOpen Access

A global analysis of national cardiovascular disease control plans using a multi-agent artificial intelligence model

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HPHugh PearsonCKCaleb J. KumarCRChe L. Reddy

Key Result

Analysis of 45 national cardiovascular disease control plans using an AI model revealed low overall comprehensiveness (median score 1.20/5), lacking operational detail and contextual assessment.

Key Points

  • To assess the comprehensiveness of national cardiovascular disease control plans worldwide.
  • Identified and analyzed national plans for 45 countries using a multi-agent artificial intelligence model.
  • Utilized a validated health-systems framework structured into 11 elements and 69 sub-elements.
  • Employed a three-stage AI pipeline for document analysis, scoring based on framework criteria, and validation.
  • Overall comprehensiveness of plans averaged 1.20 out of 5, indicating low effectiveness.
  • Strategic direction scored highest among elements with a median of 2.80.
  • Plans lacked detail on contextual assessments, particularly in threats (0.12) and opportunities (0.29).

Study Design

Type

Cross-Sectional (n=45)

Multicenter

Yes

Structured PICO

P
Population
45 national cardiovascular disease control plans analyzed for comprehensiveness using a validated health-systems framework and a multi-agent artificial intelligence model.
E
Exposure
Analysis using a validated health-systems framework and a multi-agent artificial intelligence model
O
Outcome
Comprehensiveness of national plans scored on a 0-5 scale across 11 elements and 69 sub-elements

National cardiovascular disease control plans globally lack operational detail, suggesting a need for standardized templates and AI-supported benchmarking to improve planning quality.

Limitations

  • Small low-income country sample (n = 2) preventing inferential conclusions about income group differences
  • Weak ordinal agreement statistics with human review indicating validation for structural benchmarking rather than fine-grained qualitative judgement
  • Small LIC sample (n = 2) preventing inferential conclusions about income group differences
  • Ordinal agreement statistics with human review were uniformly weak and non-significant

Abstract

Cardiovascular diseases cause nearly one-third of global deaths, yet standalone National Cardiovascular Disease Control Plans remain uncommon and inconsistently structured. We assessed the comprehensiveness of recent national plans using a validated health-systems framework and a multi-agent artificial intelligence model. We identified the most recent official plan for 45 countries from World Health Organisation and World Heart Federation repositories and government sources. We adapted a health-systems planning framework for cardiovascular disease and validated it through a two-stage expert consensus process involving 42 specialists from 28 countries, resulting in 11 elements and 69 sub-elements with standardised definitions and scoring criteria. Plans were analysed using a three-stage artificial intelligence pipeline that ingested documents, applied framework-based scoring, and performed automated validation checks. Sub-elements were scored on a 0–5 scale and summarised by element, World Health Organisation region, and World Bank income group. Overall comprehensiveness was low (median 1.20/5). Plans most consistently addressed strategic direction (median 2.80) and governance arrangements (2.14). Contextual assessment was deficient — threats (0.12) and opportunities (0.29) — as were performance specification elements, including objectives (0.50) and health system outcomes (0.67). The Western Pacific region scored highest (median 1.71) and Africa lowest (0.90), though scores remained below moderate levels across all regions. Income group pairwise comparisons were non-significant across all groups; given the small LIC sample (n = 2), no inferential conclusions about income group differences are drawn. Validation against blinded human review across six countries showed 43.7%exact agreement and 68.0%agreement within one point; ordinal agreement statistics were uniformly weak and non-significant, indicating the approach is validated for structural benchmarking rather than fine-grained qualitative judgement. Most national cardiovascular disease plans articulate vision without sufficient operational detail, particularly for contextual analysis, measurement, and integrated financing. Standardised planning templates and artificial intelligence–supported benchmarking, complemented by expert review, could strengthen national planning quality and enable scalable global comparisons.

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Cite This Study

Pearson et al. (2026) conducted a cross-sectional in Cardiovascular disease (n=45). National cardiovascular disease control plans was evaluated on Overall comprehensiveness score (0-5 scale). Analysis of 45 national cardiovascular disease control plans using an AI model revealed low overall comprehensiveness (median score 1.20/5), lacking operational detail and contextual assessment.

synapsesocial.com/papers/6a1fc56bdee9eb8c0dce6df0https://doi.org/10.1371/journal.pdig.0001447
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