Evidence map›Paper›PMID 40979439›Full record

ArticleFrontiers in artificial intelligence2025

Global reform population health management as stewarded by Higher Expert Medical Science Safety (HEMSS).

James Andrew Henry

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Population health management fit lifecycles in analytics.Frontiers in artificial intelligence · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

James Andrew HenryInstitute of Biomedical Sciences, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As described in a Memorandum of Understanding (MoU) on AI infrastructure, global human phenotype ontology (HPO) is a priority for the US and the UK. The UK NHS Act of 1946 and the Medicare and Medicaid Act of 1965 classify using genomics as primary care, supporting international HPO aims for Population Health Management (PHM). The Higher Expert Medical Science Safety (HEMSS) proposes the NHS England, Genomics, and Biobank agile group developers. The HEMSS strategy executes the PHM of the HPO through digital records, pilot citizen predictor pre-eXams, and precise eXam intercept classifications, continuously improving public safety. PHM reform includes biobank opportunities for Value-Based Care (VBC) stratifying genomic and socio-environmental factors that risk HPO in disease segmentation. The author evaluated a standard approach to PHM for HPO with mature and advanced interoperable standards. A reform toolkit aligns adversarial, neural, and transformer models for Generative AI by utilizing multimodal data nuanced for fairness in Quantum Intelligence. The recommendations include HEMSS steps from well-being evaluations to the PHM strategy for HPO in the UK-US. Concepts involve piloting the scaling up of neighborhood clinics and federal centers through reform classification. Plans for citizen privacy facilitate data use with access to reference biobanks, ensuring DNA democratization and national cybersecurity. The UK NHSE corporate governance and US federal authorities monitor and reform the Integrated Care Board assessments and the Centers for Medicare and Medicaid Services surveys using agile methods. The UK-US MoU for AI safety is an international ideal for PHM, creating a safe space for HPO adherence to predictive and interceptive adoption for health and socioeconomic growth. HEMSS Agile Group Development impacts ethical and societal primary care debates. HEMSS discussions on global public health inclusiveness and national engagement aim to govern the classification phases for adherence. Therefore, debates on UK-US accreditation or regulation on the future of Artificial General Intelligence follow. The author concludes in support of the Population Health Management Expert Medical Science Safety Agile Group Development Program. The UK and US governments would benefit from this proposition, and international goals for well-being and socioeconomic growth would also be supported.

Indexed as

higher expert medical science safetymemorandum of understanding on AIpopulation health managementprecision carepredictive health

Identifiers

PMID40979439
PMCPMC12445053

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.