GENOMICS
DATA MODALITIES
REAL TIME PLATFORMS
BULK DATA BATCH LOAD
DATA SPOKE ALLIANCES
PHYSIOLOGY
IMAGES MEDICAL LABORATORY
MEDICAL DATA
SOCIAL FACTORS
GENOME & BIOBANK HUBS
H P O
D A T A
U S E
A N D
A C C E S S
VARIANT CALL FORMAT GATEWAY
DICOM API GATEWAY
FHIR API GATEWAY
HL7 V2 GATEWAY
GENOME, IMAGE AND HEALTH FACTOR INGESTION
TOOLING
GOOGLE DEEP
VARIANT DEEPMIND
FEDERATED DATA
PLATFORM OPEN AI B BIOLOGICAL MODELLING A DATA SCIENCE & AI TECHNOLOGY
NATIONAL APPLICATION PRE-PROCESSING
LEARNING REFERENCES
MULTIMODAL DATA GENERATIVE AI
STORAGE CAPACITY
BIAS XAI
CAPABILITY CAPACITY
C VALUE BASED CARE RNN, LSTMS, CNN
Vit, LLM,
Multimodal Data
PUBLIC HEALTH & PATIENT SAFETY
QUANTUM COMPUTE
3
FEDERATED DATA
LEARNING
GEN AI GAN GPT5
GEMINI 2.0
2 AI DIGITAL REGULATION SERVICE
AI SAFETY INSTITUTE & RESOURCE RESEARCH
POPULATION HEALTH MANAGEMENT AT SCALE
CLASSIFICATIONS GENOME PRE-EXAM EXAM INTERCEPTS
Fig 4. Population Health Management, HPO Transformation with Science and Technology.
(NICE) expanded technology appraisal process, enabling the removal of outdated technologies to free resources for effective investments.2,20
Figure 4
illustrates the operational efficiency in practice with data science and AI technology (A) impacting biological modelling (B) for value-based care (C) as realised through the development and adoption of the operational components in points 1-3. Figure 4 depicts the integration of data modalities with data use and access with data science and AI technology. It highlights bias and AI explainability towards excellence in public health and patient safety through a technological backbone for achieving data-driven health and efficiency goals of the plan. The technological foundation for achieving data-driven health and efficiency goals is clearly laid out in Figure 4.
Establishing standard interoperability with public trust For a truly integrated national health service, the 10-Year Plan needs to be capable of seamless data flow and collaborative care with standardisation in interoperability and public trust on both an ethical and safe implementation.1-3
The
manuscript moves forward from >30 ISO norms21-25
on HPO transformation within the HIMSS infrastructure.26 practices4-6 and AIRR15
to frontier ecosystem thinking Adopting standard
for the AIDRS,14 56 AISI,16 technical and governance
ecosystem transitions the genomic network.11-13
The UK plan prioritises
ethical governance, patient safety, and public trust for successful digital transformation. Public trust is multifaceted in ethics, privacy, and security, which the author details in the PHM series for HPO transformation, informing how principles can be established and stewarded with the HEMSS proposal.2
From Figure 5,
limitations like algorithmic bias and data inequalities require mitigation in an approach to an HPO well-being adoption, which cultivates public confidence in a PHM plan with comparative analytics. Figure 5 depicts the evidence base of algorithms vital for HPO classification. It showcases a rigorous, transparent framework for AI-driven healthcare, including measures for accuracy and equity. By illustrating how advanced AI refines genomic pre-eXams and precise care eXams, this figure directly links technical robustness to strengthening public trust, equity, and ethical governance that is stewarded to support the 10 Year Health Plan. The concepts of trust, equity, and transparency in HPO adoption are directly linked to the quantitative analysis presented in Figure 5.
Discussion – paving the way for a future-ready health ecosystem This discussion section elaborates on the strategic vision and practical implementation of the HPO
transformation, with each point directly supported by the detailed information found in the tables contained in the PHM – HPO Transformation’ manuscript.2 The belief that this plan is a meticulous blueprint, providing concrete mechanisms and operational strategies, is underpinned by the detailed ecosystem presented in Table 10 (HPO Transformation Roadmap), which outlines a phased approach with aims, activities, outcomes, and metrics for HIMSS development through HEMSS adoption. This roadmap ensures the plan is actionable, moving beyond theoretical possibilities. A profound aspect, the focus on
preventive health via genomic pre- eXams, directly envisions a future where individuals receive highly personalised risk assessments based on unique DNA and epigenetic profiles. The integration of such data with established clinical pathways needs to demonstrate a realistic approach to widespread adoption, a concept visually supported by Figure 1. The central role of HPO policy transformation as primary care, linking traditional diagnostics with digital genomics and defining preventive health, aligns with the broader context of managing population health defined in Table 1. The scientific and technological foundation for national preventive programmes, including newborn screening and polygenic risk scores, is elaborated upon with Table 7 (Real-world AI in Clinical Practice Comparatives for
AUGUST 2025
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