Five Research Frontiers That Could Reshape Healthcare
A proposed PHAT research programme examining the information,
infrastructure, artificial intelligence and human factors that
may determine how healthcare evolves over the next decade.
devices. Artificial intelligence, longitudinal health data,
interoperability, remote monitoring, diagnostics and new
regulatory systems are increasingly interacting.
PHAT’s 2027 objective is not to predict which company or
technology will win. It is to investigate the deeper
infrastructure questions beneath healthcare transformation.
Research principle:
PHAT will distinguish established evidence from inference and
from original PHAT hypotheses. The purpose of this programme is
to identify questions that can be investigated, tested and
challenged — not to present speculation as established medical
knowledge.
The Five Research Frontiers
These subjects are intentionally interconnected. Together they
form a proposed PHAT research architecture rather than five
unrelated technology trends.
The Continuous Patient
between appointments without turning patients into
surveillance subjects?
Building on PHAT’s Invisible Patient
hypothesis, this research programme will examine whether
patient-reported experience, treatment friction, symptoms,
behaviour and other low-burden signals could contribute to
a more continuous understanding of health.
The research will examine what information is genuinely
actionable, what should remain private, how frequently
information should be collected and whether artificial
intelligence could provide continuity without replacing
clinical judgement.
How PHAT will investigate this in 2027
Rather than beginning with a technology and asking what
it can do, PHAT will begin with the information gap:
what clinicians need to know, what patients experience,
what is currently lost and whether collecting a signal
would actually change an action.
- Map information lost between healthcare encounters.
- Review evidence for patient-generated and remote data.
- Identify high-value rather than high-volume signals.
- Examine privacy and digital-exclusion risks.
- Develop testable PHAT hypotheses.
Primary research starting points
-
NHS England — digital health, patient records and
connected systems. - World Health Organization — digital health and AI.
-
Peer-reviewed literature on remote monitoring,
patient-generated health data and continuity of care.
The Health Data Infrastructure Problem
a person rather than a collection of disconnected
clinical encounters?
Healthcare increasingly depends upon information generated
across different locations, organisations and systems.
PHAT will investigate interoperability, longitudinal
records, data standards, patient-generated information,
secure research environments and data governance.
The objective is not to advocate for unlimited data
collection. It is to ask which forms of connected
information create genuine clinical or research value.
How PHAT will investigate this in 2027
PHAT will study the health-data ecosystem as
infrastructure. The research will follow information
from creation to clinical use, asking where value is
created, where information is lost and where
interoperability fails.
A central distinction will be between
more data and
better connected information.
Primary research starting points
- NHS England — interoperability and Single Patient Record.
- WHO — digital health and health-data governance.
- Major UK biomedical research infrastructures.
- Peer-reviewed research on health-data interoperability.
Predictive Prevention
conventional diagnosis becomes obvious?
Much of modern healthcare remains organised around
identifiable disease. PHAT will investigate the possibility
of moving further upstream by examining longitudinal
information, biomarkers, behaviour, environment and
clinical history.
The central question will not simply be whether AI can
predict disease. It will be whether prediction produces
a sufficiently reliable and useful action to improve
outcomes.
How PHAT will investigate this in 2027
PHAT will examine the complete chain:
Signal → Prediction → Clinical Decision →
Intervention → Outcome
Predictions that cannot lead to useful action will be
distinguished from predictions capable of changing a
clinical pathway. False positives, overdiagnosis,
inequality and psychological burden will be treated as
central research questions.
Primary research starting points
- Our Future Health.
- UK Biobank.
- NICE evidence and technology assessment.
- NHS England population-health programmes.
- Peer-reviewed preventive-medicine research.
The AI Assurance Layer
remain safe, accurate, transparent and useful in the
real world?
AI adoption creates a second-order problem that receives
less attention than the algorithms themselves:
continuous assurance.
PHAT will investigate validation, monitoring, clinical
evaluation, bias assessment, model drift, provenance,
governance, human oversight and post-deployment evidence.
How PHAT will investigate this in 2027
Instead of asking only whether an AI system works,
PHAT will investigate the complete lifecycle:
Development → Validation → Deployment →
Monitoring → Re-evaluation
The research will examine whether healthcare requires
an independent assurance layer capable of evaluating
systems throughout their operational life.
Primary research starting points
- MHRA medical-device and AI regulation.
- UK / FDA / Health Canada Good Machine Learning Practice.
- International AI and medical-device standards.
- Peer-reviewed AI safety and clinical-validation research.
The Last Mile of Medicine
the healthcare decision and the real-world outcome?
A prescription is not the same thing as treatment.
A referral is not the same thing as access.
A discharge is not the same thing as recovery.
PHAT will investigate the final stage of healthcare
delivery: adherence, treatment burden, access,
coordination, communication, digital friction and
the practical workload placed on patients and carers.
How PHAT will investigate this in 2027
PHAT will treat the period after a healthcare decision
as a research environment in its own right.
The central question becomes:
What happens between what healthcare intends to
happen and what actually happens?
This connects directly with PHAT’s work on medication
cascades and the Invisible Patient.
Primary research starting points
- NICE — medicines, adherence and implementation evidence.
- NHS England — care delivery and personalised care.
- WHO — health-system and digital-health research.
- Peer-reviewed implementation and health-services research.
PHAT Research Radar
Select a frontier to explore the central hypothesis and
the infrastructure opportunity that PHAT intends to
investigate.
The Continuous Patient
Core hypothesis:
healthcare may be missing meaningful information because
important changes occur between formal encounters.
Potential infrastructure opportunity:
longitudinal patient-signal systems, remote monitoring,
intelligent summarisation and privacy-preserving health
infrastructure.
The complete five-frontier research programme remains
available above without JavaScript.
The Infrastructure & Investment Lens
PHAT does not provide investment advice and this research
programme is not designed to promote individual companies.
The purpose of this section is to identify infrastructure
categories that may become increasingly important as
healthcare digitises.
Systems that make fragmented information interoperable,
secure and usable.
Validation, monitoring, governance and safety
infrastructure surrounding healthcare AI.
Technologies capable of identifying actionable changes
before conventional intervention points.
Infrastructure connecting patients, clinicians and
information between appointments.
Technology designed to reduce friction between diagnosis,
treatment and real-world outcomes.
Secure datasets, analytical environments and tools
enabling large-scale health research.
PHAT’s infrastructure question:
Where could the next generation of healthcare infrastructure
be built before its importance becomes obvious?
How PHAT Will Research These Questions in 2027
PHAT will not treat technological novelty as evidence of
healthcare value. Each research programme will follow a
common analytical process.
The PHAT Research Method
Define the current system and identify the information
or implementation gap.
Review clinical research, policy, regulation and
implementation evidence.
Search for contradictory evidence, failure modes and
unintended consequences.
Develop clearly labelled PHAT hypotheses and
conceptual frameworks.
Define what evidence would strengthen, weaken or
falsify the hypothesis.
The Standard We Will Apply
A promising technology is not the same thing as
demonstrated healthcare value.
PHAT may propose new frameworks, but will distinguish
them clearly from established evidence.
The final question is whether an innovation improves
health, experience, efficiency, equity or understanding.
Research Starting Points
The following institutions and research infrastructures
provide starting points for the programme. They are sources
for investigation, not endorsements of PHAT’s hypotheses.
-
NHS England — digital transformation,
interoperability, patient records, AI adoption and
health-system strategy. -
NICE — clinical evidence, medicines,
technology assessment and implementation. -
MHRA — software, AI-enabled medical
devices and regulatory principles. -
World Health Organization — digital
health, AI, governance and international health-system
transformation. -
Our Future Health — large-scale UK
health and research infrastructure. -
UK Biobank — large-scale biomedical
research infrastructure and longitudinal health data. -
Peer-reviewed research — systematic
reviews, cohort studies, implementation research,
health-services research and relevant technical literature.
Editorial status:
This page establishes a proposed PHAT research agenda.
The concepts described here are research questions and
hypotheses, not validated clinical tools, NHS programmes,
government policy or investment recommendations.
PHAT is an independent health-information and research
project and is not affiliated with NHS England, NICE,
MHRA, WHO, UK Government, Our Future Health or UK Biobank.