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AI-powered monitoring for better heart failure care

Precision Cardiovascular
  • Design
  • Research

The first AI-powered system providing continual data for better heart failure management, keeping patients active and clinicians informed.

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The problem

Heart failure is a growing global burden, affecting millions of patients and placing sustained pressure on healthcare systems.

Ideation Workshops

We worked closely with Precision Cardiovascular to explore the real-world challenges of managing heart failure at scale, bringing together clinical, technical, and product perspectives in a structured research and ideation process.

Through facilitated workshops and early research activities, we examined current care pathways, data availability, and points of friction across monitoring, diagnosis, and intervention.

Research

We conducted a mixed-method research programme combining clinician interviews, patient focus groups, and structured desk research to understand real-world heart failure management challenges. This included interviews with cardiologists and heart failure nurses, moderated sessions with patients living with heart failure, and a review of published clinical studies and comparable monitoring programmes.

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The Research

The research focused on adoption barriers, workflow burden, alert fatigue, compliance behaviours, and the gap between available data and actionable clinical insight. Findings were synthesised into service blueprints, opportunity maps, and evidence-led hypotheses to ensure future innovation was grounded in clinical reality, patient behaviour, and operational constraints.

Pre-clinical testing & clinical readiness

The system is currently being evaluated in a pre-clinical animal model, with ongoing testing in pigs to validate signal fidelity, reliability, and real-world wearability under physiological conditions that closely mirror human cardiovascular dynamics.

From concept to build

Following the research, work progressed into detailed product definition across both hardware and software. Precision Cardiovascular is currently collaborating with a contract development and manufacturing organisation (CDMO) on hardware design, manufacturability, and system integration.

In parallel, the reader and software experience have been designed to support real-world clinical workflows, focusing on signal clarity, ease of use, and minimal burden for patients and care teams. Together, this work translates research and workshop outputs into a cohesive, build-ready system aligned with clinical, technical, and operational requirements.

Our involvement

What we did

Discovery

Clinical Problem Framing & Needs Discovery

Structured sessions with clinicians, researchers, and stakeholders to translate complex cardiovascular care challenges into clearly defined, evidence-based problem statements aligned with real-world workflows.

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What it is

Structured sessions with clinicians, researchers and stakeholders to translate complex cardiovascular care challenges into clearly defined, evidence-based problem statements.

When you need it

A clinical AI initiative needs a shared, evidence-based problem statement before any solution work starts.

What you'll get

Problem statements aligned with real-world clinical workflows, ready to brief a design or engineering team.

How we do it

Structured stakeholder sessions with clinicians and researchers. Typical timeline: 2–3 weeks.
Ideation

AI & Smart Healthcare Innovation Labs

Strategic ideation workshops to identify, assess, and prioritise AI-enabled healthcare solutions, including predictive monitoring, clinical decision support, and patient engagement technologies.

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What it is

Strategic ideation workshops to identify, assess and prioritise AI-enabled healthcare solutions.

When you need it

You have a mandate to explore AI but no shortlist of which use cases are worth pursuing.

What you'll get

A prioritised set of AI-enabled concepts, predictive monitoring, decision support, patient engagement, ranked by feasibility and impact.

How we do it

Facilitated innovation labs with clinical and technical stakeholders. Typical timeline: 1–2 weeks.
Research

Clinical & Stakeholder Research

Conducted in-depth interviews and working sessions with clinicians, researchers, and key stakeholders to understand heart failure care pathways, operational challenges, and unmet clinical needs.

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What it is

In-depth interviews and working sessions with clinicians, researchers and key stakeholders.

When you need it

Care pathways, operational constraints or unmet clinical needs aren't well understood yet.

What you'll get

A grounded picture of heart failure care pathways, operational challenges and the gaps worth solving for.

How we do it

Semi-structured interviews and working sessions with clinical staff. Typical timeline: 3–4 weeks.
Mapping

Workflow & System Mapping

Mapped real-world clinical workflows, data flows, and care journeys to identify inefficiencies, risk points, and opportunities for AI-enabled monitoring and intervention.

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What it is

Mapping real-world clinical workflows, data flows and care journeys.

When you need it

A solution needs to fit around existing clinical operations rather than replace them.

What you'll get

A mapped set of workflows and data flows with inefficiencies, risk points and monitoring opportunities marked.

How we do it

Workflow shadowing and data-flow mapping with operational teams. Typical timeline: 2–3 weeks.
Synthesis

Insights & Opportunities

Translated qualitative and operational insights into clear opportunity areas, user needs, and strategic requirements to guide innovation, product design, and investment decisions.

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What it is

Translating qualitative and operational insights into clear opportunity areas and requirements.

When you need it

Research is done but hasn't yet been turned into a brief the wider team can act on.

What you'll get

Opportunity areas, user needs and strategic requirements ready to guide product and investment decisions.

How we do it

Synthesis workshops against the research and mapping. Typical timeline: 1 week.
Architecture

AI Solution Design & Architecture

Defined end-to-end system concepts across hardware, software, and AI layers, ensuring solutions aligned with clinical workflows, data availability, and regulatory requirements.

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What it is

Defining end-to-end system concepts across hardware, software and AI layers.

When you need it

An opportunity area is agreed and needs a concrete, buildable system concept.

What you'll get

A system concept aligned with clinical workflows, data availability and regulatory requirements.

How we do it

Technical and clinical co-design sessions with your engineering team. Typical timeline: 2–4 weeks.
Design

Product Experience Design

Designed the clinician and patient-facing experiences to support real-world use, prioritising usability, signal clarity, and minimal operational burden.

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What it is

Designing the clinician and patient-facing experiences for real-world use.

When you need it

A validated concept needs to become something clinicians and patients can actually use.

What you'll get

Interface designs that prioritise usability, signal clarity and minimal operational burden.

How we do it

Iterative design with clinician and patient testing. Typical timeline: 3–5 weeks.
Case studies

Our research work