RIKHTA · CVD PREVENTION INTELLIGENCE FOR NHS ICSs

Data to decisions.

Rikhta traverses GP records, A&E attendances, community pharmacy dispensing and social care data — synthesises them into unified causal intelligence — and tells your ICS exactly which CVD prevention intervention, or which combination, prevents the most cardiovascular events per pound.

£7.4B

CVD ANNUAL NHS COST

40+

MACE EVENTS PREVENTED/YR

110%

NET ANNUAL ROI

01  THE FRAGMENTATION PROBLEM

Data exists. It just doesn't speak.

A patient with uncontrolled hypertension in Newham appears across at least five disconnected systems simultaneously. None of them talk to each other. Current tools show you the primary care gap. They cannot answer the commissioning question that actually matters.

"Given our finite budget and the complete picture of what's happening across all care settings — which intervention, or which combination, will prevent the most cardiovascular events in our specific population?"

THE QUESTION NO EXISTING TOOL CAN ANSWER

/ PRIMARY CARE ONLY

CVDPREVENT & Sheffield tools

Excellent benchmarking — but single-tier. Cannot traverse secondary care, community services, or pharmacy data simultaneously.

/ GP SYSTEM ANCHORED

EMIS PHM & EHR platforms

Strong cohort identification within GP data, but structurally incapable of traversing the full care pathway.

/ STATIC OBSERVATORY

NHS Fingertips & PHE tools

Rich contextual data that cannot translate into dynamically updated resource allocation decisions from live cross-system signals.

02  AGENTIC CROSS-SYSTEM TRAVERSAL

Every level of care. One intelligence environment.

Rikhta's traversal agent continuously queries, reconciles, and synthesises data across the full NHS ecosystem — treating it as a single queryable data layer, not a collection of dashboards.

TIER 1 Primary care EHR via FHIR R4 · prescribing · diagnoses · QOF registers
TIER 2 Secondary & emergency care SUS+ MACE events · ECDS A&E attendances
TIER 3 Community & pharmacy CSDS community services · NHSBSA · dispensing patterns
TIER 4 Population health & social determinants NHS Fingertips · ONS Census · JSNA intelligence

/ CAUSAL INFERENCE

DoWhy + EconML engine

Directed Acyclic Graphs model causal pathways across interventions. Double Machine Learning estimates heterogeneous treatment effects by demographic subgroup.

/ GRAPH INTELLIGENCE

Population graph networks

Patients as nodes. Cross-system care connections, geography, and social determinants as edges. Identifies clusters falling between care tiers.

/ BUDGET OPTIMISATION

Thompson Sampling bandits

Optimisation layer recommends the single intervention or cocktail that maximises expected QALY gains under your exact budget constraint.

03  THE FIXED INTERVENTION FRAMEWORK

Four pillars. Infinite precision.

Rikhta operates against a fixed, clinically validated menu of the four CVDPREVENT intervention pillars. Not open-ended recommendations — evidence-based options, optimised against the complete cross-system picture of your population.

P-01

Hypertension case-finding & monitoring

Cross-system signals identify undiagnosed hypertension invisible to GP records alone — A&E crisis presentations, pharmacy dispensing gaps, community service referrals.

P-02

Hypertension treatment to target

Adherence signals from pharmacy dispensing patterns and social care assessments reveal the true drivers of uncontrolled blood pressure — housing stress, medication barriers, care fragmentation.

P-03

Lipid-lowering therapy initiation

NHSBSA prescribing data reconciled with community pharmacy dispensing identifies prescribing variations and non-collection patterns across your ICS.

P-04

Lipid treatment to target in established CVD

Secondary care SUS+ data integrated with GP records to track treatment gaps in high-risk patients across their entire care journey, not just within one system.

04  REGULATORY & CLINICAL SAFETY

Defensible by design.

UKCA Class IIa Software as a Medical Device pathway. Full DCB0129/0160 compliance with embedded Clinical Safety Officer oversight. Every recommendation traces to its exact cross-system data inputs and causal assumptions — built for MHRA, built for CQC.

UK DATA RESIDENCY DSPT ALIGNED HUMAN-IN-THE-LOOP DCB0129/0160 ILAP ENGAGED

05  COMMERCIAL MODEL

The numbers, plainly.

/ NEWHAM-SCALE POPULATION · 390,000 RESIDENTS

Prevented MACE events (annually) 30–40
NHS cost avoidance £420,000
Platform cost (annually) £200,000
Net annual ROI 110%

Excludes QALY gains, health inequality reduction, and operational efficiency savings from eliminating manual cross-system data synthesis.

/ ICS STRATEGIC TIER

£180k – £240k / year

Full cross-system causal modelling and commissioning intelligence for 500,000–1 million population ICSs.

/ PCN INTELLIGENCE TIER

£8k – £12k / PCN / year

Patient-level optimisation enriched by cross-system signals, surfaced directly into existing GP workflows via FHIR R4.

/ OUTCOMES-BASED COMPONENT

20% of contract value

Tied to demonstrated CVDPREVENT indicator improvements above baseline trajectory.

06  EVIDENCE, NOT PROMISES

Quietly becoming the standard.

“It's the first system that feels like it's on my side of the desk. I stopped being a data clerk somewhere in week two.”
DR. A. RAHMAN · GP PARTNER · PILOT PRACTICE, NORTH WEST LONDON

/ WORKFLOW INTEGRATION

No rip-and-replace

Vendor-neutral intelligence overlay on existing ICS data platforms. Feeds into Joint Forward Plans and JSNA refresh cycles. Live in weeks.

/ TRANSPARENCY

Every recommendation explained

Every recommendation references the specific cross-system data signals that drove it. Full auditability for commissioners and regulators.

/ AUTOMATION

Board-ready outputs

Automatically generates ICS-ready scenario packs, investment options, and NHS board papers. Clinicians review and sign, not type.

GET IN TOUCH

Let's talk about your ICS.

Reach out and we'll walk you through how Rikhta maps your data environment against the cross-system traversal architecture — no procurement forms, no sales deck.

Get in touch