A practical guide for teams working on high blood pressure and cardiometabolic risk: digital health products, clinics, pharma-supported programmes, insurers and employer health programmes.
High blood pressure is one of the most common conditions in the world and one of the easiest to measure. A reading takes a minute, home monitors are affordable, and treatment works. Yet it remains a leading cause of stroke, heart attack, heart failure and kidney disease, largely because so many people are never diagnosed, never treated or never brought under control.
The WHO Global Report on Hypertension 2025 estimates that 1.4 billion people were living with hypertension in 2024, and only about one in five had it under control.1 WHO estimates that expanding affordable treatment to half of those affected could prevent 76 million deaths by 2050.2
Source: WHO Global Report on Hypertension 2025.
Most people with hypertension live in low and middle income countries,1 but the gap is visible everywhere. Asian populations carry a higher burden of stroke than Western populations, and salt intake is high in many Asian countries,3, 4 so hypertension is a public health priority across the region, and Asian guidance places particular emphasis on morning blood pressure measured at home.3, 4 Everywhere, the data needed to close the gap is scattered across home monitors, clinics, laboratories and pharmacies.
We wrote this guide for teams working on hypertension and the cardiometabolic risk that surrounds it. If you are building a digital health product, it sets out the data decisions to get right before you scale. If you run a clinic or chronic care service, it covers what it takes to keep records coherent across providers and years. If you lead a pharma-supported programme, it explains what your data needs in order to show outcomes and support real-world evidence. If you are an insurer or run an employer health programme, it shows how measurement and definitions shape who you identify and what you can demonstrate. Pregnancy-related hypertension and secondary causes of high blood pressure have their own considerations and are outside the scope of this guide.
A person with hypertension may take readings on a home monitor that stores them in its memory, write them in a notebook, or photograph the screen. Their clinic records office readings, sometimes on a different arm or device each visit. Lipid, glucose and kidney results arrive through a laboratory portal, ECG and echocardiogram reports sit as PDFs, and medicines are collected from more than one pharmacy. Their watch records heart rate and may flag an irregular rhythm. None of these sources were designed to work together.
Each source holds part of the story. The value comes from bringing them together in a way that stays accurate over years of care.
The twelve points below are grouped into four themes: getting the clinical picture right, making the data usable, connecting the longer story, and building for trust and scale.
Hypertension is defined differently depending on the guideline. The 2025 AHA/ACC guideline in the United States classifies office readings of 130 to 139 systolic or 80 to 89 diastolic as stage 1 hypertension, and recommends a treatment goal below 130/80 mmHg for most adults.5, 6 The 2024 European Society of Cardiology guidelines keep the diagnostic threshold at 140/90 mmHg and describe readings of 120 to 139 systolic or 70 to 89 diastolic as elevated blood pressure.7 Home readings have their own thresholds, such as 135/85 mmHg in European guidance,7 and national guidelines across Asia set their own classifications and targets. The Japanese Society of Hypertension's 2025 guideline, for example, sets an office target below 130/80 mmHg and a home target below 125/75 mmHg.4 When systolic and diastolic readings fall into different categories, the AHA/ACC approach assigns the higher category.8
SBP is systolic and DBP is diastolic blood pressure. Office thresholds only; home and ambulatory thresholds differ. Always check the full guideline you apply.5, 7
None of these is wrong, but mixing them silently causes real problems. The same population can produce very different numbers of people "with hypertension" or "controlled" depending on the thresholds used, which matters for eligibility, reported outcomes and cost projections.
What good looks like: the guideline and thresholds you use written down, applied consistently to office and home readings separately, and recorded alongside each classification so results can be recalculated if you change standards or markets.
Matters most to: Startups, Insurers and employers, Pharma programmes
A single office reading is not a diagnosis. Some people read high only in the clinic (white coat hypertension), while others read normal in the clinic but high at home (masked hypertension).7 Guidelines recommend confirming diagnosis and monitoring control with out-of-office readings taken on a structured schedule. The ESC recommends two readings each morning and evening for three to seven days, averaged,7 and the Japanese guideline asks for morning and evening readings over seven days.4
For a digital tool, this means the unit of truth is usually a series of readings rather than any single value. Products that react to every individual reading tend to generate noise, anxiety and alert fatigue.
What good looks like: office and home readings stored and analysed separately, structured home monitoring schedules, and decisions based on averages across a defined period rather than on single readings.
Matters most to: Clinics, Startups
Blood pressure responds to almost everything: cuff size, arm position, whether the person rested first, caffeine, exercise, pain, time of day and when they last took their medication. A reading taken standing up with the wrong cuff straight after climbing the stairs tells you very little. Many apps capture only the numbers, losing the context that clinicians use to decide whether a reading can be trusted.
What good looks like: each reading captured with its time, arm, position and whether it followed the recommended preparation, with simple prompts that make good technique the default.
Matters most to: Startups, Clinics
Not every blood pressure monitor on the market has been independently validated for accuracy, and validation status varies by model, cuff size and population. Independent lists, such as the STRIDE BP database, show which devices have passed recognised validation protocols.9 Wrist devices and cuffless wearables add further uncertainty. The 2025 AHA/ACC guideline advises against relying on cuffless devices, including smartwatches, for accurate blood pressure measurement until they show greater reliability.6
What good looks like: device make and model recorded with every reading, a list of validated devices you support or recommend, and cuffless or wearable estimates clearly labelled and kept separate from cuff readings.
Matters most to: Startups, Insurers and employers, Pharma programmes
Home monitors store readings in their memory, but in most markets that data never leaves the device. People copy numbers into notebooks, type them into apps or send a photo of the screen. Each route has its own errors: systolic and diastolic swapped, pulse entered as blood pressure, averages mistaken for single readings, and device clocks that were never set. Some monitors also display an irregular heartbeat symbol that carries clinical meaning and is easily lost.
Photo capture is an important bridge where connected monitors are rare, but it needs to read systolic, diastolic, pulse, the timestamp and any warning symbols reliably across many models, as we cover in How to Choose a Medical Device Reading API.
What good looks like: each reading stored with its capture method, device model and a verified timestamp, with plausibility checks that catch swapped or impossible values before they reach a clinician or an alert.
Matters most to: Startups, Clinics, Insurers and employers
Cholesterol and triglycerides are reported in mmol/L in some countries, such as the UK, and in mg/dL in others, such as the United States, and both can appear within one person's record. LDL cholesterol may be measured directly or calculated using one of several formulas, which give different results, particularly when triglycerides are high.10 Lipoprotein(a) is reported either as a mass (mg/dL) or in molar units (nmol/L), and because the size of apolipoprotein(a) varies between people, there is no reliable single factor for converting between them.11 Glucose, HbA1c and kidney markers bring their own unit and method differences.
What good looks like: every result stored with its original value, unit and method, converted to a consistent unit where conversion is valid, flagged where it is not, and traceable to its source laboratory.
Matters most to: Startups, Pharma programmes, Clinics
Most people with hypertension eventually need more than one medicine. ACE inhibitors, angiotensin receptor blockers, calcium channel blockers, diuretics and beta blockers appear under many brand names, and single-pill combinations of two or three medicines are increasingly recommended, including by the 2025 AHA/ACC guideline for starting treatment in stage 2 hypertension.6 Statins and other lipid-lowering treatments often sit alongside them. Doses change, combinations replace separate pills, and refill gaps are one of the clearest signals that a person may have stopped treatment.
What good looks like: each medication recorded with its active ingredients (including every component of a combination), dose, start and stop dates and prescribing source, mapped to medical coding standards, with refill patterns captured where available.
Matters most to: Clinics, Pharma programmes
Treatment decisions increasingly depend on overall cardiovascular risk rather than blood pressure alone. The 2025 AHA/ACC guideline uses the PREVENT risk equations.6 European practice uses SCORE2, and the SCORE2 Asia-Pacific model, published in 2025, recalibrates risk for populations across the region.12 Other tools, such as the WHO risk charts and national calculators, are used elsewhere. Each is calibrated to particular populations, requires particular inputs and produces different numbers for the same person.
What good looks like: the risk score, version and population calibration recorded with every result, along with the inputs used, so scores can be recalculated as models are updated or as you expand into new markets.
Matters most to: Pharma programmes, Insurers and employers, Clinics
Hypertension rarely travels alone. Kidney function (eGFR and the urine albumin to creatinine ratio), glucose and HbA1c, lipids, ECG findings and echocardiogram reports all shape risk and treatment. Some watches and patches can flag a possible irregular rhythm suggestive of atrial fibrillation, which matters because atrial fibrillation raises stroke risk about five-fold.14, 15 These alerts need confirming on a medical-grade ECG, so they are signals rather than diagnoses.13
What good looks like: cardiometabolic markers held in one longitudinal record alongside blood pressure and treatment, reports structured from PDFs and scans, and wearable rhythm alerts labelled as unconfirmed until reviewed.
Matters most to: Clinics, Pharma programmes, Startups
Clinicians need averages and patterns, not hundreds of individual readings: home averages over a defined period, morning and evening patterns, trends since the last treatment change, current medicines and relevant results with dates and units.
Some readings should never simply be logged. Very high readings, particularly when accompanied by symptoms such as chest pain, breathlessness, severe headache, weakness, confusion or changes in vision, need clear rules that direct the person to seek urgent care. Very low readings with dizziness or fainting also need attention, especially after a medication change.
What good looks like: an exportable clinician summary built on averages, escalation rules agreed with clinicians and tested, and a record that can move into a clinic's own system.
Matters most to: Clinics, Startups
Many blood pressure products start as logging or coaching tools. The line into regulated software is usually crossed by what a product claims or does: recommending medication changes, running titration algorithms, diagnosing hypertension, detecting arrhythmias or predicting an individual's cardiovascular risk. Regulators in Singapore, the UK, the European Union, Australia, the United States and many other markets treat these functions as medical devices, each with its own rules.
What good looks like: an intended purpose written down early, claims reviewed against the rules in each market you serve, and validation evidence gathered from the start rather than retrofitted.
Matters most to: Startups, Pharma programmes
Blood pressure and cardiovascular risk data is health data protected under laws such as GDPR, Singapore's PDPA and, where it applies, HIPAA in the United States. When insurers and employers are involved, people need confidence that data shared for their care or wellbeing will not be used against them. Consent should be specific about how data will be used, and data used beyond direct care should be pseudonymised, with access controls and audit trails.
Hypertension is lifelong, while products and programmes change. Structuring data to interoperability standards such as FHIR, with results and medications mapped to medical coding standards, keeps it useful when people change apps, clinics, insurers or employers.
What good looks like: granular consent recorded alongside the data, clear separation between programme data and employment or underwriting decisions, pseudonymisation for secondary use, and standard-format export with provenance intact.
Matters most to: Insurers and employers, Startups, Clinics, Pharma programmes
You do not need to solve all twelve at once. The right starting point depends on what you are building and what your data needs to do.
Some of the twelve points are data problems, and some are questions of design, strategy and delivery. We support both, so you can come to us with the whole picture rather than splitting it across several partners.
Jonda Health is ISO 27001 certified, and our platform is designed to comply with HIPAA, GDPR and PDPA.
This guide is for teams designing and running digital health tools and programmes. It is not clinical advice for individuals.
