A practical guide for teams working on chronic kidney disease: digital health products, clinics and laboratories, pharma-supported programmes, insurers and employer health programmes.
Chronic kidney disease is one of the quietest conditions in medicine. It rarely causes symptoms until it is advanced, and it is detected almost entirely through laboratory results: a creatinine value turned into an estimated glomerular filtration rate (eGFR), and a urine test for albumin. That makes it the most laboratory-led of the conditions in this series, and one of the most sensitive to how data is captured, calculated and labelled.
The Global Burden of Disease 2023 study estimates that 788 million adults were living with chronic kidney disease in 2023, and that it had become the ninth leading cause of death worldwide, with 1.48 million deaths.1 Awareness remains very low. According to the 2024 guideline from KDIGO (Kidney Disease: Improving Global Outcomes), the international body that sets kidney care guidelines, only about 6% of the general population and 10% of people at high risk know their kidney disease status.2
Sources: Global Burden of Disease 2023 chronic kidney disease estimates; KDIGO 2024 Clinical Practice Guideline.
Asia carries a large share of this burden. China and India have the largest numbers of adults with chronic kidney disease, estimated at 152 million and 138 million respectively.3 Diabetes and hypertension are the two most common causes worldwide,2 which links this guide closely to our diabetes and hypertension guides. There is also a form of kidney disease that does not follow the usual pattern: chronic kidney disease of unknown cause affects agricultural communities in Sri Lanka's North Central region, sugarcane workers in Central America, and the Uddanam region of Andhra Pradesh in India.4 Tools built on assumptions from Western populations can miss these patterns entirely.
We wrote this guide for teams working on chronic kidney disease. 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 laboratory, it covers what it takes to keep results coherent and comparable over 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 testing and definitions shape who you identify and what you can demonstrate. Acute kidney injury, dialysis and transplantation each have their own considerations and are outside the scope of this guide.
Most kidney data is laboratory data, which makes it easy to assume it is already structured and consistent. In practice, a person's creatinine and eGFR may come from several laboratories using different equations and units, their urine albumin results may be recorded as a ratio, a dipstick reading or not at all, and their ultrasound and specialist letters arrive as documents. Their blood pressure and glucose are measured at home, and their medicines, which often need adjusting as kidney function changes, are collected from more than one pharmacy.
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.
KDIGO defines chronic kidney disease as abnormalities of kidney structure or function present for more than three months, with implications for health. It classifies the condition by Cause, glomerular filtration rate (GFR) category (G1 to G5) and Albuminuria category (A1 to A3), known as the CGA system.2 The two measures work together: a person with near-normal eGFR but heavy albuminuria can be at higher risk than someone with a lower eGFR and no albuminuria.
Adapted from the KDIGO 2024 guideline risk grid. ACR is the urine albumin to creatinine ratio. A3 corresponds to above 300 mg/g, and A1 to below 30 mg/g. Green indicates low risk if there are no other markers of kidney disease.
Products that track eGFR alone, or that show a single "kidney score" without saying how it was derived, lose exactly the information clinicians use to judge risk and plan care.
What good looks like: both eGFR and albuminuria categories stored and shown together, with the cause of kidney disease recorded where known, and classification logic that follows the CGA system.
Matters most to: Startups, Clinics and laboratories, Pharma programmes
Because the definition requires abnormalities lasting more than three months, one low eGFR or one raised albumin result does not establish chronic kidney disease. KDIGO specifically cautions against assuming chronicity from a single abnormal result, because it may reflect acute kidney injury or acute kidney disease.5
For a data product, this means the unit of truth is a series of results over time, with dates. A tool that flags "kidney disease" from one value will generate false alarms, and one that averages away a sudden fall may hide an acute problem that needs urgent attention.
What good looks like: results stored with collection dates, logic that distinguishes a sustained pattern from a single abnormal value, and sudden changes flagged separately from chronic trends.
Matters most to: Startups, Insurers and employers, Clinics and laboratories
Most eGFR values are calculated from serum creatinine, and creatinine reflects more than kidney function. KDIGO lists factors that change creatinine independently of filtration, including muscle mass, high-protein diets, creatine supplements and medicines that reduce tubular secretion of creatinine.5 Trimethoprim, for example, can raise creatinine quickly and reversibly without any change in kidney function.6 KDIGO also calls for creatinine assays to be calibrated to a traceable reference standard, so results are comparable between laboratories.5
This matters for populations with very different body composition, for older people with low muscle mass, and for fitness and wellness products whose users may be taking supplements.
What good looks like: creatinine stored with the laboratory and method, relevant context captured (supplements, recent medication changes, very high or low muscle mass), and cystatin C results kept alongside where they exist.
Matters most to: Clinics and laboratories, Startups
eGFR is a calculation, not a measurement, and the equation matters. KDIGO 2024 recommends a validated creatinine-based equation that does not use race, such as the 2021 CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equation, adding cystatin C when greater accuracy is needed. It also advises using the same equation consistently within a region.2, 5 In practice, other equations remain in use in some laboratories and countries, and older results in a person's record may have been calculated differently from newer ones.
When results calculated with different equations sit side by side in one record, an apparent change in kidney function can simply be a change of formula.
What good looks like: each eGFR stored with the equation that produced it, the underlying creatinine (and cystatin C) kept so eGFR can be recalculated consistently, and trends drawn from a single, stated equation.
Matters most to: Clinics and laboratories, Pharma programmes, Startups
Creatinine is reported in µmol/L in some countries and mg/dL in others (1 mg/dL is 88.4 µmol/L).7 The urine albumin to creatinine ratio (ACR) appears in mg/g or mg/mmol, and KDIGO pairs the key threshold of 30 mg/g with 3 mg/mmol.2 Some laboratories report urea and others blood urea nitrogen, which are not the same measure. Without harmonisation, a creatinine of 1.2 can sit next to a creatinine of 106 and look like a dramatic change when it is the same result.
What good looks like: every result stored with its original value, unit and method, converted to a consistent unit for analysis, and traceable to its source laboratory.
Matters most to: Startups, Clinics and laboratories, Pharma programmes
Albuminuria is often the earliest sign of kidney damage, yet it is the result most likely to be missing. In a global consortium study, a median of only 35% of adults with diabetes and 4% of adults with hypertension had been tested for albuminuria.8
When results do exist, they vary in type and reliability. KDIGO recommends the urine albumin to creatinine ratio, with a raised result confirmed on a first morning sample. Exercise, infection, fever and menstruation can raise results temporarily, and semi-quantitative dipstick readings should be confirmed with a laboratory measurement.2, 5
What good looks like: albuminuria results stored with their test type (ratio, protein ratio or dipstick) and sample type, confirmation status recorded, and missing tests flagged as gaps rather than read as normal.
Matters most to: Insurers and employers, Clinics and laboratories, Pharma programmes
Kidney function shapes medication decisions in two directions. Many medicines cleared by the kidneys need their dose reviewed as eGFR falls, and KDIGO advises considering GFR when dosing them and taking care with nephrotoxic medicines.5 At the same time, several treatments now slow the progression of kidney disease. KDIGO 2024 recommends SGLT2 (sodium-glucose cotransporter 2) inhibitors for many adults with chronic kidney disease and an eGFR of 20 or above, recommends RAS (renin-angiotensin system) inhibitors, meaning ACE (angiotensin-converting enzyme) inhibitors or angiotensin receptor blockers, for chronic kidney disease with albuminuria, and suggests a nonsteroidal mineralocorticoid receptor antagonist with proven benefit for adults with type 2 diabetes and persistent albuminuria despite RAS inhibition.5
What good looks like: each medication recorded with its active ingredient, dose, dates and prescribing source, mapped to medical coding standards, and linked to the eGFR and albuminuria values at the time of each change.
Matters most to: Clinics and laboratories, Pharma programmes
As kidney function declines, other results start to matter: potassium, bicarbonate, haemoglobin for anaemia, and calcium, phosphate and parathyroid hormone for mineral and bone disorder. KDIGO 2024 addresses metabolic acidosis and high potassium directly and refers anaemia and bone disorder to its dedicated guidelines.5 Because diabetes and hypertension are the most common causes,2 glucose, HbA1c (glycated haemoglobin) and blood pressure belong in the same record.
What good looks like: complication markers and the drivers of kidney disease held in one longitudinal record, so a clinician or programme can see cause, progression and complications together.
Matters most to: Clinics and laboratories, Pharma programmes, Startups
KDIGO 2024 recommends using an externally validated risk equation, such as the Kidney Failure Risk Equation (KFRE), for people with chronic kidney disease in categories G3 to G5. It links risk thresholds to action: considering nephrology referral at a five-year kidney failure risk of 3% to 5%, multidisciplinary care at a two-year risk above 10%, and preparation for kidney replacement therapy at a two-year risk above 40%.5 The KFRE has been validated in more than 30 countries, although some regions needed recalibration.9
What good looks like: the equation, version and any regional calibration recorded with every risk result, along with the inputs used, so risk can be recalculated as models are updated or as you expand into new markets.
Matters most to: Pharma programmes, Insurers and employers, Clinics and laboratories
A useful kidney summary shows eGFR and albuminuria trends on a consistent basis, the current CGA category, relevant complication markers, current medicines, and risk equation results with dates.
Some results should never simply be logged. Named guidelines give clear thresholds to build escalation rules on:
Rules built on these thresholds should still be agreed with the clinicians who will act on them, and adapted to the guideline your market follows.
What good looks like: an exportable clinician summary in a consistent format, escalation rules agreed with clinicians and tested, and a record that can move into a clinic's own system.
Matters most to: Clinics and laboratories, Startups
Software intended to be used for a medical purpose, without being part of a hardware device, is described internationally as Software as a Medical Device.10 Kidney tools cross into this territory when they classify disease, recommend medication doses, or predict an individual's risk of kidney failure. Regulators in Singapore, the UK, the European Union, Australia, the United States and many other markets each apply their own rules to these functions.
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
Kidney data is health data protected under laws such as the EU General Data Protection Regulation (GDPR), Singapore's Personal Data Protection Act (PDPA) and, where it applies, the Health Insurance Portability and Accountability Act (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.
Kidney disease is usually lifelong. Structuring data to interoperability standards such as FHIR (Fast Healthcare Interoperability Resources), with results and medications mapped to medical coding standards, keeps it useful when people change clinics, laboratories, 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 and laboratories, 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.
