Improving chronic kidney disease identification and assessing its association with health inequalities in coding practices

Plain English summary of protocol

Background and study aims
Chronic Kidney Disease (CKD) is a global public health problem. It is a long-term condition that gradually damages the kidneys and can lead to serious health problems if not detected early. It is defined as a sustained reduction in the glomerular filtration rate (GFR) of less than 60 ml/min/1.73m2 for 3 months or more, and/or urinary abnormalities or structural abnormalities of the kidney tract. All patients with CKD should be coded in their primary care electronic health records. Accurate coding supports pathways that ensure regular review and monitoring through the CKD register and enhance safe prescribing via automated decision-support alerts.

However, CKD is often under-recorded in primary care because systems may lack reliable disease detection tools, and GPs may not have full access to hospital blood and urine results. As a result, some patients miss essential care, while others are incorrectly coded as having CKD when they do not. These issues are more common in socially deprived areas and among ethnic minority groups, where CKD prevalence is higher.

This project aims to transform CKD detection through a data-driven tool that addresses coding inaccuracies, health inequities, and economic burdens. The early stage of the study consists of three parts:
1) Development and pilot testing of a novel CKD detection algorithm designed to identify undiagnosed CKD cases and incorrect CKD coding.
2) Optimisation and validation of the algorithm to improve CKD classification accuracy by enhancing its sensitivity and specificity.
3) Analysis of kidney care inequalities by comparing coded and uncoded CKD groups, stratified by socioeconomic status, age, sex, ethnicity, other health conditions (comorbidities) and major complications related to CKD (sequelae) including cerebrovascular disease.

Who can participate?
Adult volunteers aged 18 or over (and no upper age limit) who are registered with GP practices located within Lancashire & South Cumbria (L&SC).

What does the study involve?
This study uses existing health records and does not involve any direct patient contact activity. The study comprises the collection of information that is already routinely recorded as part of standard care. Once the CKD detection algorithm is validated in the real-world population, the next step will be to implement it across Lancashire and South Cumbria. The algorithm will then be compared against current practice to assess its impact on clinical outcomes and economic implications. For example, improved CKD coding could prompt timely medication reviews, ensuring that patients receive appropriate treatments, such as sodium–glucose co-transporter 2 (SGLT2) inhibitors, to help slow disease progression. By identifying and coding patients who were previously missed from CKD registers, the tool may also help reduce the financial burden associated with CKD complications, including late presentation with kidney failure requiring urgent dialysis, unplanned hospital admissions, and mortality. Additionally, it may support earlier referral to secondary care services when needed.

What are the possible benefits and risks of participating?
The study aims to improve the detection and coding of CKD in primary care electronic health records. Conversely, patients who have been incorrectly coded as having CKD could be identified and removed from the register, avoiding unnecessary interventions. This would reduce the workload for GPs and provide reassurance to patients. A cost analysis will also be conducted to estimate savings resulting from fewer unnecessary or duplicated appointments and investigations.

As there will be no direct patient contact for research purposes, there will be no risk of intrusion, inconvenience, or any change in the relationship between participants and their general practitioner or kidney specialists (if they are under specialist care).
The main potential risk relates to data confidentiality. To minimise this risk, strict measures will be in place throughout the study:
- Participating GP practices will provide only the NHS numbers of their registered patients and their CKD registers to enable the CKD detection algorithm to run. No other identifiable information will be required from primary care providers.
- The research team will only access identifiable information on a strict need-to-know basis.
- All data will be stored and shared securely using approved platforms within Lancashire Teaching Hospitals NHS Foundation Trust (LTHTR), such as secure email and Microsoft shared folders linked to LTHTR accounts.
- Lower-layer Super Output Area (LSOA), rather than postcode, will be used to assess socioeconomic status to better maintain anonymity.
With these safeguards in place, the risk to participants is considered very low.

Where is the study run from?
Renal Department, Royal Preston Hospital, UK.

When is the study starting and how long is it expected to run for?
April 2026 to July 2028.

Who is funding the study?
Lancashire Teaching Hospitals NHS Foundation Trust, UK.

Who is the main contact?
Dr Wing Yin Leung, w.leung@nhs.net.

Contact information

Dr Wing Yin Leung
Principal investigator, Scientific, Public

Renal Department
Royal Preston Hospital
Preston
PR2 9HT
United Kingdom

ORCID ID	0000-0003-4191-2762
Phone	+44 1772 716565
Email	wingyin.leung@lthtr.nhs.uk

Study information

Eligibility

Locations

Countries of recruitment

• United Kingdom
• England

Study participating centres

Results and Publications

Study outputs

Additional files

49377_Data Flow Chart_v1.1_10Feb2026.pdf

Other files

49377_Protocol_v1.1_10Feb2026.pdf

Protocol file

Editorial Notes

17/04/2026: Study's existence confirmed by Health Research Authority (HRA) (UK).