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

Algorithm-based approach to CKD identification and its association with health inequalities in coding practices

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

ISRCTN

Registry ID

ISRCTN16150211

Enrollment

60000

Registered

2026-04-22

Start date

2026-04-20

Completion date

Unknown

Last updated

2026-05-04

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Chronic Kidney Disease Urological and Genital Diseases

Interventions

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 part

Eligibility

Sex/Gender

All

Age

18 Years to 120 Years

Inclusion criteria

Inclusion criteria: 1. Adults aged 18 or over (and no upper age limit) 2. Patients registered with GP practices located within Lancashire & South Cumbria (L&SC) participating in the study 3. No other specific inclusion criteria apply

Exclusion criteria

Exclusion criteria: 1. Patients under the age of 18 2. Patients registered with GP practices outside Lancashire & South Cumbria (L&SC) 3. No other exclusion criteria apply

Countries

England, United Kingdom

Contacts

Public ContactWing Yin Leung

wingyin.leung@lthtr.nhs.uk+44 1772 716565

Outcome results

None listed

Source: ISRCTN (via WHO ICTRP) · Data processed: May 7, 2026