Kidney Disease

Improving kidney patient care and outcomes through health informatics research

Kidney Disease@Farr brought a multidisciplinary group of researchers with interests in health informatics and kidney disease from across the four Farr Institute Centres together with the UK and Scottish Renal Registries, Patient View, the UK Renal Data Collaboration and academic partners to:

  • Generate opportunities to share ideas, challenges and learning
  • Foster collaborations around kidney research


Kidney disease is a substantial public health problem, with Chronic Kidney Disease (CKD) affecting approximately 10% of the population, and Acute Kidney Injury (AKI) complicating up to 1 in 7 hospital admissions. Internationally and in the UK, there has been substantial focus on raising awareness, facilitating early diagnosis and developing clinical practice guidelines. The UK Renal Registries’ provide longstanding exemplars for high quality data collection for people with severe kidney disease requiring renal replacement therapy. Data linkage provides a growing opportunity to improve our understanding of kidney disease and care across the spectrum of kidney disease.

Across the UK, researchers in the Farr Institute of Health Informatics Research Centres developed novel data linkages to support kidney disease research. Linkages included examples from laboratory, primary care, hospital episode, prescribing, clinical cohorts and registries.

Kidney Disease@Farr was an initiative that aimed to support the development and sharing of research ideas, foster collaborations and utilise the Farr Infrastructure to improve kidney patient care and outcomes through collaborative health informatics research.



  • Identifying Episodes of acute kidney injury across health care settings using routinely collected data (start date: 0ct 2016; duration: 6 months; PIs: Sabine van der Veer, Corri Black; funded by a £15K cross-Farr HIRN grant).This project aims to develop an electronic phenotyping algorithm for discrete acute kidney injury (AKI) events in routinely collected health care data. This will be applied across four data sets with different information infrastructures to evaluate algorithm portability whilst further progressing the algorithm’s design and robustness.The algorithm which will be made publically available together with associated metadata and guidance for local implementation. Additionally, we anticipate the publication of a clinical report of incidence and characteristics of AKI episodes in four UK health care populations, including potential explanations for any differences. We will also publish a methodological paper providing generic guidance how to replicate electronic phenotyping algorithms across datasets with different contexts and underlying infrastructures.
  • The UK data landscape as a platform for renal research (start date: April 2014; duration: 4 months; PIs: Corri Black, Sabine van der Veer; funded by a £10K Farr Network grant).The project aims to promote the potential for rapid, replicable high impact health informatics research in the UK by expediting secondary use of available data; kidney research will serve as an exemplar. Combining the results of a scoping literature review with expert panel input, we will explore which renal data sources are available, and describe if and how they are used for addressing high priority research questions related to chronic kidney disease.
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