Identifying Episodes of Acute Kidney Injury Across Health Care Settings Using Routinely Collected Data.

Project Details

Description

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.
Short titleR:KCB VEES1
StatusFinished
Effective start/end date1/10/1631/03/17

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.