Nephwork is the generic name for audit projects designed to allow SpRs to gain experience taking part in research projects. The plan is that a new project every year or two will be started where SpRs from around the country take part and gain the approriate training experience. This is a Renal Association driven initiative.
The first project is based on the AKI Alert data and aims to look at whether the expected treatment received as part of a Hospital admission met the guidelines.
Project: AKI Alert Audit
This project involves anna generating a list of patients to audit for from participating hospitals.
Anna will produce a cohort from the Lab-AKI and HES data such that -
I have the master patient index (MPI) list of AKI-episodes by patients and Laboratory, with a start-date end-date and peak-stage (peak within 30days form AKI-episode start).
Just to clarify how we define an episode:
Consecutive alerts from one person are considered part of the same AKI-episode if there are less that 30days between consecutive alerts.
For example:
Alerts on 1stFeb, 5thFeb 19thFeb 25thApril 1stMay and then nothing else will be reduced to
2 episodes: 1-19Feb (start-end) & 25April-1stMay (start-end)
For the pilot:
I’ll select people with AKI-episodes with start/end date between Jan-Feb 2018 from Addenbrooke’s and Leicester laboratories.
Of those people, I’ll keep those that had an hospitalisation during the duration of AKI-episode (this will mean I keep both hospital acquired AKI and community-acquired AKI which result in hospitalisation), if admission date in the first week 2 weeks of February
Then I’ll check the aki-stage of all alerts that were issued during the first 1-2 weeks of the hospital-admission, and keep if AKI-2 or AKI-3 present
So, for example, a person that has an AKI-2 in the community, then goes into hospital after a couple of days but gets only alerts stage-1 during his hospital admission (based on what we hold in the MPI), will not be included in the list of patients
The dataset the UKRR will provide should have:
- Date of start and end of AKI episode
- Admission and discharge date for the hospitalisation associated to the AKI episode
- Hospital of admission (procode-3)
- Date and stage of peak AKI during the hospital-stay
- ID of patient (name, surname, nhsno, date of birth)
Systems will be required to provide the demographics by masking the hashed nhs no etc. to the Lab AKI database.
This data will be loaded in to a Django based audit tool and participating SpRs will be able to login and see patients to check up on. They will then answer a series of questions about treatment care and outcomes for patients from their sites. saving the records via the audit interface.
The resulting audit data will then be analysed. The project is being run by Garry King and coordinated by Manuela Savino.