Nephwork
- George Swinnerton
- Tim Whitlock (Deactivated)
The NephWork is a new SpR driven National SpR audit and research network supported by the Renal Association and the Renal Registry who’s aim is to develop, coordinate and deliver simple audit and research projects that answer a specific and simple question on a large scale by coordinating the audit and research activity of a large number of renal trainees nationally. The NephWork is part of and is financially supported by the Renal Association and runs with the support of the UK Renal Registry to undertake selected projects.
The first audit project selected is an audit of AKI care in acute admitting trusts nationally, 10 years on from the original NCEPOD report. Data will be used to compare patterns of care across the UK to nationally agreed audit standards for the care of patients with AKI (recently published RA guidelines) in order to review care standards and patient outcomes identified through the Renal Registry Master patient index for AKI.
Project: AKI Alert Audit
Description
The audit pro-forma has been developed by the NephWork steering committee following the Renal Association AKI audit guidelines. SpR's working in an NHS Trust who agree to be member of Nephwork will register the audit locally using a guidance which the Nephwork steering committee will provide in order to help with the process of registering. It will be necessary for a Consultant within the department to nominally be lead for the Audit locally.
We will be auditing the care of all episodes of AKI stage 2 and stage 3 which occur in patients admitted to Acute NHS Trusts during a period of four weeks in early 2020 (start date to be confirmed). These patients will be identified through the Master Patient Index at the UK Renal Registry and a patient identifier for each episode will be sent electronically from the Registry through a specially designed, secure, electronic portal hosted on a dedicated platform to SpR’s completing the Audit locally. SpR’s will review patient notes and records for the selected episodes and then return data using the electronic pro-forma securely through the portal.
This data will be analysed by the renal registry, following a pre-specified statistical analysis plan looking at:
- variations in care regionally/locally and
- associations between measures of AKI care and outcome
An important aspect of this project is that because each identifier contains a unique patient identifier code, we will then be able to link the data gained from the audit in order to analyse patient outcomes, including mortality.
Identifying Patients
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.