1. Outcomes in AKI, the national audit
Dr K A Abraham
Aintree University Hospitals

2. AIMS Study the provision of renal services across the country
Ascertain workload
Study outcomes for different categories of renal disease
Provide user friendly data to clinicians, without adding to their work

3. Hospital Episode Statistics for Physicians Renal Reference Group
KA Abraham/ Jan 09

4. Methods - 1 HES data, All Trusts in England. 06 – 07 & 07 - 08
Acute Trusts
ICD Code Algorithms
3 Renal Streams – AKI, CKD, RRT
Emergency Medical Admissions

5. Coding Algorithm Acute Renal failure [Acute Kidney Injury]: AKI Codes:
A985, D596, K767, N170 – 179, N990, O084, O904
Electrolyte imbalances associated with AKI:
E870 - Hyperosmolality & hypernatraemia
E875 – Hyperkalaemia
N251 - Nephrogenic diabetes insipidus
Renal replacement Codes:
X401 – 406, 408, 409

6. AKI Algorithm – ICD10 List of AKI diagnoses - A
List of clinical conditions likely to be associated with AKI - B
Definite AKI = A in Coding position 1
Probable AKI = A in Coding position 2 – & B in position 1
Possible AKI = A in Coding position 2 – 7
but No B diagnosis in position 1

7. Methods - 2 3 classes of Trusts – Transplant, Onsite, Visiting
Linked to Office of National Statistics
Pilot in 4 renal networks – 16 trusts
Validated by clinicians from each network
National roll out for year 1
Analyses sent out to all nephrologists
Feedback incorporated into 2 year analysis.

8. Statistics
SPSS (v16)
Unpaired t tests or Chi squared tests as appropriate
30 day mortality using the ONS death data linked to the HES data
Corrected for a variety of known confounders.
Age is non-linearly related to mortality, so corrections were performed by comparing each 5 year age band in each trust with the national mortality for that age band with look up tables.
Corrections also for index of multiple deprivations
Co-morbidity variable using Charlson index.

9. Weaknesses CODING – Variation, Depth, Accuracy
Unaccounted Variables - Consultations
Interactions of Factors

10. Validation
Multiple logistic regression used to compare mortality risk using age, co morbidity, deprivation, and specialty of physician
The data was re run a) excluding patients transferred between units and b) for only patients with an ICD 10 code of N179 that carries the descriptor of “acute renal failure - unspecified”.
Excluded “possible AKI” analysed.

11. Results
AKI Incidence = 1·34% of all emergency admissions. [61,739 of 4,637,488]
Only half would have been identified if only the first diagnosis listed had been used.
The numbers & types of AKI cases were similar in all trusts, regardless of the service available.
Thirty day mortality was 30·0%.
More than half the acute hospitals did not have on site renal specialists [55%]

12. Baseline Comparisons Transplant Onsite Visiting Admissions. 18121
16674
11652*
% AKI.
1.5
1.3
Age in yrs
71.9
75.1
76.2*
Codes
5.9
5.8
Comorbidity
1.1
Deprivation.
12663
15800
15127
Specialists
10.7
4.0 0*
Discharges%.
26.9
19.9**
* p < separate or combined ** p < 0.05 between T & O units

13. AKI Outcomes * * ** *
* p < separate & combined ** p < V to T only

14. AKI Outcomes Transplant [21] Onsite [47] Visiting [82]
Median dialysed %
9.6
4.3
1.3*
Median LOS in days
15.7
14.2
13.7**
Median mortality unadjusted [30d]
23.8
28.4**
33.0*
Median mortality adjusted [30d] %
25.3
29.4**
32.5*
* p < separate or combined ** p < 0.05 between T & O units

15. Inter Hospital Transfers
13·7% of admissions to T and 5·7% to O.
Transfer patients were younger - mean age 64 vs. 73 years
Did a selection bias lead to better results?
Within centre, no significant differences in the outcomes between transfer and direct patients
Significant mortality differences persisted when transfers excluded

16. Adjusted Mortality & Renal Cover

17. AKI Mortality Vs Nephrologists in SHA
London
All other SHA’s
Population
7,443,379
44,021,267
AKI No. /pmp
1260
1189
Mean age (yrs)
73.5
75.4
Mean No. Dx codes
5.9
5.8
Mean co-morbidity score
1.05
1.07
Mean deprivation score
13400
15193
No. nephrologists/ pmp
11.4
6.1*
Adjusted mortality (%) 26
31.2*
* p < 0.001

18. Do nephrologists make a difference?
% Deaths
% Renal

19. Conclusions AKI is not rare AKI is deadly
Specialist renal care is associated with better AKI outcomes
A substantial majority do not receive specialist care
Models for better provision have to be considered
similar to acute diabetes
worse than MI or COPD

20. What can we do better? EDUCATION Spoke unit cover Rapid Response
CIN Prophylaxis
AKI Guidance
What can we do better?
Region wide IT
EDUCATION
Clerking proforma
AKI Flag
ITU Liaison
Transfer Protocols

21. Thank You. M Pearson, E Thompson, K Bodger, AHOP
Jane MacDonald, Afzal Chaudhry, Donal O’Donoghue, Charlie Tomson, Kevin Harris, Gary Cook, James Hollinshead, Melanie Maxwell
NHS IC
K. A. Abraham, UHA.