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The ICE-AKI study: Impact analysis of a Clinical prediction rule and Electronic AKI alert in general medical patients

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posted on 2019-07-03, 09:18 authored by LE Hodgson, PJ Roderick, RM Venn, GL Yao, BD Dimitrov, LG Forni
Background Acute kidney injury (AKI) is assoicated with high mortality and measures to improve risk stratification and early identification have been urgently called for. This study investigated whether an electronic clinical prediction rule (CPR) combined with an AKI e-alert could reduce hospital-acquired AKI (HA-AKI) and improve associated outcomes. Methods and findings A controlled before-and-after study included 30,295 acute medical admissions to two adult non-specialist hospital sites in the South of England (two ten-month time periods, 2014–16); all included patients stayed at least one night and had at least two serum creatinine tests. In the second period at the intervention site a CPR flagged those at risk of AKI and an alert was generated for those with AKI; both alerts incorporated care bundles. Patients were followed-up until death or hospital discharge. Primary outcome was change in incident HA-AKI. Secondary outcomes in those developing HA-AKI included: in-hospital mortality, AKI progression and escalation of care. On difference-in-differences analysis incidence of HA-AKI reduced (odds ratio [OR] 0.990, 95% CI 0.981–1.000, P = 0.049). In-hospital mortality in HA-AKI cases reduced on difference-in-differences analysis (OR 0.924, 95% CI 0.858–0.996, P = 0.038) and unadjusted analysis (27.46% pre vs 21.67% post, OR 0.731, 95% CI 0.560–0.954, P = 0.021). Mortality in those flagged by the CPR significantly reduced (14% pre vs 11% post intervention, P = 0.008). Outcomes for community-acquired AKI (CA-AKI) cases did not change. A number of process measures significantly improved at the intervention site. Limitations include lack of randomization, and generalizability will require future investigation. Conclusions In acute medical admissions a multi-modal intervention, including an electronically integrated CPR alongside an e-alert for those developing HA-AKI improved in-hospital outcomes. CA-AKI outcomes were not affected. The study provides a template for investigations utilising electronically generated prediction modelling. Further studies should assess generalisability and cost effectiveness.

Funding

Grants from the Small Business Research Initiative (National Institute for Health Research Devices for Dignity HTC partnered with the Department of Health) and the British Renal Society / British Kidney Patient Association, 14-013 (LEH) helped fund integration and implementation of the technology into Patientrack from the Hospital Trust’s electronic servers.

History

Citation

PLoS ONE, 2018, 13(8): e0200584.

Author affiliation

/Organisation/COLLEGE OF LIFE SCIENCES/School of Medicine/Department of Health Sciences

Version

  • VoR (Version of Record)

Published in

PLoS ONE

Publisher

Public Library of Science

eissn

1932-6203

Acceptance date

2018-06-28

Copyright date

2018

Available date

2019-07-03

Publisher version

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0200584

Notes

Supporting information S1 TREND Checklist. (PDF) S1 File. (DOCX) S1 Protocol. (PDF)

Language

en

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