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Service evaluation of the implementation of a digitally-enabled care pathway for the recognition and management of acute kidney injury

Connell, A; Montgomery, H; Morris, S; Nightingale, C; Stanley, S; Emerson, M; Jones, G; Sadeghi-Alavijeh, O; Merrick, C; King, D; et al. Connell, A; Montgomery, H; Morris, S; Nightingale, C; Stanley, S; Emerson, M; Jones, G; Sadeghi-Alavijeh, O; Merrick, C; King, D; Karthikesalingam, A; Hughes, C; Ledsam, J; Back, T; Rees, G; Raine, R; Laing, C (2017) Service evaluation of the implementation of a digitally-enabled care pathway for the recognition and management of acute kidney injury. F1000Research, 6. p. 1033. ISSN 2046-1402 https://doi.org/10.12688/f1000research.11637.1
SGUL Authors: Nightingale, Claire

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Abstract

Acute Kidney Injury (AKI), an abrupt deterioration in kidney function, is defined by changes in urine output or serum creatinine. AKI is common (affecting up to 20% of acute hospital admissions in the United Kingdom), associated with significant morbidity and mortality, and expensive (excess costs to the National Health Service in England alone may exceed £1 billion per year). NHS England has mandated the implementation of an automated algorithm to detect AKI based on changes in serum creatinine, and to alert clinicians. It is uncertain, however, whether ‘alerting’ alone improves care quality. We have thus developed a digitally-enabled care pathway as a clinical service to inpatients in the Royal Free Hospital (RFH), a large London hospital. This pathway incorporates a mobile software application - the “Streams-AKI” app, developed by DeepMind Health - that applies the NHS AKI algorithm to routinely collected serum creatinine data in hospital inpatients. Streams-AKI alerts clinicians to potential AKI cases, furnishing them with a trend view of kidney function alongside other relevant data, in real-time, on a mobile device. A clinical response team comprising nephrologists and critical care nurses responds to these AKI alerts by reviewing individual patients and administering interventions according to existing clinical practice guidelines. We propose a mixed methods service evaluation of the implementation of this care pathway. This evaluation will assess how the care pathway meets the health and care needs of service users (RFH inpatients), in terms of clinical outcome, processes of care, and NHS costs. It will also seek to assess acceptance of the pathway by members of the response team and wider hospital community. All analyses will be undertaken by the service evaluation team from UCL (Department of Applied Health Research) and St George’s, University of London (Population Health Research Institute).

Item Type: Article
Additional Information: © 2017 Connell A et al. This is an open access article distributed under the terms of the Creative Commons Attribution Licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
SGUL Research Institute / Research Centre: Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: F1000Research
ISSN: 2046-1402
Dates:
DateEvent
8 August 2017Published Online
30 June 2017Published Online
Projects:
Project IDFunderFunder ID
UNSPECIFIEDNational Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
URI: https://openaccess.sgul.ac.uk/id/eprint/109246
Publisher's version: https://doi.org/10.12688/f1000research.11637.1

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