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Connell A, Montgomery H, Morris S, et al. Service evaluation of the implementation of a digitally-enabled care pathway for the recognition and management of acute kidney injury. F1000Res. 2017;6:1033doi: 10.12688/f1000research.11637.2.
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, 61033. https://doi.org/10.12688/f1000research.11637.2
Connell, Alistair, et al. "Service evaluation of the implementation of a digitally-enabled care pathway for the recognition and management of acute kidney injury." F1000Research vol. 6 (2017): 1033. doi: https://doi.org/10.12688/f1000research.11637.2
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. Service evaluation of the implementation of a digitally-enabled care pathway for the recognition and management of acute kidney injury. F1000Res. 2017 Jun 30;6:1033. doi: 10.12688/f1000research.11637.2. eCollection 2017. PMID: 28751970; PMCID: PMC5510018.
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F1000Res. 2017 Jun 30;6:1033. doi: 10.12688/f1000research.11637.2. eCollection 2017.

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

F1000Research

Alistair Connell, Hugh Montgomery, Stephen Morris, Claire Nightingale, Sarah Stanley, Mary Emerson, Gareth Jones, Omid Sadeghi-Alavijeh, Charles Merrick, Dominic King, Alan Karthikesalingam, Cian Hughes, Joseph Ledsam, Trevor Back, Geraint Rees, Rosalind Raine, Christopher Laing

Affiliations

  1. Centre for Human Health and Performance, University College London, 170 Tottenham Court Road, London, W1T 7HA, UK.
  2. Institute of Sport, Exercise and Health, London, W1T 7HA, UK.
  3. Department of Applied Health Research, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.
  4. Population Health Research Institute, St George's, University of London, Cranmer Terrace, London, SW17 0RE, UK.
  5. Royal Free London NHS Foundation Trust, Pond Street, London, NW3 2QG, UK.
  6. DeepMind Health, 5 New Street Square, London, EC4A 3TW, UK.
  7. University College London, Gower Street, London, WC1E 6BT, UK.

PMID: 28751970 PMCID: PMC5510018 DOI: 10.12688/f1000research.11637.2

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).

Keywords: AKI; acute kidney injury; e-alert; nephrology

Conflict of interest statement

Competing interests: CL, HM, GR, and RR are paid clinical advisors to DeepMind. AC’s clinical research fellowship is part-funded by DeepMind. DeepMind will remain independent from the collection and a

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