Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Jul 15;21(7):e13147.
doi: 10.2196/13147.

Implementation of a Digitally Enabled Care Pathway (Part 1): Impact on Clinical Outcomes and Associated Health Care Costs

Alistair Connell  1   2 , Rosalind Raine  3 , Peter Martin  3 , Estela Capelas Barbosa  3 , Stephen Morris  3 , Claire Nightingale  3   4 , Omid Sadeghi-Alavijeh  5 , Dominic King  2 , Alan Karthikesalingam  2 , Cían Hughes  2 , Trevor Back  2 , Kareem Ayoub  2 , Mustafa Suleyman  2 , Gareth Jones  5 , Jennifer Cross  5 , Sarah Stanley  5 , Mary Emerson  5 , Charles Merrick  5 , Geraint Rees  6 , Hugh Montgomery #  1 , Christopher Laing #  5
Affiliations

Implementation of a Digitally Enabled Care Pathway (Part 1): Impact on Clinical Outcomes and Associated Health Care Costs

Alistair Connell et al. J Med Internet Res. .

Abstract

Background: The development of acute kidney injury (AKI) in hospitalized patients is associated with adverse outcomes and increased health care costs. Simple automated e-alerts indicating its presence do not appear to improve outcomes, perhaps because of a lack of explicitly defined integration with a clinical response.

Objective: We sought to test this hypothesis by evaluating the impact of a digitally enabled intervention on clinical outcomes and health care costs associated with AKI in hospitalized patients.

Methods: We developed a care pathway comprising automated AKI detection, mobile clinician notification, in-app triage, and a protocolized specialist clinical response. We evaluated its impact by comparing data from pre- and postimplementation phases (May 2016 to January 2017 and May to September 2017, respectively) at the intervention site and another site not receiving the intervention. Clinical outcomes were analyzed using segmented regression analysis. The primary outcome was recovery of renal function to ≤120% of baseline by hospital discharge. Secondary clinical outcomes were mortality within 30 days of alert, progression of AKI stage, transfer to renal/intensive care units, hospital re-admission within 30 days of discharge, dependence on renal replacement therapy 30 days after discharge, and hospital-wide cardiac arrest rate. Time taken for specialist review of AKI alerts was measured. Impact on health care costs as defined by Patient-Level Information and Costing System data was evaluated using difference-in-differences (DID) analysis.

Results: The median time to AKI alert review by a specialist was 14.0 min (interquartile range 1.0-60.0 min). There was no impact on the primary outcome (estimated odds ratio [OR] 1.00, 95% CI 0.58-1.71; P=.99). Although the hospital-wide cardiac arrest rate fell significantly at the intervention site (OR 0.55, 95% CI 0.38-0.76; P<.001), DID analysis with the comparator site was not significant (OR 1.13, 95% CI 0.63-1.99; P=.69). There was no impact on other secondary clinical outcomes. Mean health care costs per patient were reduced by £2123 (95% CI -£4024 to -£222; P=.03), not including costs of providing the technology.

Conclusions: The digitally enabled clinical intervention to detect and treat AKI in hospitalized patients reduced health care costs and possibly reduced cardiac arrest rates. Its impact on other clinical outcomes and identification of the active components of the pathway requires clarification through evaluation across multiple sites.

Keywords: acute kidney injury; nephrology.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: CL, HM, GR, and RR are paid clinical advisors to DeepMind. AC’s clinical research fellowship was part-funded by DeepMind, where he has been a full-time employee since May 2018. DeepMind remained independent from the collection and analysis of all data. CL was a member of the NICE clinical guideline 169 development group referenced in the article. HM coholds a patent on a fluid delivery device, which might ultimately help in preventing some (dehydration-related) cases of AKI occurring.

DeepMind was acquired by Google in 2014 and is now part of the Alphabet group. The deployment of Streams app at RFH was the subject of an investigation by the Information Commissioner’s Office in 2017. RFH has since published an audit completed to comply with undertakings following this investigation [39]. In November 2018, it was announced that the Streams app team will be joining Google as part of a wider health effort [40].

Figures

Figure 1
Figure 1
Defining the final evaluation sample. AKI: acute kidney injury; ITU: intensive treatment unit.
Figure 2
Figure 2
Weekly recovery rate at Royal Free Hospital (RFH) and Barnet General Hospital (BGH) before and after implementation of the care pathway. Individual data points reflect the rate of each outcome for a single week. Solid lines indicate fitted values from the modeling functions.
Figure 3
Figure 3
Cardiac arrests at Royal Free Hospital (RFH) and Barnet General Hospital (BGH). Individual data points reflect the rate of cardiac arrest per thousand admissions for a single month. Solid lines indicate fitted values from the modeling functions.
See this image and copyright information in PMC

References

    1. Bellomo R, Kellum JA, Ronco C. Acute kidney injury. Lancet. 2012 Aug 25;380(9843):756–66. doi: 10.1016/S0140-6736(11)61454-2.S0140-6736(11)61454-2 - DOI - PubMed
    1. Zeng X, McMahon GM, Brunelli SM, Bates DW, Waikar SS. Incidence, outcomes, and comparisons across definitions of AKI in hospitalized individuals. Clin J Am Soc Nephrol. 2014 Jan;9(1):12–20. doi: 10.2215/CJN.02730313. http://cjasn.asnjournals.org/cgi/pmidlookup?view=long&pmid=24178971 CJN.02730313 - DOI - PMC - PubMed
    1. Metcalfe W, Simpson M, Khan IH, Prescott GJ, Simpson K, Smith WC, MacLeod AM, Scottish Renal Registry Acute renal failure requiring renal replacement therapy: incidence and outcome. QJM. 2002 Sep;95(9):579–83. - PubMed
    1. Wang HE, Muntner P, Chertow GM, Warnock DG. Acute kidney injury and mortality in hospitalized patients. Am J Nephrol. 2012;35(4):349–55. doi: 10.1159/000337487. https://www.karger.com?DOI=10.1159/000337487 000337487 - DOI - PMC - PubMed
    1. Chawla LS, Amdur RL, Amodeo S, Kimmel PL, Palant CE. The severity of acute kidney injury predicts progression to chronic kidney disease. Kidney Int. 2011 Jun;79(12):1361–9. doi: 10.1038/ki.2011.42. https://linkinghub.elsevier.com/retrieve/pii/S0085-2538(15)54748-0 S0085-2538(15)54748-0 - DOI - PMC - PubMed

Publication types