Digital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup - PubMed (original) (raw)

Review

. 2023 Dec;19(12):807-818.

doi: 10.1038/s41581-023-00744-7. Epub 2023 Aug 14.

Linda Awdishu 2, Sean M Bagshaw 3, Erin F Barreto 4, Rolando Claure-Del Granado 5 6, Barbara J Evans 7, Lui G Forni 8, Erina Ghosh 9, Stuart L Goldstein 10, Sandra L Kane-Gill 11, Jejo Koola 12, Jay L Koyner 13, Mei Liu 14, Raghavan Murugan 15 16, Girish N Nadkarni 17, Javier A Neyra 18, Jacob Ninan 19, Marlies Ostermann 20, Neesh Pannu 21, Parisa Rashidi 7, Claudio Ronco 22, Mitchell H Rosner 23, Nicholas M Selby 24 25, Benjamin Shickel 7, Karandeep Singh 26, Danielle E Soranno 27, Scott M Sutherland 28, Azra Bihorac 29, Ravindra L Mehta 30

Affiliations

Review

Digital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup

Kianoush B Kashani et al. Nat Rev Nephrol. 2023 Dec.

Abstract

Acute kidney injury (AKI), which is a common complication of acute illnesses, affects the health of individuals in community, acute care and post-acute care settings. Although the recognition, prevention and management of AKI has advanced over the past decades, its incidence and related morbidity, mortality and health care burden remain overwhelming. The rapid growth of digital technologies has provided a new platform to improve patient care, and reports show demonstrable benefits in care processes and, in some instances, in patient outcomes. However, despite great progress, the potential benefits of using digital technology to manage AKI has not yet been fully explored or implemented in clinical practice. Digital health studies in AKI have shown variable evidence of benefits, and the digital divide means that access to digital technologies is not equitable. Upstream research and development costs, limited stakeholder participation and acceptance, and poor scalability of digital health solutions have hindered their widespread implementation and use. Here, we provide recommendations from the Acute Disease Quality Initiative consensus meeting, which involved experts in adult and paediatric nephrology, critical care, pharmacy and data science, at which the use of digital health for risk prediction, prevention, identification and management of AKI and its consequences was discussed.

© 2023. Springer Nature Limited.

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Conflict of interest statement

K.B.K. received research grants from Philips Research North America and Google; speaker honorarium from Nikkiso Critical Care Medical Supplies (Shanghai) Co., Ltd; Funding from National Institute of Diabetes and Digestive and Kidney Diseases grant (R01DK131586); also reports consulting fees to Mayo Clinic from Baxter Inc. L.A. holds grant funding from the UCSD-UAB O’Brien Center for AKI (NIDDK) and Sony Electronics, Inc. S.M.B. is supported by a Canada Research Chair in Critical Care Outcomes and Systems Evaluation, and received fees for scientific advisory and speaking from Baxter, fees for scientific advisory from Novartis, fees for data safety monitoring for I-SPY-COVID, and fees for scientific advisory and adjudication from BioPorto. E.F.B. received consulting fees for FAST Biomedical, Wolters-Kluwer (unrelated), and also research support from NIH, AHRQ. R.C.-D.G. received consulting fees from Medtronic for developing CRRT educational material and a speaker honorarium from Nova Biomedical. B.J.E. did not disclose any conflicting interests. L.G.F. received research funding from Baxter, Ortho Clinical Diagnostics, NIHR. E.G. is employed in Philips Research North America and owns stock in Philips. S.L.K.-G. receives royalties from Vigilanz Corporation (Minneapolis, MN, USA) for the Nephrotoxic Injury Negated by Just-in-Time (NINJA) application licensed to Vigilanz from Cincinnati Children’s Hospital Medical Center. S.L.K.-G. receives research funding from NIDDK and NCCIH and is a member of the executive committee for the Society of Critical Care Medicine. J.L.K. received research funding from NIH, Fresenius Medical, Astute/BioMérieux; consulting fees from Baxter, Astute/BioMérieux, Novartis, Guard Therapeutic, and honoraria from ASN. M.L. received research funding from NIDDK (R01DK116986), NSF (2014554) and NCATS (UL1TR002366).

R.M. received research funding from the National Institute of Diabetes and Digestive and Kidney Diseases grant (R01DK131586), consulting fees from Baxter Inc unrelated to this study. G.N.N. received consulting fees from AstraZeneca, Reata, BioVie, Daiichi Sankyo, Qiming Capital and GLG, financial compensation as a scientific board member and adviser to Renalytix, and owns equity in Renalytix, Nexus iConnect, Data2Wisdom, and Pensieve Health as a cofounder. J.A.N. received consulting fees form Baxter, Outset, Vifor and Leadiant Biosciences, and research funding from NIDDK (R56 DK126930, R01 DK128208, U01 DK129989, and P30 DK079337). M.O. receives research funding from Fresenius Medical Care, Baxter, Biomérieux and LaJolla Pharma, and speaker honoraria from Fresenius Medical Care, Baxter, BioMérieux and Gilead. P.R. receives research funding from the National Institutes of Health (R21 AG073769, R01 GM110240, OT2 OD032701), NIH/National Institute of Biomedical Imaging and Bioengineering (R01 EB029699), NIH/National Institute of Neurological Disorders and Stroke (R01 NS120924), NIH/National Institute of Diabetes and Digestive and Kidney Diseases (R01 KD121730), and the National Science Foundation (CAREER 1750192). N.M.S. received research funding from the NIHR HS&DR Programme (NIHR131948, co-applicant), NIHR Health Technology Assessment (HTA) program (NIHR129617 Co-Chief Investigator) and speaker honoraria from GE, Fresenius and AstraZeneca, and has a provisional patent for measuring pressure waves in dialysis lines to derive continuous arterial blood pressure. K.S. receives grant funding from Blue Cross Blue Shield of Michigan and Teva Pharmaceuticals for unrelated work, and serves on a scientific advisory board for Flatiron Health (New York, NY, USA). R.L.M. receives consulting fees from Baxter, AM Pharma, BioMérieux, Mallinckrodt, GE Healthcare; Sanofi, Nova BioMed, Abiomed, Novartis, Fresenius, Renasym, Alexion, Renibus, SeaStar, Abbott, Guard. J.K., J.N., N.P., C.R., M.H.R., B.S., D.E.S., S.M.S. and A.B. declare no competing interests.

Figures

Fig. 1 |

Fig. 1 |. Categories of digital health interventions and strategies for employing digital health across the care continuum.

A digital health strategy centres around the patient and involves digital health tools deployed with intention across different settings. Importantly, because digital health can have unintended consequences, ethical, legal and social principles must be embedded into digital health solutions as they mature. Adapted from the Acute Dialysis Quality Initiative, CC BY 2.0 (

https://creativecommons.org/licenses/by/2.0/

). AI, artificial intelligence; FAIR, findable, accessible, interoperable and reusable.

Fig. 2 |

Fig. 2 |. Areas with potential impact by digital health solutions across the AKI care continuum.

Digital health solutions across the acute kidney injury (AKI) continuum could apply to the community, acute and post-acute care settings. The digital profile of individual patients, which is sourced from patient-related information, health care systems and population data, could be used to risk stratify patients for AKI, identify patients with AKI, tailor the clinical response to the risk or presence of AKI, and expedite AKI recovery in different settings. Adapted from the Acute Dialysis Quality Initiative, CC BY 2.0 (

https://creativecommons.org/licenses/by/2.0/

). AI, artificial intelligence; CKD, chronic kidney disease; FAIR, findable, accessible, interoperable and reusable; HIT, health information technology; KRT, kidney replacement therapy; mHealth, mobile health.

Fig. 3 |

Fig. 3 |. DHAKI implementation cycle.

The four phases of digital health solution implementation include exploring the need and resources, deploying the resources required for successful project conduct, implementing the digital health solution within the workflow, and finally, knowledge transfer and broader implementation of the digital health in acute kidney injury (DHAKI) solution across institutions, regions, countries and globally. Adapted from the Acute Dialysis Quality Initiative, CC BY 2.0 (

https://creativecommons.org/licenses/by/2.0/

).

Fig. 4 |

Fig. 4 |. DHAKI solution implementation steps, barriers and constraints.

Digital health in acute kidney injury care (DHAKI) implementation is conditioned by barriers, enablers and constraints that can inhibit or promote the identification of health care needs and of the appropriate choice of digital health solutions to improve the prevention, detection or treatment of AKI. These factors are also affected by health determinants and the geographical scale of implementation. Adapted from the Acute Dialysis Quality Initiative, CC BY 2.0 (

https://creativecommons.org/licenses/by/2.0/

). CKD, chronic kidney disease; Cr, creatinine; DH, digital health; ELSI, ethical, legal and social implications.

Fig. 5 |

Fig. 5 |. Interconnecting factors that restrict the choice of a DHAKI solution.

The development and implementation of digital health in acute kidney injury care (DHAKI) solutions must consider the needs that the solution must address, existing constraints, as well as the available technology choices and design approaches. A successful DHAKI solution implementation requires alignment among all of these major components. Adapted from the Acute Dialysis Quality Initiative, CC BY 2.0 (

https://creativecommons.org/licenses/by/2.0/

). Cr, creatinine; DH, digital health; ELSI, ethical, legal and social implications; IT, information technology.

References

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