# Leveraging ICT Tools to Improve Kidney Health: A Comprehensive Review of Innovations in Nephrology

**Authors:** Abel Mata-Lima, José Javier Serrano-Olmedo, Ana Rita Paquete

PMC · DOI: 10.3390/healthcare14060785 · Healthcare · 2026-03-20

## TL;DR

This paper reviews how digital tools like remote monitoring and AI are transforming kidney care by improving patient outcomes and making treatment more accessible.

## Contribution

The paper provides a comprehensive review of current ICT applications in nephrology and evaluates their impact on kidney care models.

## Key findings

- ICT tools such as remote monitoring and AI have improved patient outcomes and early detection of complications.
- Digital health technologies are shifting nephrology from reactive to proactive care, enhancing accessibility and clinical efficiency.

## Abstract

Background: Chronic kidney disease (CKD) and end-stage renal disease (ESRD) represent a growing global health burden, affecting nearly one in ten adults worldwide. CKD is associated with high morbidity, premature mortality, reduced quality of life and enormous healthcare costs, and is primarily driven by dialysis and kidney transplantation. The silent and progressive nature of CKD means that most patients are diagnosed late, when irreversible damage has already occurred and costly kidney replacement therapies (KRT) become necessary. Dialysis services are resource-intensive, requiring significant infrastructure, specialized staff, and consumables, which makes them especially challenging to sustain in low- and middle-income countries. Traditional models of nephrology, care center-based dialysis and fragmented follow-up are increasingly inadequate in meeting the demands of a rising CKD population. These challenges highlight the urgent need for innovative approaches that enhance efficiency, improve patient outcomes, and expand access. Objective: This review aims to analyze the current landscape of information and communication technology (ICT) applications in nephrology and to evaluate how digital innovations are reconfiguring kidney therapy. Specifically, it seeks to identify the major ICT tools that are currently in use, assess their clinical and operational impact, and discuss their role in creating more sustainable, patient-centered kidney care models. This study reviews and analyzes ICT tools that are reconfiguring nephrology, including remote monitoring, AI, wearables, patient engagement apps and data dashboards. Methods: Narrative and scoping review of recent innovations in nephrology, including remote patient monitoring (RPM), telehealth, artificial intelligence (AI) analytics, wearable sensors, and clinical decision support platforms. Results: ICT tools such as Sharesource, Versia, telenephrology platforms, medical assistant for Chronic Care Service (MACCS), AI-based predictive analytics, wearable devices and patient engagement apps have improved patient outcomes, adherence, and early detection of complications. Key metrics include technique survival, hospitalization rate, patient-reported outcomes, workflow efficiency, and prediction accuracy. The relevant literature describing the potential of digital health technologies, including ICT platforms, artificial intelligence tools, and remote monitoring systems, to transform nephrology care was retrieved and screened for inclusion in this narrative review. Conclusions: ICT has shifted nephrology from reactive to proactive care, enhancing accessibility, patient empowerment and clinical efficiency. Future directions include precision nephrology, fully wearable kidneys, AI integration and large language models for education and triage. Challenges include digital divide, regulatory heterogeneity, cost and the need for long-term evidence.

## Linked entities

- **Diseases:** end-stage renal disease (ESRD) (MONDO:0004375)

## Full-text entities

- **Diseases:** ESRD (MESH:D007676), CKD (MESH:D051436)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC13026592/full.md

## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13026592/full.md

## References

110 references — full list in the complete paper: https://tomesphere.com/paper/PMC13026592/full.md

---
Source: https://tomesphere.com/paper/PMC13026592