Digital Health Support: Current Status and Future Development for Enhancing Dialysis Patient Care and Empowering Patients.
Bernard CanaudAndrew DavenportHélène Leray-MoraguesMarion MorenaJean-Paul CristolJeroen KoomanPeter KotankoPublished in: Toxins (2024)
Chronic kidney disease poses a growing global health concern, as an increasing number of patients progress to end-stage kidney disease requiring kidney replacement therapy, presenting various challenges including shortage of care givers and cost-related issues. In this narrative essay, we explore innovative strategies based on in-depth literature analysis that may help healthcare systems face these challenges, with a focus on digital health technologies (DHTs), to enhance removal and ensure better control of broader spectrum of uremic toxins, to optimize resources, improve care and outcomes, and empower patients. Therefore, alternative strategies, such as self-care dialysis, home-based dialysis with the support of teledialysis, need to be developed. Managing ESKD requires an improvement in patient management, emphasizing patient education, caregiver knowledge, and robust digital support systems. The solution involves leveraging DHTs to automate HD, implement automated algorithm-driven controlled HD, remotely monitor patients, provide health education, and enable caregivers with data-driven decision-making. These technologies, including artificial intelligence, aim to enhance care quality, reduce practice variations, and improve treatment outcomes whilst supporting personalized kidney replacement therapy. This narrative essay offers an update on currently available digital health technologies used in the management of HD patients and envisions future technologies that, through digital solutions, potentially empower patients and will more effectively support their HD treatments.
Keyphrases
- end stage renal disease
- chronic kidney disease
- healthcare
- ejection fraction
- newly diagnosed
- artificial intelligence
- public health
- palliative care
- prognostic factors
- primary care
- mental health
- decision making
- deep learning
- patient reported outcomes
- metabolic syndrome
- skeletal muscle
- risk assessment
- pain management
- adipose tissue
- high throughput
- insulin resistance
- chronic pain
- smoking cessation
- human health