Integrating Algorithm-Driven Analytics and Clinical Decision Support in Remote Monitoring in Automated Peritoneal...

Area of Science:

• Nephrology
• Health Informatics
• Patient Care Technology

Background:

• Automated peritoneal dialysis remote monitoring programs (APD-RMP) are expanding globally.
• These programs aim to improve clinical outcomes for kidney failure patients.
• The Sharesource Analytics 1.0 platform represents a new advancement in APD-RMP.

Purpose of the Study:

• To evaluate patient-reported perceptions and healthcare professional experiences with the Sharesource Analytics 1.0 APD-RMP platform.
• To generate proposals for easily implementable decision rules for APD-RMP data.
• To assess the usability and satisfaction of a new remote monitoring platform.

Main Methods:

• Prospective observational study involving 284 adult patients on APD-RMP switching to Sharesource Analytics 1.0.
• Patient experience measured via Kidney PREM survey; healthcare usability via Telehealth Usability Questionnaire.
• Expert consensus and focus groups with 27 healthcare professionals to develop decision rules.

Main Results:

• Patients reported high overall experience (6.9/7).
• Nephrologists and nurses reported high satisfaction (6.8/7) and usability (6.8/7) with the platform.
• Decision rules for interventions were proposed based on alarm data, findings, causes, and actions.

Conclusions:

• Remote monitoring with analytics is linked to high patient experience and healthcare professional satisfaction.
• Structured decision rules can enhance the proactivity, personalization, and efficiency of APD-RMP.
• The Sharesource Analytics 1.0 platform demonstrates strong potential for improving APD-RMP care.