Integrating Algorithm Driven Analytics and Clinical Decision Support in Remote Monitoring in Automated Peritoneal Dialysis: Patient and Clinician Experiences

Background Remote monitoring programs for kidney failure patients undergoing automated peritoneal dialysis (APD-RMP) are increasing worldwide and improving clinical outcomes. This study evaluated both patient-reported perceptions and experiences of healthcare professionals when using the new Sharesource Analytics 1.0 APD-RMP platform and generated proposals for easily implemented decision rules. Methods This prospective observational study of 284 adult patients receiving APD-RMP and switching to the Sharesource Analytics 1.0 platform was conducted from March 1 to April 12, 2024, in six dialysis centers. Patient-reported experience was measured using the Kidney PREM survey, and healthcare usability was measured using the Telehealth Usability Questionnaire. Expert consensus and focus group techniques were used to create decision rules in response to data presented in the Sharesource Analytics 1.0 platform. Results Patients rated their overall experience with the service provided by their dialysis center at the end of the study period as 6.9 (SD 0.3), with seven being the best possible score. Nephrologists and nurses rated their satisfaction with the new tool at 6.8 (SD 0.3) and its usability at 6.8 (SD 0.3); the maximum possible score was 7. Twenty-seven healthcare professionals (20 women), including nephrologists and nurses, participated in the expert consensus and focus group, which - based on type of alarm, findings and causes, and review of possible actions - proposed decision rules for interventions. Conclusions Care delivered using a remote monitoring platform with analytics was associated with high patient-reported experience ratings and very good usability and satisfaction ratings from healthcare professionals. Integrating structured decision rules alongside remote analytics could facilitate a more proactive, personalized, and efficient APD-RMP care.