Sabrina Milan Manani1,2, Mitchell H Rosner3, Grazia Maria Virzì4,5, Anna Giuliani1,2, Sonia Berti1,2, Carlo Crepaldi1,2, Claudio Ronco1,2,6. 1. Department of Nephrology, Dialysis and Transplant, San Bortolo Hospital, Vicenza, Italy. 2. IRRIV-International Renal Research Institute Vicenza, Vicenza, Italy. 3. Division of Nephrology, University of Virginia Health System, Charlottesville, Virginia, USA. 4. Department of Nephrology, Dialysis and Transplant, San Bortolo Hospital, Vicenza, Italy, graziamaria.virzi@gmail.com. 5. IRRIV-International Renal Research Institute Vicenza, Vicenza, Italy, graziamaria.virzi@gmail.com. 6. Full Professor of Nephrology, Department of Medicine, University of Padua, Padua, Italy.
Abstract
BACKGROUND: Peritoneal dialysis (PD) is an ideal model for testing remote monitoring (RM). In this study, we evaluated the RM application longitudinally in stable patients undergoing automated PD (APD). METHODS: This was an observational study, comparing outcomes in patients with (current patients) and without (historical data) exposure of RM. We analyzed cost-effectiveness of RM-APD measuring the number of night alarms, number of hospital visits, direct and indirect costs. RESULTS: Changes in APD prescription were almost double in the case group (RM) compared to the control group (p = 0.0005). The need for in-person visits and nocturnal alarms was significantly less in RM-APD than in traditional APD (p = 0.01 and p = 0.002, respectively). The distance traveled by patients in the case of RM-APD was reduced by 1,134 km with a time saving of 1,554 min for patients. The overall cost reduction for the PD center in terms of time/nurse and time/physician was 2,647 and 3,673 min, respectively. All these advantages were obtained in the presence of an improved technique survival with a significant reduction of dropouts. All patients found that it is easy to use the RM system and were satisfied with the high level of interaction with the care team and with the possibility of timely resolving technical problems. CONCLUSION: These data confirm the long-term benefits of RM applied to APD. RM-APD is cost-effective; it allows early detection and resolution of problems, improved treatment compliance, reduction of patient's access to hospital center for technical and clinical complications with consequent savings, and improved patient's quality of life.
BACKGROUND: Peritoneal dialysis (PD) is an ideal model for testing remote monitoring (RM). In this study, we evaluated the RM application longitudinally in stable patients undergoing automated PD (APD). METHODS: This was an observational study, comparing outcomes in patients with (current patients) and without (historical data) exposure of RM. We analyzed cost-effectiveness of RM-APD measuring the number of night alarms, number of hospital visits, direct and indirect costs. RESULTS: Changes in APD prescription were almost double in the case group (RM) compared to the control group (p = 0.0005). The need for in-person visits and nocturnal alarms was significantly less in RM-APD than in traditional APD (p = 0.01 and p = 0.002, respectively). The distance traveled by patients in the case of RM-APD was reduced by 1,134 km with a time saving of 1,554 min for patients. The overall cost reduction for the PD center in terms of time/nurse and time/physician was 2,647 and 3,673 min, respectively. All these advantages were obtained in the presence of an improved technique survival with a significant reduction of dropouts. All patients found that it is easy to use the RM system and were satisfied with the high level of interaction with the care team and with the possibility of timely resolving technical problems. CONCLUSION: These data confirm the long-term benefits of RM applied to APD. RM-APD is cost-effective; it allows early detection and resolution of problems, improved treatment compliance, reduction of patient's access to hospital center for technical and clinical complications with consequent savings, and improved patient's quality of life.
Authors: Orla O'Carroll; Rachel MacCann; Aoife O'Reilly; Eleanor M Dunican; Eoin R Feeney; Silke Ryan; Aoife Cotter; Patrick W Mallon; Michael P Keane; Marcus W Butler; Cormac McCarthy Journal: Eur Respir J Date: 2020-08-13 Impact factor: 16.671
Authors: Hasan H Yeter; Ebru Gok Oguz; Omer F Akcay; Refika Karaer; Emre Yasar; Murat Duranay; Mehmet D Ayli; Galip Guz Journal: Semin Dial Date: 2020-11-19 Impact factor: 2.886