Abstract
BACKGROUND: This study investigated the application of software-based data monitoring for quality control (QC) in continuous renal replacement therapy (CRRT) management. METHODS: This single-center pre-post intervention study, conducted in three ICUs of a tertiary hospital in Shanghai, compared outcomes before (Jan-Dec 2023) and after (Jan-Dec 2024) implementing the Sharesource Connect system. Data from 9 Prismaflex CRRT machines were collected retrospectively during 2023 and prospectively on a monthly basis during 2024. Alongside the software, a comprehensive quality improvement program: (1) multidisciplinary team collaboration; (2) data-driven QC; and (3) structured training. Primary outcomes-filter lifespan, downtime percentage, delivered/prescribed dose ratio, ultrafiltration volume, and vascular access alarms-were compared. RESULTS: A total of 798 filters from 514 patients (2023) and 717 filters from 492 patients (2024) were analyzed. Key quality metrics improved significantly following implementation (2024 vs. 2023): Filter lifespan increased significantly from 20.08 ± 4.12 h to 24.08 ± 4.27 h (P = 0.043), Kaplan-Meier analysis demonstrated improved filter survival (Log-Rank p < 0.001). Cumulative survival increased from 2023 to 2024 at key time points: 12 h (69.1%-87.2%, + 18.1%), 24 h (30.9%-34.6%, + 3.7%), and 36 h (5.6%-13.6%, + 8.0%), with consistent improvements observed. Downtime percentage decreased from 39 to 28% (P = 0.015), reducing non-effective treatment time by 11 percentage points. The delivered/prescribed dose ratio increased from 82 to 86% (P = 0.046). The mean delivered dose was 35.67 ± 4.01 mL/kg/h (prescribed: 41.33 ± 4.5 mL/kg/h). Ultrafiltration volume remained stable (3.13 ± 0.37 vs. 3.52 ± 0.44 L/treatment day, P = 0.058). There was no significant difference in vascular access alarms (3.39 ± 1.44 vs. 2.93 ± 0.73 events/day, P = 0.392). CONCLUSION: The Sharesource Connect system could be used for the monitoring, collection, and analysis of CRRT data to assist in the QC management related to CRRT, so as to provide a software basis for further multi-center studies or random control trials on the intelligent management of critical patients undergoing CRRT.