The Impact of a Social Networking Service–Enhanced Smart Care Model on Stage 5 Chronic Kidney Disease: Quasi-Experimental Study

Abstract

Background Stage 5 chronic kidney disease (CKD) presents a high risk for dialysis initiation and for complications such as uremic encephalopathy, uremic symptoms, gastrointestinal bleeding, and infection. One of the most common barriers to health care for patients with stage 5 CKD is poor continuity of care due to unresolved communication gaps. Objective Our aim was to establish a powerful care model that includes the use of a social networking service (SNS) to improve care quality for patients with CKD and safely delay dialysis initiation. Methods We used a retrospective cohort of CKD patients aged 20-85 years who received care between 2007 and 2017 to evaluate the efficacy of incorporating an SNS into the health care system. In 2014, author F-JY, a nephrologist at the National Taiwan University Hospital Yunlin Branch, started to use an SNS app to connect with stage 5 CKD patients and their families. In cases of emergency, patients and families could quickly report any condition to F-JY. Using this app, F-JY helped facilitate productive interactions between these patients and the health care system. The intention was to safely delay the initiation of dialysis therapy. We divided patients into four groups: group 1 (G1) included patients at the study hospital during the 2007-2014 period who had contact only with nephrologists other than F-JY; group 2 (G2) included patients who visited F-JY during the 2007-2014 period before he began using the SNS app; group 3 (G3) included patients who visited nephrologists other than F-JY during the 2014-2017 period and had no interactions using the SNS; and group 4 (G4) included patients who visited F-JY during the 2014-2017 period and interacted with him using the SNS app. Results We recruited 209 patients with stage 5 CKD who had been enrolled in the study hospital’s CKD program between 2007 and 2017. Each of the four groups initiated dialysis at different times. Before adjusting for baseline estimated glomerular filtration rate (eGFR), the G4 patients had a longer time to dialysis (mean 761.7 days, SD 616.2 days) than the other groups (G1: mean 403.6 days, SD 409.4 days, P=.011 for G4 vs G1; G2: 394.8 days, SD 318.8 days, P=.04; G3: 369.1 days, SD 330.8 days, P=.049). After adjusting for baseline eGFR, G4 had a longer duration for each eGFR drop (mean 84.8 days, SD 65.1 days) than the other groups (G1: mean 43.5 days, SD 45.4 days, P=.005; G2: mean 42.5 days, SD 26.5 days, P=.03; G3: mean 3.8.7 days, SD 33.5 days, P=.002). Conclusions The use of an SNS app between patients with stage 5 CKD and their physicians can reduce the communication gap between them and create benefits such as prolonging time-to-dialysis initiation. The role of SNSs and associated care models should be further investigated in a larger population.