Big Data-Enabled Analysis of Factors Affecting Patient Waiting Time in the Nephrology Department of a Large Tertiary Hospital

Table 3

Analysis of linear regression model of the waiting time and factors.

Variables	Unstandardized coefficient		Standardization coefficient			95% confidence interval
		Standard error
Intercept	5.647	1.087	0.066	1.353	0.1762	(–0.030, 0.162)
Gender (male)	0.527	0.266	0.024	1.978	0.048	(0.000, 0.047)
WIAC
Thursday	0.042	0.473	0.002	0.088	0.930	(–0.040, 0.044)
Monday	–0.839	0.453	–0.038	–1.853	0.064	(–0.078, 0.002)
Sunday	–4.244	1.328	–0.191	–3.195	0.001	(–0.309, –0.074)
Saturday	1.704	0.777	0.077	2.194	0.028	(0.008, 0.146)
Wednesday	0.136	0.463	0.006	0.294	0.769	(–0.035, 0.047)
Tuesday	–0.777	0.476	–0.035	–1.633	0.103	(–0.077, 0.007)
APA (Afternoon)	1.057	0.268	0.048	3.941	0.000	(0.024, 0.071)
RI	0.789	0.007	0.724	121.349	0.000	(0.712, 0.736)
TD
Renal biopsy	–3.091	0.741	–0.139	–4.172	0.000	(–0.205, –0.074)
Peritoneal dialysis	–0.520	0.351	–0.023	–1.481	0.139	(–0.054, 0.008)
Vascular access	–0.373	0.350	–0.017	–1.066	0.286	(–0.048, 0.014)
After renal transplant	1.212	0.722	0.055	1.679	0.093	(–0.009, 0.119)
NDD
2 diagnoses	–1.445	0.993	–0.065	–1.455	0.146	(–0.154, 0.022)
3 diagnoses	–1.472	1.22	–0.065	–1.206	0.228	(–0.176, 0.040)
≥4 diagnoses	–2.156	1.035	–0.097	–2.082	0.037	(–0.190, –0.007)

Note. Bold fields indicate statistically significant variables.