Table 5.

Segmented logistic regression results examining impact of transition from tFFS to eFFS on FPSC ED Visits

Parameter	Unadjusted Model			Adjusted Model
	Estimatea	95% CI	P-Value	Estimate	95% CI	P-Value
Intercept (baseline ED)	−3.51	−3.53 to −3.50	< 0.0001	−3.28	−3.33 to −3.23	< 0.0001
Pre-intervention slope (secular trend, per year)	0.015	0.013 to 0.019	< 0.0001	0.018	0.015 to 0.021	< 0.0001
Change in intercept (immediate impact)	−0.011	−0.014 to −0.0070	0.0098	−0.010	−0.018 to − 0.0020	0.0128
Change in slope (gradual effect, per year)	−0.010	− 0.014 to − 0.0068	< 0.0001	−0.011	− 0.014 to − 0.0080	< 0.0001
Female physician				−0.041	− 0.089 to − 0.022	0.0123
Physician panel size
< 500				0
500–999				−0.021	−0.055 to − 0.060	0.015
1000–1999				− 0.030	−0.067 to − 0.015	0.0018
2000–2999				− 0.070	−0.098 to − 0.042	< 0.0001
> 3000				− 0.074	− 0.110 to − 0.039	< 0.0001
Foreign Trained				− 0.23	−0.27 to − 0.19	< 0.0001
Years since graduation				0.0058	0.0040 to 0.0080	< 0.0001
Patient age				−0.021	−0.022 to − 0.021	< 0.0001
Female patient				− 0.047	− 0.051 to − 0.044	< 0.0001
Adjusted Clinical Group (ACG)c
0				0
1–4				0.20	0.19 to 0.21	< 0.0001
5–9				0.79	0.77 to 0.80	< 0.0001
10+				1.53	1.52 to 1.56	< 0.0001
Income Quintileb
1				0
2				−0.12	−0.12 to 0.11	0.88
3				−0.194	−0.200 to − 0.189	< 0.0001
4				− 0.256	− 0.261 to − 0.251	< 0.0001
5				− 0.333	−0.338 to − 0.327	< 0.0001
Patient rurality
Urban				0
Suburban				0.65	0.64 to 0.65	< 0.0001
Rural				1.31	1.29 to 1.31	< 0.0001

^aEstimates represent the log odds of an FPSC ED visit

^bincome quintile represents the rank of the patient’s total household income based on the aggregate census data derived from postal code. The first quintile represents the highest incomes

^cAdjusted Clinical Groups (ACG) quantifies morbidity by grouping patients based on age and gender and all medical diagnoses in a given year. Those in group three represent represents those with the greatest morbidity