Spatial access to Emergency General Surgery (EGS) services and EGS bypass behaviours in California

Figures & data

Table 1. Descriptive Analysis of Covariates of EGS bypass behaviours.

Variable	Bypass/Total	Rate (%)	P Value
ZCTA Level Variable
SPAR
Q1 (0–0.370)	8,526/14,529	58.68	p<0.001
Q2 (0.371–0.970)	30,478/97,952	31.12
Q3 (0.971–1.519)	32,561/157,062	20.73
Q4 (1.520–3.129)	19,505/170,979	11.41
Rural-Urban Status
Urban	73,735/399,301	18.47	p<0.001
Rural	17,335/41,221	42.05
Poverty Rate
Q1 (0–0.080)	20,518/8,6045	23.85	p<0.001
Q2 (0.081–0.133)	21,538/102,432	21.03
Q3 (0.134–0.216)	28,471/143,065	19.90
Q4 (0.217–1)	20,543/108,980	18.85
Individual Level Variable
Age
Q1 (18–41)	23,505/110,796	21.21	p<0.001
Q2 (42–56)	23,905/111,105	21.52
Q3 (57–71)	24,880/114,206	21.79
Q4 (72+)	18,780/104,415	17.99
Sex
Male	41,759/201,746	20.70	p=0.703
Female	49,311/238,776	20.65
Race/Ethnicity
Non-Hispanic White	46,431/208,334	22.29	p<0.001
Non-Hispanic Black	6,094/31,923	19.09
Hispanic	29,202/148,675	19.64
Asian/Pacific Islander	6,214/35,559	17.48
Native American	351/1,363	25.75
Other	2,778/14,668	18.94
Health Insurance Type
Medicare	31,312/159,868	19.59	p<0.001
Medi-Cal/Medicaid	24,118/135,588	17.79
Private	31,081/122,464	25.38
Self pay	2,562/13,043	19.64
Other payer	1,997/9,559	20.89
Disease complexity
Noncomplex	86,509/421,740	20.51	p<0.001
Complex	4,561/18,782	24.28
Hospital Inpatient Surgical Volume
Q1 (35–1736)	16,328/110,353	14.80	p<0.001
Q2 (1737–3131)	22,347/111,659	20.01
Q3 (3132–5277)	21,045/111,099	18.94
Q4 (5278–15679)	31,350/107,411	29.19

Note: Continuous variables were categorized into quartiles for the convenience of description; p value by logistic regression for continuous variables and chi-square test for categorical variables.

Figure 1. Spatial Access Ratio (SPAR) to EGS services in California, 2014–2016 (Note: SPAR values were first calculated for CBG centroids and then interpolated to the entire state using an inverse distance weighting method; SPAR values were categorized using the Jenks natural breaks method with minor revisions, greater values of SPAR denote better spatial access).

Figure 2. Exponential mean of the structured spatial component (a: the likelihood of bypass due to spatial effect by neighboring relationships; larger values mean higher likelihood of bypass) and unstructured component (b: the likelihood of bypass due to non-spatial effect; larger values means higher probability of bypass) of the BYM2 model.

Table 2. Results of the BYM2 model.

Variable	Posterior Mean	95% Posterior Interval
Intercept	0.17	0.16–0.19
ZCTA Level Variable
SPAR	0.52	0.47–0.56
Rural-Urban Status
Urban (ref)
Rural	2.18	1.75–2.72
Poverty Rate	0.97	0.91–1.02
Individual Level Variable
Age	0.90	0.89–0.91
Sex
Male (ref)
Female	0.98	0.96–1.00
Race/Ethnicity
Non-Hispanic White (ref)
Non-Hispanic Black	1.10	1.05–1.14
Hispanic	0.93	0.90–0.95
Asian/Pacific Islander	1.04	1.00–1.08
Native American	1.01	0.87–1.18
Other	0.88	0.84–0.93
Health Insurance Type
Medicare (ref)
Medi-Cal/Medicaid	0.86	0.84–0.89
Private	1.24	1.21–1.28
Self pay	0.96	0.90–1.01
Other payer	1.01	0.95–1.08
Disease Complexity
Noncomplex (ref)
Complex	1.18	1.13–1.23
Hospital Inpatient Surgical Volume	2.27	2.24–2.30