Table 3.

Estimated out-of-pocket spending for the index prescription fill by spending quartile^*

Spending outcomes	Fully insured		Self-funded		Unadjusted difference-in-differences		Adjusted difference-in-differences
	Preparity	Postparity	Preparity	Postparity	DD, $	95% CI, $	aDD, $	95% CI, $	P †
TKIs, n	523	432	638	489	—	—	—	—	—
Mean‡	$480	$498	$312	$507	−178	−369 to 12.92	−74	−268 to 120	.46
25th percentile	$37	$0	$29	$30	−38	−38 to −37	−35	−35 to −34	<.001
50th percentile	$44	$20	$46	$55	−34	−44 to −25	−17	−24 to −9	<.001
75th percentile	$273	$88	$103	$150	−232	−342 to −122	−181	−270 to −91	<.001
90th percentile	$1736	$2621	$920	$1805	−381	−1206 to 444	−96	−741 to 549	.77
95th percentile	$2488	$3566	$1877	$2956	−187	−1198 to 824	73	−343 to 1289	.26
Immunomodulatory agents, n	523	432	638	489	—	—	—	—	—
Mean	$493	$474	$369	$433	−82	−248 to 83	−14	−186 to 158	.87
25th percentile	$41	$0	$35	$16	−23	−23 to −23	−24	−24 to −24	<.001
50th percentile	$65	$4	$61	$58	−59	−67 to −50	−33	−42 to −23	<.001
75th percentile	$118	$110	$119	$122	−12	−49 to 26	3	−32 to 37	.88
90th percentile	$2230	$2539	$961	$1475	−205	−1100 to 690	833	219 to 1448	.008
95th percentile	$3060	$3240	$2224	$2841	−438	−1100 to 225	115	−492 to 722	.71

^*Quantile regression was estimated using PROC QUANTREG in SAS 9.4. Both models were adjusted using inverse probability of treatment propensity score weights. DD = diference-in-differences; TKI = tryosine kinase inhibitor.

^†Two-sided difference-in-difference P value.

^‡Means were estimated via linear regression using a generalized estimating equation with an identity link and normal distribution. Models were estimated using PROC GENMOD in SAS 9.4.