Table 1.

Antihypertensive adherence trajectories in the 12 months following initiation according to adherence measures

	Group size		Average probability of adherence a		Proportion days covered (PDC)		Proportion months covered (PMC)		Average posterior probability b
Trajectory group	N	%	Mean	Std	Mean	Std	Mean	Std	Mean	Std
Immediate drop-off	50,797	18.0	0.095	0.257	0.136	0.092	0.099	0.050	0.887	0.174
Rapid drop-off	22,404	7.9	0.267	0.385	0.318	0.093	0.281	0.064	0.856	0.177
Gradual drop-off	39,953	14.1	0.629	0.258	0.708	0.137	0.636	0.135	0.855	0.170
Partial drop-off	29,429	10.4	0.346	0.226	0.465	0.147	0.352	0.118	0.865	0.161
Early drop-off then rebound	28,304	10.0	0.733	0.196	0.789	0.100	0.720	0.100	0.818	0.151
Adherent	111,633	39.5	0.973	0.016	0.979	0.031	0.975	0.043	0.956	0.086
Comparison of adherence measures ability to distinguish between adherent and nonadherent months
Adherence measure	AUCc						95% Confidence interval (CI)
PDC	0.914						0.914, 0.914
PMC	0.918						0.918, 0.919
Six-group trajectory model	0.954						0.954, 0.955

Overall model BIC for 6-group trajectory model: -1300277. BIC is used as a measure of model fit. Lower BIC values signify better model fit. Logistic regression models were used to identify trajectory groups. The dependent variables were the monthly binary indicators of antihypertensive use and months since start of antihypertensive therapy were the independent variables. Time was modeled using cubic terms. Abbreviations: BIC, Bayesian information criterion.

^aAverage probability of being at least 80% adherent over 12 months of follow-up.

^bIndicates how well beneficiaries fit in their assigned group. 0.70 is typically used as a threshold to signify good model fit.

^cArea under the curve (AUC) statistics are used to quantify the ability of the measures to discriminate between adherent and nonadherent months. Values of 1 symbolize perfect discrimination.