Trajectories of Diabetes Medication Adherence and Hospitalization Risk: A Retrospective Cohort Study in a Large State Medicaid Program

Abstract

BACKGROUND: Numerous interventions are available to boost medication adherence, but the targeting of these interventions often relies on crude measures of poor adherence. Group-based trajectory models identify individuals with similar longitudinal prescription filling patterns. Identifying distinct adherence trajectories may be more useful for targeting interventions, although the association between adherence trajectories and clinical outcomes is unknown. OBJECTIVE: To examine the association between adherence trajectories for oral hypoglycemics and subsequent hospitalizations among diabetes patients. DESIGN: Retrospective cohort study. PATIENTS: A total of 16,256 Pennsylvania Medicaid enrollees, non-dually eligible for Medicare, initiating oral hypoglycemics between 2007 and 2009. MAIN MEASURES: We used group-based trajectory models to identify trajectories of oral hypoglycemics in the 12 months post-treatment initiation, using monthly proportion of days covered (PDC) as the adherence measure. Multivariable Cox proportional hazard models were used to examine the association between trajectories and time to first diabetes-related hospitalization/emergency department (ED) visits in the following year. We used the C-index to compare prediction performance between adherence trajectories and dichotomous cutpoints (annual PDC <80 vs. ≥80 %). RESULTS: The mean annual PDC was 0.58 (SD 0.32). Seven trajectories were identified: perfect adherers (9 % of the cohort), nearly perfect adherers (31.4 %), moderate adherers (21.0 %), low adherers (11.0 %), late discontinuers (6.8 %), early discontinuers (9.7 %), and non-adherers with only one fill (11.1 %). Compared to perfect adherers, trajectories of moderate adherers (HR = 1.48, 95 % CI 1.25, 1.75), low adherers (HR = 1.51, 95 % CI 1.25, 1.83), and non-adherers with only one fill (HR = 1.35, 95 % CI 1.09, 1.67) had greater risk of diabetes-related hospitalizations/ED visits. Predictive accuracy was improved using trajectories compared to dichotomized cutpoints (C-index = 0.714 vs. 0.652). CONCLUSIONS: Oral hypoglycemic treatment trajectories were highly variable in this large Medicaid cohort. Low and moderate adherers and those filling only one prescription had a modestly higher risk of hospitalizations/ED visits compared to perfect adherers. Trajectory models may be valuable in identifying specific non-adherence patterns for targeting interventions.

The myths of medication adherence

“…To take advantage of repeated measurements, advanced statistical methods can be applied to data obtained with a variety of measurement methods (eg, electronic medication monitoring, refill adherence, self‐report). One such method is group‐based trajectory models (GBTM) . Modi and colleagues applied this technique to examine patterns of nonadherence to antiepileptic medications in children, assessed by electronic drug monitoring .…”

The association between pharmacy refill-adherence metrics and healthcare utilisation: a prospective cohort study of older hypertensive adults

“…However, it must be noted that these studies categorised patients into different adherence groups using various PDC thresholds, whereas we treated PDC as a continuous variable in regression analyses as is now recommended . More recently, a growing number of medication adherence studies have recommended GBTM over PDC . An advantage of GBTM is the grouping of patients based on similar patterns of adherence rather than an arbitrary threshold often employed with PDC .…”

“…An advantage of GBTM is the grouping of patients based on similar patterns of adherence rather than an arbitrary threshold often employed with PDC . Additionally, GBTM also provides a graphical display of longitudinal patterns of adherence, information that is lost when adherence is summarised with PDC . Only one previous study examined the association between adherence trajectory groups and healthcare utilisation.…”

“…In contrast, group‐based trajectory modelling (GBTM) is a newer modelling technique that groups patients according to their longitudinal pattern of medication refill . GBTM has demonstrated improved prediction of clinical outcomes in comparison with standard adherence‐refill metrics such as PDC, including identifying groups of patients at higher risk of hospitalisation and ED visits due to low adherence to diabetic medication . However, no study has examined the association between antihypertensive adherence trajectory groups and healthcare utilisation in a clinical setting.…”

Improving Medication Adherence: Keep Your Eyes on the Prize

“…Novel methods, such as group-based trajectory modeling, can be used to model the dynamic nature of adherence over time. 9 Furthermore, with an increasing medication burden on patients, providers will need to decide which medications to select for monitoring and how best to respond to the information collected. 10 The use of an electronic monitoring bottle for a statin is one thing-but what about a patient on five medications of critical importance, some of which are weekly injections?…”