Antidepressant adherence in United States active duty Army Soldiers: A small descriptive study

Antidepressant Adherence Among Hispanics: Patients in an Integrated Health Care Model

Purpose

We report on antidepressant (AD) adherence among Hispanics seeking mental health services in a community primary care clinic in Texas as an ancillary outcome from a National Institutes of Health-funded study that collected data on Hispanic AD adherence over a period of two years (February 2016-February 2018). Adherence to AD medications was measured throughout the year-long trial and compared across various demographic characteristics. Since Hispanic individuals often experience stigma and cultural barriers related to AD treatment, we sought to understand what factors may increase the likelihood of non-adherence in this population.

Patients and Methods

This study focused on 69 patients who were prescribed AD medications while receiving treatment through an integrated health care model. Adherence was measured with the Patient Adherence Questionnaire, a validated 2-item questionnaire that asks patients about their medication use (missed medications or dosage changes) over the past week. We looked at patient adherence at two key time points (4-weeks and 13-weeks) and utilized logistic regression to identify factors that may increase or decrease the likelihood of adherence in Hispanic patients at a community primary care clinic.

Results

Non-adherence to AD medication was 49.3% at 4-weeks and 57% at 13-weeks post-treatment initiation. Logistic regression analyses revealed that age was the only significant predictor of AD non-adherence. As age increased, the likelihood of adherence increased by 12.2% at 13-weeks post-treatment initiation and by 11.1% at 4-weeks post-treatment initiation.

Conclusion

The likelihood of Hispanic patients to adhere to AD therapy increased with the age of the patient. Since primary care is the most likely place to be prescribed an AD for Hispanic patients, further research to better understand adherence is essential. Integrated health care interventions designed to help identify, reduce, or eliminate barriers to adherence and improve cultural understanding may help address issues of non-adherence in primary care settings.

Identifying temporal patterns of adherence to antidepressants, bisphosphonates and statins, and associated patient factors

Background

Group-based trajectory modelling (GBTM) has recently been explored internationally as an improved approach to measuring medication adherence (MA) by differentiating between alternative temporal patterns of nonadherence. To build on this international research, we use the method to identify temporal patterns of medication adherence to antidepressants, bisphosphonates or statins, and their associations with patient characteristics.

Objectives

The objectives include identification of MA types using GBTM, exploration of features and associated patient characteristics of each MA type, and identification of the advantages of GBTM compared to the traditional proportion of days covered (PDC) measure.

Data and methods

We used 45 and Up Study survey data which contains information about demographics, family, health, diet, work and lifestyle of 267,153 participants aged at least 45 years across New South Wales, Australia. This data was linked to participant records of medication use, outpatient and inpatient care, and death. Our study participants initiated use of antidepressants (9287 participants), bisphosphonates (1660 participants) or statins (10,242 participants) during 2012–2016. MA types were identified from 180-day patterns of medication use for antidepressants and 360-day patterns for bisphosphonates and statins. Multinomial and binomial logistic regressions were performed to estimate participant characteristics associated with GBTM MA and PDC MA, respectively.

Results

Three GBTM MA types were identified for antidepressants and six for bisphosphonates and statins. For all three medications, MA types included: almost fully adherent; decreasing adherence and early discontinuation. The additional nonadherent types for bisphosphonates and statins were improved adherence, low adherence and later discontinuation. Participant characteristics impacting GBTM MA and PDC MA were consistent. However, several associations were uniquely found for GBTM MA as compared to PDC MA.

Conclusion

GBTM permits clinicians, policy-makers and researchers to differentiate between alternative nonadherence patterns, allowing them to better identify patients at risk of poor adherence and tailor interventions accordingly.

•

Medication adherence was categorised using group-based trajectory modelling (GBTM).

•

GBTM categories include adherence, early discontinuation and decreasing adherence.

•

Demographic, economic, health and other factors determined GBTM categories.

•

GBTM provides additional information to better target adherence interventions.