Date of Award
2016
Degree Type
Thesis
Degree Name
Master of Science in Pharmaceutical Sciences
Department
Biomedical and Pharmaceutical Sciences
First Advisor
Stephen Kogut
Abstract
Depression is a significant problem for the managed care system. Antidepressant medication helps ameliorate the symptoms of depression yet adherence to medication is known to be poor. The current approach to adherence measurement (i.e HEDIS) is limited or lacking. Other methods are used (e.g Proportion of Days Covered –PDC) in other chronic diseases to measure adherence. Medication adherence is a growing concern for clinicians and other health care stakeholders (e.g payer) because of the increasing evidence that non-adherence is prevalent and places patients at an increased risk for adverse health outcomes and higher cost of care.
We conducted a retrospective cohort study of patients enrolled in a Medicaid plan. For the inclusion in the study population patients had to meet HEDIS inclusion criteria and PDC respectively. Patients included in the HEDIS study’s cohort were adults at least 18 years of age with a new diagnosis of depression confirmed by outpatient medication use and an ICD-9 diagnostic code. The upper limit age was set at 75 years old in order to maintain the hidden information about the patients. Patients had to meet certain enrollment eligibility criteria as well. For the PDC study population patients met the same age requirement as for the HEDIS measurement inclusion criteria. Patients included in the study for the PDC cohort were not required to have a new diagnosis of depression certified by a diagnostic code; they only had to be antidepressant medication users during the study period. We evaluated antidepressant medication adherence by applying the HEDIS measures and PDC measures. The measure of effect was the odds ratio in separate models. We also applied HEDIS measures to the PDS cohort to be provide a head-to-head comparison of the rates of adherence. Adherence was assessed with seven medication classes as recommended by HEDIS: Miscellaneous Antidepressants Monoamine Oxidase Inhibitors (MAOIs) Phenylpiperazine Antidepressants Selective Serotonin-Norepinephrine Reuptake Inhibitors Antidepressants (SSNRIs) Selective Serotonin Reuptake Inhibitors Antidepressants (SSRIs) Tetracyclic Antidepressants (TeCAs) Tricyclic Antidepressants (TCAs). Differences in baseline characteristics and the odds of adherence were assessed between the groups for each methodology separately as well as patient demographic and health related variables. We constructed multivariate logistic regression models to measure the odds of adherence with antidepressant medication for each methodology while controlling for potential confounders and assessing for interaction terms. The level of significance and the corresponding 95% confidence intervals of the odds were presented as well.
A total of 626 eligible antidepressant users were identified according to the HEDIS criteria and 22,351 eligible antidepressant users were identified according to PDC criteria and were evaluated for adherence with antidepressant medication. In both study samples patients 50 years and older were significantly more likely to be adherent with antidepressant medication than the younger group <35 >years) patients. In both groups patients that had respiratory disease had an increased odds of adherence with antidepressant medication relative to patients that were not classified having a respiratory disease. Patients that had other mental health diagnosis in addition to depression had a statistically increased odds of adherence with antidepressant medication relative to patients that did not have such diagnoses. The beta coefficient representing the relationship between the antidepressant medication adherence and the therapy regimen was positive and statistically significant for both samples. Patients that were using more than one drug were significantly more likely to be adherent to antidepressant medication regimen than patients that were using only one type of antidepressant drugs.
Our results implicate older age and comorbid diseases such as respiratory and other mental health diseases and polymedication as risk factors associated with better adherence with antidepressant medication therapy in Medicaid insured people. Interventions that strive to improve adherence with antidepressant medication therapy should continue to be implemented and evaluated.
Recommended Citation
Telinoiu, Carmen Monica, "Measuring Adherence with Antidepressant Medication: Comparison of HEDIS and PDC Methodologies" (2016). Open Access Master's Theses. Paper 823.
https://digitalcommons.uri.edu/theses/823
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