OBJECTIVES : Group-based trajectory model (GBTM) has been explored internationally as an improved approach to measuring medication adherence (MA), compared to traditional methods such as proportion of days covered (PDC). It accounts for longitudinal patterns of medication consumption, allowing researchers to differentiate between alternative patterns or ‘types’ of non-adherence and to measure their effect on health outcomes. To build on this international research, we explore the use of GBTM to define MA for Australians with three chronic health conditions, depression, cardiovascular disease and osteoporosis.

METHODS : The cohort includes patients prescribed antidepressants, statins or bisphosphonates in the NSW 45 and Up Study, a large-scale study based on repeated surveys. Their survey answers, hospital records, emergency department records, mental health ambulatory records, death records, prescription filling records and primary medical service records are utilised. Adherence types are identified using the GBTM and related to adherence measured as PDC using descriptive statistics and logistic regression. The patient characteristics, health outcomes or healthcare resource use that are associated with adherence type are identified using Classification And Regression Tree (CART) and Random Forests. The identified associations are quantified using multivariate linear or logistic regression. The potential benefits of using the GBTM in measuring MA are evaluated by comparing to PDC.

RESULTS : The identified adherence types and their relationships with PDC, factors associated with adherence, and potential benefits of using the GBTM in measuring MA will be presented.

CONCLUSIONS : Our research will be the first to explore differences in MA patterns for depression, cardiovascular disease, and osteoporosis and how these patterns relate to patient characteristics, health outcomes and healthcare resource use. The research can inform the development of targeted healthcare interventions to help improve adherence, thereby leading to better health outcomes and more efficient healthcare resource use.