Abstract
Background:
Understanding relationships between polypharmacy, treatment burden and other factors (e.g. age, knowledge of medicines), could inform interventions to reduce treatment burden.
Aim:
To explore sociodemographic, clinical and medication factors associated with high treatment burden.
Design and setting:
Secondary analysis of multi-centre UK primary care baseline clinical trial data.
Methods:
Participants were ≥18 years, prescribed ≥5 repeat medicines with ≥1 indicator of potentially inappropriate prescribing (PIP). Survey data captured treatment burden (13-item Multimorbidity Treatment Burden Questionnaire; dichotomised with high burden ≥22), sociodemographic characteristics, quality of life, self-reported knowledge of medicines, and medication adherence. Electronic health records provided data on age, gender, long-term conditions, PIP, medicines use (last 3 months), and consultations (last 12 months). Associations between treatment burden and other factors were modelled using multivariable logistic regression.
Results:
1711 adults from 37 general practices were included (mean age 72 years, 51% male). 381 (23%) reported high treatment burden. Multivariable analysis found high treatment burden was associated with younger age, being unemployed or in paid work, university or high education, multimorbidity, anxiety/depression, polypharmacy (≥8 medicines), lower medication adherence, knowledge of medicines, and quality of life. There was strong evidence (p<0.005) that the association between high treatment burden and polypharmacy was greater in people aged <60 years, those with poor knowledge of medicines, more multimorbidity, and those with low/moderate medication adherence.
Conclusion:
High treatment burden was more common in adults with polypharmacy who were younger, had multimorbidity, poor medication knowledge, or low adherence. This should inform design of interventions addressing treatment burden.
Understanding relationships between polypharmacy, treatment burden and other factors (e.g. age, knowledge of medicines), could inform interventions to reduce treatment burden.
Aim:
To explore sociodemographic, clinical and medication factors associated with high treatment burden.
Design and setting:
Secondary analysis of multi-centre UK primary care baseline clinical trial data.
Methods:
Participants were ≥18 years, prescribed ≥5 repeat medicines with ≥1 indicator of potentially inappropriate prescribing (PIP). Survey data captured treatment burden (13-item Multimorbidity Treatment Burden Questionnaire; dichotomised with high burden ≥22), sociodemographic characteristics, quality of life, self-reported knowledge of medicines, and medication adherence. Electronic health records provided data on age, gender, long-term conditions, PIP, medicines use (last 3 months), and consultations (last 12 months). Associations between treatment burden and other factors were modelled using multivariable logistic regression.
Results:
1711 adults from 37 general practices were included (mean age 72 years, 51% male). 381 (23%) reported high treatment burden. Multivariable analysis found high treatment burden was associated with younger age, being unemployed or in paid work, university or high education, multimorbidity, anxiety/depression, polypharmacy (≥8 medicines), lower medication adherence, knowledge of medicines, and quality of life. There was strong evidence (p<0.005) that the association between high treatment burden and polypharmacy was greater in people aged <60 years, those with poor knowledge of medicines, more multimorbidity, and those with low/moderate medication adherence.
Conclusion:
High treatment burden was more common in adults with polypharmacy who were younger, had multimorbidity, poor medication knowledge, or low adherence. This should inform design of interventions addressing treatment burden.
| Original language | English |
|---|---|
| Journal | Journal of Multimorbidity and Comorbidity |
| Publication status | Accepted/In press - 4 Jan 2026 |