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Hirst, Nicholas G., Whitty, Jennifer A. 
ORCID: https://orcid.org/0000-0002-5886-1933, Synnott, Robyn L., Eley, Diann S. and Scuffham, Paul A.
(2011)
Predictors of government subsidized pharmaceutical use in patients with diabetes or cardiovascular disease in a primary care setting: evidence from a prospective randomized trial.
Journal of Medical Economics, 14 (6).
pp. 698-704.
ISSN 1369-6998
Abstract
Objectives: This study uses data from a prospective randomized controlled trial to estimate predictors of pharmaceutical expenditure in diabetes (DM) or cardiovascular disease (CVD) patients. Identifying drivers of pharmaceutical use and the extent to which they are modifiable may inform cost-effective policy-making. Methods: The trial followed 260 patients aged >18 years (mean 68) from three general practices for 12 months. Patients had type 2 diabetes (90 patients) or cardiovascular disease (170 patients). Costs for pharmaceuticals prescribed on the Pharmaceutical Benefits Scheme (PBS) were obtained retrospectively at 12 months. Sociodemographic data and health-related quality-of-life (QoL) were recorded from questionnaires. Clinical measures (including body mass index (BMI), blood pressure, high and low density lipoprotein (LDL), and HbA1c) were also collected. Results: Mean pharmaceutical costs for DM patients (AU$4119) was greater than CVD patients (AU$2424). The largest contributor to costs in both groups was pharmaceuticals used for management of conditions other than CVD or DM. QoL (EQ5D) and BMI were significant predictors of costs in both groups. A history of cardiac events, HbA1c, age, and unemployment were significant predictors of costs in the DM group. A diagnosis of heart failure, frequency of hospital admissions, and LDL levels were significant predictors of costs in the CVD group. Roughly one third of total variation of costs can be explained by the regressors in both models. Limitations: Generalizability will be limited as data was derived from a trial and the study was not powered for this post-hoc analysis. Missing data imputation and self-reporting bias may also impact on results. Conclusions: Factors such as QoL BMI, HbA1c levels, and a history of cardiac events are significant predictors of costs. The results suggest there may be a place for interventions that improve quality-of-life and concurrently reduce pharmaceutical costs in patients with CVD or DM.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | drug costs,drug utilization,diabetes mellitus,cardiovascular diseases,sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being |
| Faculty \ School: | Faculty of Medicine and Health Sciences > Norwich Medical School |
| UEA Research Groups: | Faculty of Medicine and Health Sciences > Research Groups > Health Economics Faculty of Medicine and Health Sciences > Research Groups > Respiratory and Airways Group Faculty of Medicine and Health Sciences > Research Groups > Health Services and Primary Care Faculty of Medicine and Health Sciences > Research Groups > Public Health and Health Services Research (former - to 2023) |
| Depositing User: | Pure Connector |
| Date Deposited: | 27 Apr 2016 15:02 |
| Last Modified: | 15 Dec 2022 02:48 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/58444 |
| DOI: | 10.3111/13696998.2011.614304 |
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