TY - JOUR
T1 - Projected New-Onset Cardiovascular Disease by Socioeconomic Group in Australia
AU - Hastings, Kaitlyn
AU - Marquina, Clara
AU - Morton, Jedidiah
AU - Abushanab, Dina
AU - Berkovic, Danielle
AU - Talic, Stella
AU - Zomer, Ella
AU - Liew, Danny
AU - Ademi, Zanfina
N1 - Funding Information:
Kaitlyn Hastings, Clara Marquina, Jedidiah Morton, Danielle Berkovic, Stella Talic and Zanfina Ademi have no conflicts of interest to declare. Ella Zomer declares grants from Amgen, AstraZeneca, Pfizer and Shire, outside the submitted work. Danny Liew declares previous grants, participation in advisory boards and/or receipt of honoraria from Abbvie, Amgen, Astellas, AstraZeneza, Bristol-Myers Squibb, Edwards Lifesciences, Novartis, Pfizer, Sanofi and Shire, outside the submitted work.
Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
PY - 2022/4
Y1 - 2022/4
N2 - Background: Socioeconomic status has an important effect on cardiovascular disease (CVD). Data on the economic implications of CVD by socioeconomic status are needed to inform healthcare planning. Objectives: The aim of this study was to project new-onset CVD and related health economic outcomes in Australia by socioeconomic status from 2021 to 2030. Methods: A dynamic population model was built to project annual new-onset CVD by socioeconomic quintile in Australians aged 40–79 years from 2021 to 2030. Cardiovascular risk was estimated using the Pooled Cohort Equation (PCE) from Australian-specific data, stratified for each socioeconomic quintile. The model projected years of life lived, quality- adjusted life-years (QALYs), acute healthcare medical costs, and productivity losses due to new-onset CVD. All outcomes were discounted by 5% annually. Results: PCE estimates showed that 8.4% of people in the most disadvantaged quintile were at high risk of CVD, compared with 3.7% in the least disadvantaged quintile (p < 0.001). From 2021 to 2030, the model projected 32% more cardiovascular events in the most disadvantaged quintile compared with the least disadvantaged (127,070 in SE 1 vs. 96,222 in SE 5). Acute healthcare costs in the most disadvantaged quintile were Australian dollars (AU$) 183 million higher than the least disadvantaged, and the difference in productivity costs was AU$959 million. Removing the equity gap (by applying the cardiovascular risk from the least disadvantaged quintile to the whole population) would prevent 114,822 cardiovascular events and save AU$704 million of healthcare costs and AU$3844 million of lost earnings over the next 10 years. Conclusion: Our results highlight the pressing need to implement primary prevention interventions to reduce cardiovascular health inequity. This model provides a platform to incorporate socioeconomic status into health economic models by estimating which interventions are likely to yield more benefits in each socioeconomic quintile.
AB - Background: Socioeconomic status has an important effect on cardiovascular disease (CVD). Data on the economic implications of CVD by socioeconomic status are needed to inform healthcare planning. Objectives: The aim of this study was to project new-onset CVD and related health economic outcomes in Australia by socioeconomic status from 2021 to 2030. Methods: A dynamic population model was built to project annual new-onset CVD by socioeconomic quintile in Australians aged 40–79 years from 2021 to 2030. Cardiovascular risk was estimated using the Pooled Cohort Equation (PCE) from Australian-specific data, stratified for each socioeconomic quintile. The model projected years of life lived, quality- adjusted life-years (QALYs), acute healthcare medical costs, and productivity losses due to new-onset CVD. All outcomes were discounted by 5% annually. Results: PCE estimates showed that 8.4% of people in the most disadvantaged quintile were at high risk of CVD, compared with 3.7% in the least disadvantaged quintile (p < 0.001). From 2021 to 2030, the model projected 32% more cardiovascular events in the most disadvantaged quintile compared with the least disadvantaged (127,070 in SE 1 vs. 96,222 in SE 5). Acute healthcare costs in the most disadvantaged quintile were Australian dollars (AU$) 183 million higher than the least disadvantaged, and the difference in productivity costs was AU$959 million. Removing the equity gap (by applying the cardiovascular risk from the least disadvantaged quintile to the whole population) would prevent 114,822 cardiovascular events and save AU$704 million of healthcare costs and AU$3844 million of lost earnings over the next 10 years. Conclusion: Our results highlight the pressing need to implement primary prevention interventions to reduce cardiovascular health inequity. This model provides a platform to incorporate socioeconomic status into health economic models by estimating which interventions are likely to yield more benefits in each socioeconomic quintile.
UR - http://www.scopus.com/inward/record.url?scp=85123116575&partnerID=8YFLogxK
U2 - 10.1007/s40273-021-01127-1
DO - 10.1007/s40273-021-01127-1
M3 - Article
C2 - 35037191
AN - SCOPUS:85123116575
SN - 1170-7690
VL - 40
SP - 449
EP - 460
JO - PharmacoEconomics
JF - PharmacoEconomics
IS - 4
ER -
