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. 2021 May;35(5):893-903.
doi: 10.1177/0269216321999576. Epub 2021 Mar 17.

End-of-life cost trajectories and the trade-off between treatment costs and life-extension: Findings from the Cost and Medical Care of Patients with Advanced Serious Illness (COMPASS) cohort study

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End-of-life cost trajectories and the trade-off between treatment costs and life-extension: Findings from the Cost and Medical Care of Patients with Advanced Serious Illness (COMPASS) cohort study

Brett Doble et al. Palliat Med. 2021 May.

Abstract

Background: Few studies have assessed how patient preferences influence end-of-life costs.

Aim: To estimate mean monthly healthcare costs in 2019 Singapore Dollars (SGD) at five time points within the last year of life and identify how patients' preferences for the trade-off between treatment cost containment and life-extension and other factors affect these costs.

Design: Mean monthly costs were quantified in the last 1, 3, 6, 9, and 12-months before death. Univariate and multivariate analyses were conducted.

Setting/participants: Billing records for 286 deceased participants in the Cost and Medical Care of Patients with Advanced Serious Illness (COMPASS) cancer cohort study in Singapore.

Results: Mean monthly costs were $5140 (95% CI: $4750; $5520) in the 12-months before death and rose to $8350 (95% CI: $7110; $9590) 1-month before death. Participants preferring higher cost containment/less life-extension defied the trend of increasing costs closer to death (mean monthly costs of $4630 (95% CI: $3690; $ 5580) and $4850 (95% CI: $2850; $6850) (12-months and 1-month before death respectively). Participants preferring lower cost containment/more life-extension had costs that were $1050 (95% CI: $49; $2051) and $5220 (95% CI: $2320; $8130) higher than those preferring lower costs/less life-extension 12-months and 1-month before death respectively.

Conclusions: On average, cancer patients in Singapore can expect to spend $61,680 in the last year of life. Of broader relevance is that patient preferences and other observable factors clearly influence these costs, suggesting that policymakers and patients can better predict and budget for end-of-life costs by considering these factors.

Keywords: Cost; cancer; end of life; observational study; patient preference.

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