DELAYED EFFECT APPROACH TO RESOLVE THE CARER QALY TRAP
Author(s)
Shinichi Noto, PhD1, Tetsuya Iwamoto, PhD2;
1Niigata University of Health and Welfare, Professor, Niigata, Japan, 2National Institute of Public Health, Wako-shi, Japan
1Niigata University of Health and Welfare, Professor, Niigata, Japan, 2National Institute of Public Health, Wako-shi, Japan
OBJECTIVES: The carer QALY trap refers to the phenomenon where incorporating informal caregivers' HRQoL as QALYs into cost-effectiveness analysis leads to cumulative carer QALY loss (disadvantage) that exceeds the patient's gained QALYs. This has been deemed ethically unacceptable, prompting various proposed approaches to address it. We propose a new approach to avoid this trap.
METHODS: Our approach conceptualizes a new treatment as delaying the increase in carer disadvantage that progresses in accordance with patient disease severity. This “delay effect” approach is simpler than previously proposed subtraction, addition, and loss-effect approaches, and it resolves the associated ethical dilemma. We simulated changes in QALYs using the delay effect approach, the subtraction approach, and the addition approach, assuming a progressive disease.
RESULTS: In the simulated progressive disease model, disease severity progressed through three stages—mild, moderate, and severe—each lasting five years. Patient utility values were set at 0.5, 0.4, and 0.3 for the mild, moderate, and severe stages, respectively, while carer utility values were set at 0.8, 0.65, and 0.5. Simulations assumed that the new treatment extended the mild and moderate stages by one year each. The resulting changes in combined patient and carer QALYs were as follows: an increase of 0.55 QALYs under the delay effect approach (patient: +0.30; carer: +0.25), a decrease of 1.20 QALYs under the subtraction approach (patient: +0.30; carer: −1.50), and an increase of 1.75 QALYs under the addition approach (patient: +0.30; carer: +1.45).
CONCLUSIONS: The delay effect approach resolves the carer QALY trap by recognizing that treatments that prolong patient survival also delay the onset of severe caregiving burden. This approach alleviates the ethical dilemma whereby strict “QALY maximization” rules may render life-prolonging treatments less favorable for adoption. Moreover, it shows promise as a practical and ethically coherent guideline for the health technology assessment of new treatments.
METHODS: Our approach conceptualizes a new treatment as delaying the increase in carer disadvantage that progresses in accordance with patient disease severity. This “delay effect” approach is simpler than previously proposed subtraction, addition, and loss-effect approaches, and it resolves the associated ethical dilemma. We simulated changes in QALYs using the delay effect approach, the subtraction approach, and the addition approach, assuming a progressive disease.
RESULTS: In the simulated progressive disease model, disease severity progressed through three stages—mild, moderate, and severe—each lasting five years. Patient utility values were set at 0.5, 0.4, and 0.3 for the mild, moderate, and severe stages, respectively, while carer utility values were set at 0.8, 0.65, and 0.5. Simulations assumed that the new treatment extended the mild and moderate stages by one year each. The resulting changes in combined patient and carer QALYs were as follows: an increase of 0.55 QALYs under the delay effect approach (patient: +0.30; carer: +0.25), a decrease of 1.20 QALYs under the subtraction approach (patient: +0.30; carer: −1.50), and an increase of 1.75 QALYs under the addition approach (patient: +0.30; carer: +1.45).
CONCLUSIONS: The delay effect approach resolves the carer QALY trap by recognizing that treatments that prolong patient survival also delay the onset of severe caregiving burden. This approach alleviates the ethical dilemma whereby strict “QALY maximization” rules may render life-prolonging treatments less favorable for adoption. Moreover, it shows promise as a practical and ethically coherent guideline for the health technology assessment of new treatments.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
MSR150
Topic
Methodological & Statistical Research
Topic Subcategory
PRO & Related Methods
Disease
SDC: Geriatrics