Better informing decision making with multiple outcomes cost-effectiveness analysis under uncertainty in cost-disutility space.
BACKGROUND
Comparing multiple, diverse outcomes with cost-effectiveness analysis (CEA) is important, yet challenging in areas like palliative care where domains are unamenable to integration with survival. Generic multi-attribute utility values exclude important domains and non-health outcomes, while partial analyses-where outcomes are considered separately, with their joint relationship under uncertainty ignored-lead to incorrect inference regarding preferred strategies.


OBJECTIVE
The objective of this paper is to consider whether such decision making can be better informed with alternative presentation and summary measures, extending methods previously shown to have advantages in multiple strategy comparison.


METHODS
Multiple outcomes CEA of a home-based palliative care model (PEACH) relative to usual care is undertaken in cost disutility (CDU) space and compared with analysis on the cost-effectiveness plane. Summary measures developed for comparing strategies across potential threshold values for multiple outcomes include: expected net loss (ENL) planes quantifying differences in expected net benefit; the ENL contour identifying preferred strategies minimising ENL and their expected value of perfect information; and cost-effectiveness acceptability planes showing probability of strategies minimising ENL.


RESULTS
Conventional analysis suggests PEACH is cost-effective when the threshold value per additional day at home (𝕜1) exceeds $1,068 or dominated by usual care when only the proportion of home deaths is considered. In contrast, neither alternative dominate in CDU space where cost and outcomes are jointly considered, with the optimal strategy depending on threshold values. For example, PEACH minimises ENL when 𝕜1=$2,000 and 𝕜2=$2,000 (threshold value for dying at home), with a 51.6% chance of PEACH being cost-effective.


CONCLUSIONS
Comparison in CDU space and associated summary measures have distinct advantages to multiple domain comparisons, aiding transparent and robust joint comparison of costs and multiple effects under uncertainty across potential threshold values for effect, better informing net benefit assessment and related reimbursement and research decisions.
Flinders Clinical Effectiveness, Flinders University, Bedford Park, South Australia, Australia 5041; Palliative and Supportive Services, Flinders University, Bedford Park, South Australia, Australia.
Nikki
N
McCaffrey
Department of Palliative Care, Braeside Hospital, Prairiewood, New South Wales, Australia; Palliative and Supportive Services, Flinders University, Bedford Park, South Australia, Australia.
Meera
M
Agar
South Western Sydney Local Health District, Liverpool, New South Wales, Australia.
Janeane
J
Harlum
School of Population Health and Clinical Practice, University of Adelaide, Adelaide, South Australia, Australia.
Jonathon
J
Karnon
Palliative and Supportive Services, Flinders University, Bedford Park, South Australia, Australia.
David
D
Currow
Centre for Health Service Development, Australian Health Services Research Institute, University of Wollongong, Wollongong, New South Wales, Australia.
Simon
S
Eckermann
D003362:Cost-Benefit Analysis / Q000379:methods*; D003657:Decision Making; D017048:Health Care Costs; D006801:Humans; D019057:Quality-Adjusted Life Years