2025/12/03 by Dylan A Mordaunt, Dylan Mordaunt, Mordaunt, Dylan A
Decision Sciences · Economics, Econometrics and Finance · #Economic and Environmental Valuation #Efficiency Analysis Using DEA #Equity (law) #Health Systems, Economic Evaluations, Quality of Life #Markov decision process #Perspective (graphical) #Probabilistic logic #Python (programming language) #Value of information #econ.GN #q-fin.EC
paper · pdf · doi:10.48550/arxiv.2512.03596
openalex publication_date 2025/12/03 · openalex created_date 2025/12/05 · openalex updated_date 2026/08/05
Health economic evaluations are sensitive to the choice of analytical perspective (e.g., health system vs. societal). We present voppocnz, a Python package for Distributional Cost-Effectiveness Analysis (DCEA), Markov cohort modeling, probabilistic sensitivity analysis, value of information, and explicit comparison of analytical perspectives. We define Value of Perspective (VoP) as a directional expected opportunity loss: the welfare loss, measured under a declared reference perspective, when decisions are selected under another perspective. Five synthetic Aotearoa New Zealand demonstration models produced deterministic decision discordance in two cases at a NZ20,000/QALY threshold. Seeded probabilistic analysis estimated mean per-person directional VoP of NZ128,706 [0, 279,088] for smoking cessation and NZ30,853 [0, 89,122] for housing insulation (95% simulation intervals in brackets); the other three cases had zero loss under the simulated strategy choices. These values test the software workflow and are not estimates for policy adoption. Release 0.2.3 supports Python 3.12-3.14 and records typed inputs, random seeds, software versions, and Arrow-schema identities for reproducible analysis.