ECONOMIC MODELING QUALITY AND HTA OUTCOMES: POPULATION-COVERAGE OUTCOMES AND APPRAISAL TIMELINES ACROSS NICE, CDA-AMC, AND PBAC (2020-2025)
Author(s)
Ahmad Hecham Alani, PharmD1, Diana Rebeca Acosta Focil, MD1, David Thompson, PhD2, Mackenzie Mills, PhD1.
1HTA-Hive (Hive Health Optimum Ltd.), London, United Kingdom, 2Rubidoux Research LLC, Manchester, MA, USA.
1HTA-Hive (Hive Health Optimum Ltd.), London, United Kingdom, 2Rubidoux Research LLC, Manchester, MA, USA.
OBJECTIVES: Economic model quality is a recurrent source of uncertainty in HTA and a documented contributor to reimbursement failure. This study examined the relationship between economic modelling quality, population-level coverage outcomes, and appraisal timelines across cost-utility analysis (CUA)-based appraisals issued by three cost-effectiveness-driven jurisdictions.
METHODS: A retrospective cross-sectional analysis was conducted using HTA-Hive, a proprietary database of HTA reports, covering initial drug launches appraised by NICE (England & Wales), CDA-AMC (Canada), and PBAC (Australia) between 2020 and 2025. Modelling quality was operationalised using the count of agency-raised economic uncertainties per appraisal, dichotomised at the sample mean (~9): "high-quality" (<9 uncertainties) versus "low-quality" (≥9 uncertainties). Outcomes assessed were: (i) population-coverage outcomes (full coverage, partial coverage, or rejection); and (ii) time from marketing authorisation (MA) to first positive HTA recommendation. Associations were assessed using χ² and t-tests (α=0.05).
RESULTS: Across 419 CUA submissions, 3,680 economic uncertainties were identified, predominantly relating to modelling assumptions (39.4%), clinical evidence inputs (16.9%), and cost and utility inputs (~11% each); the remainder (22.4%) spanned ICERs, population, comparator, time horizon, and sensitivity analyses. Overall, 243 submissions (58.0%) were classified as high-quality and 176 (42.0%) as low-quality. For high-quality versus low-quality modelling, rates of full coverage, partial coverage, and rejection were 28.8%, 53.5%, and 17.7% versus 16.5%, 48.3%, and 35.2%, respectively (χ²=19.63; p=0.0001). High-quality models showed roughly half the rejection rate and higher full coverage. Mean time from MA to positive HTA decision was 293 days (~9 months) for high-quality (n=200) and 435 days (~13 months) for low-quality models (n=114) (p=0.004).
CONCLUSIONS: Higher-quality economic modelling — operationalised as fewer agency-raised uncertainties — was associated with more favourable population-coverage outcomes and a markedly faster appraisal trajectory, with significant differences across both outcomes. These benchmarks underscore the market access relevance of robust health economic modelling in HTA submissions.
METHODS: A retrospective cross-sectional analysis was conducted using HTA-Hive, a proprietary database of HTA reports, covering initial drug launches appraised by NICE (England & Wales), CDA-AMC (Canada), and PBAC (Australia) between 2020 and 2025. Modelling quality was operationalised using the count of agency-raised economic uncertainties per appraisal, dichotomised at the sample mean (~9): "high-quality" (<9 uncertainties) versus "low-quality" (≥9 uncertainties). Outcomes assessed were: (i) population-coverage outcomes (full coverage, partial coverage, or rejection); and (ii) time from marketing authorisation (MA) to first positive HTA recommendation. Associations were assessed using χ² and t-tests (α=0.05).
RESULTS: Across 419 CUA submissions, 3,680 economic uncertainties were identified, predominantly relating to modelling assumptions (39.4%), clinical evidence inputs (16.9%), and cost and utility inputs (~11% each); the remainder (22.4%) spanned ICERs, population, comparator, time horizon, and sensitivity analyses. Overall, 243 submissions (58.0%) were classified as high-quality and 176 (42.0%) as low-quality. For high-quality versus low-quality modelling, rates of full coverage, partial coverage, and rejection were 28.8%, 53.5%, and 17.7% versus 16.5%, 48.3%, and 35.2%, respectively (χ²=19.63; p=0.0001). High-quality models showed roughly half the rejection rate and higher full coverage. Mean time from MA to positive HTA decision was 293 days (~9 months) for high-quality (n=200) and 435 days (~13 months) for low-quality models (n=114) (p=0.004).
CONCLUSIONS: Higher-quality economic modelling — operationalised as fewer agency-raised uncertainties — was associated with more favourable population-coverage outcomes and a markedly faster appraisal trajectory, with significant differences across both outcomes. These benchmarks underscore the market access relevance of robust health economic modelling in HTA submissions.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
EE654
Topic
Economic Evaluation, Health Technology Assessment, Organizational Practices
Disease
No Additional Disease & Conditions/Specialized Treatment Areas