Academic interests
- Health economic evaluation
- Health economic modelling
- Next-generation sequencing for precision cancer medicine
- Implementing environmental aspects in health economic evaluation
- European HTA and market access to innovative health technologies
Background
- European Master in Health Economics and Management (EU-HEM), 2022
University of Oslo/Erasmus University Rotterdam/Management Center Innsbruck
- Bachelor of Arts in International Business, 2018
accadis Hochschule Bad Homburg, Germany
Partners
Currently involved in the multi-stakeholder project ASCERTAIN, funded by the European Union (access2meds.eu)
Publications
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Henkel, Pia Sofie; Pedersen, Kine; Tasken, Kjetil; Hult, Ebba Hallersjö; Gelderblom, Hans & Fagereng, Gro Live
[Show all 8 contributors for this article]
(2026).
Precision cancer medicine in Europe: a mixed-methods study on infrastructure for extended molecular diagnostics.
Journal of Cancer Research and Clinical Oncology.
ISSN 0171-5216.
152.
doi:
10.1007/s00432-026-06468-y.
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Purpose
Precision cancer medicine (PCM), targeting cancer treatment to patients’ individual genomic profiles, has the potential to improve diagnosis and outcomes substantially. Implementing PCM in healthcare systems requires that extended molecular diagnostics are accessible as part of routine practice. We conducted a mixed-methods study to identify and inform the infrastructure necessary for the implementation of extended molecular diagnostics as part of the health care system.
Methods
To identify and inform relevant categories of necessary infrastructure, we combined a survey, a structured literature search, and expert interviews. The survey included questions on reimbursement and technology assessment of diagnostics for PCM. Findings from the structured literature search were grouped to identify categories of infrastructure together with emerging themes in interviews with experienced oncologists, pathologists, and health technology assessment experts.
Results
44 respondents from 20 countries participated in our survey. We identified and included 45 published papers, and seven experts were interviewed. We identified six key categories for implementing PCM as part of the healthcare system: physical, financial, organisational, competency, data and legal infrastructure. Our combined data sources revealed several themes to promote implementation, including the importance of centralisation of testing, the need for sustainable reimbursement, engagement of relevant stakeholders, interoperability of data infrastructure, and inter-disciplinary collaboration.
Conclusion
Our results highlight the need for interdisciplinary approaches and the value of initiatives to establish infrastructure within and across countries. While several European countries have come a long way in implementing diagnostics for PCM, considerable work remains to ensure equitable access for patients in need.
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Frisell, Oskar; Aas, Eline; Henkel, Pia Sofie; Fagereng, Gro Live; Tasken, Kjetil & Hult, Ebba Hallersjö
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(2026).
A conceptual health economic modelling framework to assess the cost-effectiveness of molecular target–driven treatment regimens in oncology.
Acta Oncologica.
ISSN 0284-186X.
65,
p. 141–147.
doi:
10.2340/1651-226x.2026.45088.
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Background and purpose: Molecularly targeted cancer therapies challenge conventional health economic evaluation frameworks that are structured around tumour-specific indications, comparators, and trial designs. Existing models often rely on pooled estimates from heterogeneous early-phase evidence or single-indication analyses, creating uncertainty for reimbursement decision-makers. We propose a conceptual modelling framework that aligns cost-effectiveness analyses with the biological rationale of precision oncology, evaluating therapies according to shared molecular alterations across tumour types.
Patient/material and methods: We examined the methodological limitations of conventional partitioned survival models (PSMs) commonly applied in oncology and evaluated their suitability for tumour-agnostic indications. Based on the collected literature, we developed a dynamic, modular PSM framework that integrates multiple tumour sites expressing a common biomarker. The framework supports pooled and tumour-specific analysis of cost-effectiveness and enables progressive disaggregation of subgroups as additional evidence becomes available.
Results: The proposed modelling approach facilitates transparent synthesis of heterogeneous evidence across tumour types using epidemiologically informed weighting, while preserving the ability to estimate tumour-specific cost-effectiveness where data permit. It addresses key challenges in tumour-agnostic evaluation, including variation in standard of care, treatment effects, and resource use across cancer sites. The modular design promotes internal consistency, reduces duplication of analytical effort, and enables iterative re-assessment of both overall and subgroup-specific cost-effectiveness.
Interpretation: A dynamic, weighted multi-site modelling framework represents a coherent and adaptable extension of current health-technology assessment-practice for tumour-agnostic therapies. By structuring evidence around molecular targets, the framework can improve transparency and robustness of cost-effectiveness estimates, thereby supporting more equitable and efficient reimbursement decisions in the context of precision oncology.
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Groot, Carin A. Uyl-de; Xander, Nicolas S.H.; Belleman, Tom; Burger, Emily Annika; Doeswijk, Robin & Durand-Zaleski, Isabelle
[Show all 23 contributors for this article]
(2026).
Bridging affordability and sustainability of health innovations via novel pricing, cost-effectiveness, and reimbursement models to improve patient access: The ASCERTAIN project.
Health Policy and Technology.
ISSN 2211-8837.
15(2).
doi:
10.1016/j.hlpt.2026.101155.
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Objectives
Disparities in access to potential innovative health technologies (pIHTs) persist across Europe due to differing healthcare budgets, pricing policies, and health technology assessment (HTA) practices. The ASCERTAIN project aims to reduce these inequalities by developing integrated pricing, cost-effectiveness, and reimbursement approaches that enhance affordability, long-term sustainability, and timely patient access.
Methods
The project applies a mixed-methods approach, including literature review, stakeholder surveys, interviews, and focus groups, to ensure relevance across diverse health systems. It integrates access-based pricing, value-driven HTA, and adaptable reimbursement models into a practical, open-access ACCESS2MEDS Toolbox. This includes access-based pricing frameworks, cost-effectiveness models, and budget impact and reimbursement analyses, all adaptable to country-specific conditions to reduce uncertainty and improve transparency. Tools are co-created with patients, developers, clinicians, and policymakers and will be tested and validated using three use cases representing high-impact areas of innovation: precision oncology medicines, cell and gene therapies, and next-generation sequencing tests.
Results
Outputs will include validated tools enabling improved evaluation of clinical benefit, cost-effectiveness, and financial sustainability, strengthening value-based decision-making across Europe. Innovative access- and outcome-based pricing strategies will support responsible innovation while encouraging fair reimbursement and improved budget control. Policy roadmaps will guide the adoption of equitable access models and support system-level implementation.
Conclusions
ASCERTAIN will provide a harmonized framework that balances cost control, innovation incentives, and patient-centered care. By facilitating consistent, evidence-based pricing and reimbursement decisions, the project supports fair and sustainable access to pIHTs across Europe, with continued multi-stakeholder collaboration driving its wider adoption and real-world impact.
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Henkel, Pia S.; Aas, Eline; Russnes, Hege Elisabeth Giercksky; Dyvik, Ingrid; Fagereng, Gro Live & Helland, Åslaug
[Show all 9 contributors for this article]
(2025).
Microcosting Study of Genomic Profiling for Precision Cancer Medicine. Application from the National Infrastructure for Precision Diagnostics in Norway.
Journal of Molecular Diagnostics.
ISSN 1525-1578.
27(10),
p. 945–953.
doi:
10.1016/j.jmoldx.2025.06.006.
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Detailed cost analyses of genomic profiling for precision cancer medicine can inform strategic planning and cost-effectiveness analysis. A flexible costing framework was developed in this study to conduct microcosting of genomic profiling in precision cancer medicine using the broad gene panel TruSight Oncology 500 and accounting for its integration into the molecular tumor board within the national Infrastructure for Precision Diagnostics in Norway. The framework enables calculation of costs per sample, by workflow steps and cost categories. Site visits and discussions with staff at Oslo University Hospital informed the diagnostic workflow, validation of the framework, and resource use inputs. Sensitivity analysis addressed alternative resource use estimates, higher batch sizes, and investment costs for automation of the library preparation step. Total costs per sample were $2944 USD, ranging from $2366 to $4307 when considering uncertainties in estimates. Consumables and personnel were the most resource-intensive cost categories across analyses. Automating the resource-intensive library preparation step enabled a higher weekly batch size with slightly lower costs per sample ($2881) despite the additional equipment costs. The dynamic costing framework highlights how the choice of equipment and batch sizes affects sample costs and personnel needs for genomic profiling. Consumables and personnel offer the largest potential for costs savings, but potential personnel bottlenecks need to be considered when further upscaling capacity.
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Henkel, Pia Sofie; Burger, Emily Annika; Sletner, Line & Pedersen, Kine
(2024).
Exploring Structural Uncertainty in Cost-Effectiveness Modeling of Gestational Diabetes Screening: An Application Example from Norway.
Medical decision making.
ISSN 0272-989X.
44(4),
p. 380–392.
doi:
10.1177/0272989X241241339.
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Background
Screening pregnant women for gestational diabetes mellitus (GDM) has recently been expanded in Norway, although screening eligibility criteria continue to be debated. We aimed to compare the cost-effectiveness of alternative GDM screening strategies and explored structural uncertainty and the value of future research in determining the most cost-effective eligibility criteria for GDM screening in Norway.
Design
We developed a probabilistic decision tree to estimate the total costs and health benefits (i.e., quality-adjusted life-years; QALYs) associated with 4 GDM screening strategies (universal, current guidelines, high-risk, and no screening). We identified the most cost-effective strategy as the strategy with the highest incremental cost-effectiveness ratio below a Norwegian benchmark for cost-effectiveness ($28,400/QALY). We excluded inconclusive evidence on the effects of screening on later maternal type 2 diabetes mellitus (T2DM) in the primary analysis but included this outcome in a secondary analysis using 2 different sources of evidence (i.e., Cochrane or US Preventive Services Task Force). To quantify decision uncertainty, we conducted scenario analysis and value-of-information analyses.
Results
Current screening recommendations were considered inefficient in all analyses, while universal screening was most cost-effective in our primary analysis ($26,014/QALY gained) and remained most cost-effective when we assumed a preventive effect of GDM treatment on T2DM. When we assumed no preventive effect, high-risk screening was preferred ($19,115/QALY gained). When we assumed GDM screening does not prevent perinatal death in scenario analysis, all strategies except no screening exceeded the cost-effectiveness benchmark. In most analyses, decision uncertainty was high.
Conclusions
The most cost-effective screening strategy, ranging from no screening to universal screening, depended on the source and inclusion of GDM treatment effects on perinatal death and T2DM. Further research on these long-term outcomes could reduce decision uncertainty.
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Published
Jan. 8, 2024 1:41 PM
- Last modified
July 15, 2024 10:59 AM