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ArticleThe European journal of health economics : HEPAC : health economics in prevention and care2026

Is next generation sequencing for the diagnosis of rare diseases worth its cost? A user-based approach to valuation.

Karen V MacDonald, Sebastian Heidenreich, Nicolas Krucien, Kym M Boycott, Francois P Bernier, Mandy Ryan, Deborah A Marshall

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Article in The European journal of health economics : HEPAC : health economics in prevention and care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Karen V MacDonaldDepartment of Community Health Sciences, Cumming School of Medicine, Health Research Innovation Centre, University of Calgary, Room 3C58, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.
Sebastian HeidenreichDepartment of Community Health Sciences, Cumming School of Medicine, Health Research Innovation Centre, University of Calgary, Room 3C58, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.
Nicolas KrucienEvidera Inc., London, UK.
Kym M BoycottChildren's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, ON, Canada.
Francois P BernierDepartments of Medical Genetics and Pediatrics, Cumming School of Medicine, University of Calgary and Alberta Children's Hospital Research Institute, Calgary, AB, Canada.
Mandy RyanHealth Economics Research Unit, University of Aberdeen, Aberdeen, Scotland.
Deborah A MarshallDepartment of Community Health Sciences, Cumming School of Medicine, Health Research Innovation Centre, University of Calgary, Room 3C58, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada. Damarsha@ucalgary.ca.ORCID http://orcid.org/0000-0002-8467-8008

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNext generation sequencing (NGS) can decrease the diagnostic odyssey for patients with rare diseases. However, valuing the combination of health and non-health outcomes associated with NGS is challenging. While stated preference methods can be used for monetary valuation of outcomes, frameworks that jointly account for both costs and benefits to determine cost-acceptability are limited. Insights into cost-acceptability can help inform pricing and access decisions where competition among NGS alternatives is imperfect or diagnostics are provided as a public good.

methodsWe used stated preference data to estimate the cost-acceptability of exome sequencing (ES) (i.e., cost at which ES provides value and users are willing-to-pay) in a user-based valuation. We estimated the benefit of ES as an alternative to all other diagnostic tests using a compensating variation model. Based on estimated net-benefit, we determined the proportion of users with positive expected net-benefit for varying cost (CAD$0-$15,000) and chance of diagnosis (10%-90%). We created a cost-acceptability frontier of costs and chance of diagnosis for a range of scenarios. Expected net-benefit and cost-acceptability were estimated for low-cost (CAD$1,600) and high-cost (CAD$11,660) ES scenarios.

resultsWe find that at least half of users consider costs of up to CAD$10,000 acceptable if the chance of obtaining a diagnosis of ES is at least 50%. However, at least some users are willing to accept a chance of diagnosis below 50%, even if the associated cost are high.

conclusionOur proposed valuation framework suggests that many potential users of ES are willing to accept various combinations of cost and chance of diagnosis. Cost-acceptability is especially high if the chance of diagnosis is larger the 50%.

Indexed as

Exome SequencingHigh-Throughput Nucleotide SequencingRare DiseasesCost-Benefit AnalysisHumansPatient PreferenceNext generation sequencingPatient preferencesRare diseasesUser-based valuation

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.