Health Technologies and Impermissible Delays: The Case of Digital Breast Tomosynthesis

This paper argues that we have a moral obligation to implement certain health technologies even if we have limited or incomplete evidence of their effectiveness. The focus is on technologies used in non-emergency settings, as opposed to "exceptional cases" such as compassionate use and emergency approvals during public health emergencies. A broadly plausible moral principle - the Ecumenical Principle - is introduced and applied to a test case: the use of Digital Breast Tomosynthesis in mammographic screening. The paper concludes by exploring the implications of the Ecumenical Principle for the adoption of other new health technologies.

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Publication Details

Journal
Science and Engineering Ethics
Published
2025-05-07
DOI
https://doi.org/10.1007/s11948-025-00535-2
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Health Technologies and Impermissible Delays: The Case of Digital Breast Tomosynthesis

Magnus Dustler, Johan Brännmark, Simon Rosenqvist
Science and Engineering Ethics
AI in cancer detection
article

Health Technologies and Impermissible Delays: The Case of Digital Breast Tomosynthesis

Magnus Dustler, Johan Brännmark, Simon Rosenqvist
article en

Abstract

This paper argues that we have a moral obligation to implement certain health technologies even if we have limited or incomplete evidence of their effectiveness. The focus is on technologies used in non-emergency settings, as opposed to "exceptional cases" such as compassionate use and emergency approvals during public health emergencies. A broadly plausible moral principle - the Ecumenical Principle - is introduced and applied to a test case: the use of Digital Breast Tomosynthesis in mammographic screening. The paper concludes by exploring the implications of the Ecumenical Principle for the adoption of other new health technologies.

Science and Engineering EthicsVol. 31(3)
Stockholm University (SE), Malmö University (SE), Lund University (SE), University of Gothenburg (SE)
Lunds Universitet, Göteborgs Universitet
Openalex Percentile: Top 96%
AI in cancer detection
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