{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T06:24:26Z","timestamp":1780467866134,"version":"3.54.1"},"reference-count":51,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T00:00:00Z","timestamp":1757376000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Med Screen"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To study the implications of implementing artificial intelligence (AI) as a decision support tool in the Norwegian breast cancer screening program concerning cost-effectiveness and time savings for radiologists.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In a decision tree model using recent data from AI vendors and the Cancer Registry of Norway, and assuming equal effectiveness of radiologists plus AI compared to standard practice, we simulated costs, effects and radiologist person-years over the next 20 years under different scenarios: 1) Assuming a \u20ac1 additional running cost of AI instead of the \u20ac3 assumed in the base case, 2) varying the AI-score thresholds for single vs. double readings, 3) varying the consensus and recall rates, and 4) reductions in the interval cancer rate compared to standard practice.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>AI was unlikely to be cost-effective, even when only one radiologist was used alongside AI for all screening exams. This also applied when assuming a 10% reduction in the consensus and recall rates. However, there was a 30\u201350% reduction in the radiologists\u2019 screen-reading volume. Assuming an additional running cost of \u20ac1 for AI, the costs were comparable, with similar probabilities of cost-effectiveness for AI and standard practice. Assuming a 5% reduction in the interval cancer rate, AI proved to be cost-effective across all willingness-to-pay values.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>AI may be cost-effective if the interval cancer rate is reduced by 5% or more, or if its additional cost is \u20ac1 per screening exam. Despite a substantial reduction in screening volume, this remains modest relative to the total radiologist person-years available within breast centers, accounting for only 3\u20134% of person-years.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/09691413251372829","type":"journal-article","created":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T18:08:38Z","timestamp":1757441318000},"page":"38-47","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":4,"title":["An economic scenario analysis of implementing artificial intelligence in BreastScreen Norway\u2013Impact on radiologist person-years, costs and effects"],"prefix":"10.1177","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2865-4762","authenticated-orcid":false,"given":"Tron Anders","family":"Moger","sequence":"first","affiliation":[{"name":"Institute of Health and Society, Department of Health Management and Health Economics, University of Oslo, Oslo, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sahand Barati","family":"Nardin","sequence":"additional","affiliation":[{"name":"Institute of Health and Society, Department of Health Management and Health Economics, University of Oslo, Oslo, Norway"},{"name":"Neat, Oslo, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6624-6957","authenticated-orcid":false,"given":"\u00c5sne S\u00f8rlien","family":"Holen","sequence":"additional","affiliation":[{"name":"Norwegian Institute of Public Health"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1477-1968","authenticated-orcid":false,"given":"Nataliia","family":"Moshina","sequence":"additional","affiliation":[{"name":"Norwegian Institute of Public Health"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0178-8939","authenticated-orcid":false,"given":"Solveig","family":"Hofvind","sequence":"additional","affiliation":[{"name":"Norwegian Institute of Public Health"},{"name":"UiT The Arctic University of Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,9,9]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/bs.pmbts.2017.07.002"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/djz220"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1177\/09691413231199583"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.3747\/co.25.3770"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1159\/000503715"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1002\/cncr.28174"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMsr1504363"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.g3701"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-019-1799-6"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2016161174"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2533082308"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1001\/jamainternmed.2015.5231"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41523-017-0014-x"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2019182622"},{"key":"e_1_3_2_16_2","article-title":"Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study","volume":"2","author":"Dembrower K","year":"2020","unstructured":"Dembrower K, et al. 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