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Verfasst von:Sy, Frithjof [VerfasserIn]   i
 Berner-Rodoreda, Astrid [VerfasserIn]   i
 Asnake, Takelech [VerfasserIn]   i
 Getnet, Misrak [VerfasserIn]   i
 Amogne, Wondwossen [VerfasserIn]   i
 Bussmann, Hermann [VerfasserIn]   i
 Abera, Helen [VerfasserIn]   i
 Bärnighausen, Till [VerfasserIn]   i
 Deckert, Andreas [VerfasserIn]   i
Titel:Exploring computer-aided health decision-making on cervical cancer interventions through deliberative interviews in Ethiopia
Verf.angabe:Frithjof Sy, Astrid Berner-Rodoreda, Takelech Asnake, Misrak Getnet, Wondwossen Amogne, Hermann Bussmann, Helen Abera, Till Bärnighausen and Andreas Deckert
E-Jahr:2023
Jahr:17 April 2023
Umfang:8 S.
Fussnoten:Gesehen am 15.06.2023
Titel Quelle:Enthalten in: npj digital medicine
Ort Quelle:[Basingstoke] : Macmillan Publishers Limited, 2016
Jahr Quelle:2023
Band/Heft Quelle:6(2023) vom: Apr., Artikel-ID 68, Seite 1-8
ISSN Quelle:2398-6352
Abstract:Cervical cancer is a significant disease burden in Ethiopia. Mathematical models and computer simulations on disease dynamics can support effective resource allocation. The objectives of this work are (i) to explore the perspectives of health decision-makers on computer-aided predictions supporting cervical cancer interventions, (ii) to identify their information needs from these predictions, and (iii) their willingness to apply the results in their work. We conducted deliberative interviews with 15 health decision-makers and advisors in Ethiopia in autumn 2019. We analyze the data using a five steps framework approach drawing on thematic analysis and find that Ethiopian health decision-makers are willing to use computer-aided predictions in their decisions. Data on HPV prevalence and the cervical cancer burden are scarce but valued highly and decision-makers are particularly interested in the identification of local HPV hotspots. Data-driven mathematical models and computer simulations may increasingly influence health decision-making in Ethiopia.
DOI:doi:10.1038/s41746-023-00808-9
URL:kostenfrei: Volltext: https://doi.org/10.1038/s41746-023-00808-9
 kostenfrei: Volltext: https://www.nature.com/articles/s41746-023-00808-9
 DOI: https://doi.org/10.1038/s41746-023-00808-9
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Cancer prevention
 Cervical cancer
 Computational science
 Decision making
 Viral infection
K10plus-PPN:1849773769
Verknüpfungen:→ Zeitschrift
 
 
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