Capturing artificial intelligence applications’ value proposition in healthcare – a qualitative research study

Abstract Artificial intelligence (AI) applications pave the way for innovations in the healthcare (HC) industry. However, their adoption in HC organizations is still nascent as organizations often face a fragmented and incomplete picture of how they can capture the value of AI applications on a mana...

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Main Authors: Jasmin Hennrich, Eva Ritz, Peter Hofmann, Nils Urbach
Format: Article
Language:English
Published: BMC 2024-04-01
Series:BMC Health Services Research
Subjects:
Online Access:https://doi.org/10.1186/s12913-024-10894-4
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author Jasmin Hennrich
Eva Ritz
Peter Hofmann
Nils Urbach
author_facet Jasmin Hennrich
Eva Ritz
Peter Hofmann
Nils Urbach
author_sort Jasmin Hennrich
collection DOAJ
description Abstract Artificial intelligence (AI) applications pave the way for innovations in the healthcare (HC) industry. However, their adoption in HC organizations is still nascent as organizations often face a fragmented and incomplete picture of how they can capture the value of AI applications on a managerial level. To overcome adoption hurdles, HC organizations would benefit from understanding how they can capture AI applications’ potential. We conduct a comprehensive systematic literature review and 11 semi-structured expert interviews to identify, systematize, and describe 15 business objectives that translate into six value propositions of AI applications in HC. Our results demonstrate that AI applications can have several business objectives converging into risk-reduced patient care, advanced patient care, self-management, process acceleration, resource optimization, and knowledge discovery. We contribute to the literature by extending research on value creation mechanisms of AI to the HC context and guiding HC organizations in evaluating their AI applications or those of the competition on a managerial level, to assess AI investment decisions, and to align their AI application portfolio towards an overarching strategy.
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spelling doaj.art-df37e0357a6d4027adac45b19369d6e62024-04-07T11:12:49ZengBMCBMC Health Services Research1472-69632024-04-0124111410.1186/s12913-024-10894-4Capturing artificial intelligence applications’ value proposition in healthcare – a qualitative research studyJasmin Hennrich0Eva Ritz1Peter Hofmann2Nils Urbach3FIM Research Institute for Information Management, University of Bayreuth, Branch Business and Information Systems Engineering of the Fraunhofer FITUniversity St. GallenFIM Research Institute for Information Management, University of Bayreuth, Branch Business and Information Systems Engineering of the Fraunhofer FITFIM Research Institute for Information Management, University of Bayreuth, Branch Business and Information Systems Engineering of the Fraunhofer FITAbstract Artificial intelligence (AI) applications pave the way for innovations in the healthcare (HC) industry. However, their adoption in HC organizations is still nascent as organizations often face a fragmented and incomplete picture of how they can capture the value of AI applications on a managerial level. To overcome adoption hurdles, HC organizations would benefit from understanding how they can capture AI applications’ potential. We conduct a comprehensive systematic literature review and 11 semi-structured expert interviews to identify, systematize, and describe 15 business objectives that translate into six value propositions of AI applications in HC. Our results demonstrate that AI applications can have several business objectives converging into risk-reduced patient care, advanced patient care, self-management, process acceleration, resource optimization, and knowledge discovery. We contribute to the literature by extending research on value creation mechanisms of AI to the HC context and guiding HC organizations in evaluating their AI applications or those of the competition on a managerial level, to assess AI investment decisions, and to align their AI application portfolio towards an overarching strategy.https://doi.org/10.1186/s12913-024-10894-4Artificial intelligenceValue propositionsBusiness objectivesHealthcare
spellingShingle Jasmin Hennrich
Eva Ritz
Peter Hofmann
Nils Urbach
Capturing artificial intelligence applications’ value proposition in healthcare – a qualitative research study
BMC Health Services Research
Artificial intelligence
Value propositions
Business objectives
Healthcare
title Capturing artificial intelligence applications’ value proposition in healthcare – a qualitative research study
title_full Capturing artificial intelligence applications’ value proposition in healthcare – a qualitative research study
title_fullStr Capturing artificial intelligence applications’ value proposition in healthcare – a qualitative research study
title_full_unstemmed Capturing artificial intelligence applications’ value proposition in healthcare – a qualitative research study
title_short Capturing artificial intelligence applications’ value proposition in healthcare – a qualitative research study
title_sort capturing artificial intelligence applications value proposition in healthcare a qualitative research study
topic Artificial intelligence
Value propositions
Business objectives
Healthcare
url https://doi.org/10.1186/s12913-024-10894-4
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