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The Role of Artificial Intelligence in Healthcare Quality Improvement: A Scoping Review and Critical Appraisal of Operational Efficiency, Patient Outcomes, and Implementation Challenges

Meshach Aiwerioghene, Vivian Osuchukwu Orcid Logo

Hospitals, Volume: 2, Issue: 4, Start page: 27

Swansea University Authors: Meshach Aiwerioghene, Vivian Osuchukwu Orcid Logo

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DOI (Published version): 10.3390/hospitals2040027

Abstract

Background: Artificial Intelligence (AI) holds significant potential to enhance operational efficiency and quality in healthcare. However, despite substantial investment, its widespread, sustained implementation is limited, necessitating a thorough risk assessment to overcome current adoption barrie...

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Published in: Hospitals
ISSN: 2813-4524
Published: MDPI AG 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa70865
first_indexed 2025-11-07T13:07:54Z
last_indexed 2026-01-15T05:28:36Z
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spelling 2026-01-14T14:32:51.5182741 v2 70865 2025-11-07 The Role of Artificial Intelligence in Healthcare Quality Improvement: A Scoping Review and Critical Appraisal of Operational Efficiency, Patient Outcomes, and Implementation Challenges 82dd7cf8eee57c3f121a6fe09d333c1e Meshach Aiwerioghene Meshach Aiwerioghene true false dbd532a4fee973c758a191bd882e7e31 0000-0003-3212-6786 Vivian Osuchukwu Vivian Osuchukwu true false 2025-11-07 HSOC Background: Artificial Intelligence (AI) holds significant potential to enhance operational efficiency and quality in healthcare. However, despite substantial investment, its widespread, sustained implementation is limited, necessitating a thorough risk assessment to overcome current adoption barriers. Methods: This scoping review, guided by the Arksey and Malley framework, systematically mapped 13 articles published between 2019 and 2024, sourced from five major databases (including CINAHL, Medline, and PubMed). A rigorous, systematic process involving independent data charting and critical appraisal, using the Critical Appraisal Skills Programme (CASP) tool, was implemented, followed by thematic synthesis to address the research questions. Results: AI demonstrates a significant positive impact on both operational efficiency (e.g., optimised resource allocation, reduced waiting times) and patient outcomes (e.g., improved patient-centred, proactive care, and identification of readmission risks). Major implementation hurdles identified include high costs, critical data security and privacy concerns, the risk of algorithmic bias, and significant staff resistance stemming from limited understanding. Conclusions: Healthcare managers must address key challenges related to cost, bias, and staff acceptance to leverage the potential of AI fully. Strategic investments, the implementation of robust data governance frameworks, and comprehensive staff training are crucial steps for mitigating risks and creating a more efficient, patient-centred, and effective healthcare system. Journal Article Hospitals 2 4 27 MDPI AG 2813-4524 artificial intelligence; healthcare delivery; operational efficiency; patient outcomes; predictive analytics; implementation barriers; scoping review; healthcare management; big data analytics; clinical decision support 5 11 2025 2025-11-05 10.3390/hospitals2040027 COLLEGE NANME Health and Social Care School COLLEGE CODE HSOC Swansea University Other The authors declare that they used no funding sources for this study. 2026-01-14T14:32:51.5182741 2025-11-07T12:57:32.3835578 Faculty of Medicine, Health and Life Sciences School of Health and Social Care - Public Health Meshach Aiwerioghene 1 Vivian Osuchukwu 0000-0003-3212-6786 2 70865__35992__62593176037044f4948260c0b333e423.pdf 70865.VoR.pdf 2026-01-14T14:31:06.5429008 Output 1210007 application/pdf Version of Record true © 2025 by the authors. This is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. true eng https://creativecommons.org/ licenses/by/4.0/
title The Role of Artificial Intelligence in Healthcare Quality Improvement: A Scoping Review and Critical Appraisal of Operational Efficiency, Patient Outcomes, and Implementation Challenges
spellingShingle The Role of Artificial Intelligence in Healthcare Quality Improvement: A Scoping Review and Critical Appraisal of Operational Efficiency, Patient Outcomes, and Implementation Challenges
Meshach Aiwerioghene
Vivian Osuchukwu
title_short The Role of Artificial Intelligence in Healthcare Quality Improvement: A Scoping Review and Critical Appraisal of Operational Efficiency, Patient Outcomes, and Implementation Challenges
title_full The Role of Artificial Intelligence in Healthcare Quality Improvement: A Scoping Review and Critical Appraisal of Operational Efficiency, Patient Outcomes, and Implementation Challenges
title_fullStr The Role of Artificial Intelligence in Healthcare Quality Improvement: A Scoping Review and Critical Appraisal of Operational Efficiency, Patient Outcomes, and Implementation Challenges
title_full_unstemmed The Role of Artificial Intelligence in Healthcare Quality Improvement: A Scoping Review and Critical Appraisal of Operational Efficiency, Patient Outcomes, and Implementation Challenges
title_sort The Role of Artificial Intelligence in Healthcare Quality Improvement: A Scoping Review and Critical Appraisal of Operational Efficiency, Patient Outcomes, and Implementation Challenges
author_id_str_mv 82dd7cf8eee57c3f121a6fe09d333c1e
dbd532a4fee973c758a191bd882e7e31
author_id_fullname_str_mv 82dd7cf8eee57c3f121a6fe09d333c1e_***_Meshach Aiwerioghene
dbd532a4fee973c758a191bd882e7e31_***_Vivian Osuchukwu
author Meshach Aiwerioghene
Vivian Osuchukwu
author2 Meshach Aiwerioghene
Vivian Osuchukwu
format Journal article
container_title Hospitals
container_volume 2
container_issue 4
container_start_page 27
publishDate 2025
institution Swansea University
issn 2813-4524
doi_str_mv 10.3390/hospitals2040027
publisher MDPI AG
college_str Faculty of Medicine, Health and Life Sciences
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hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str School of Health and Social Care - Public Health{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}School of Health and Social Care - Public Health
document_store_str 1
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description Background: Artificial Intelligence (AI) holds significant potential to enhance operational efficiency and quality in healthcare. However, despite substantial investment, its widespread, sustained implementation is limited, necessitating a thorough risk assessment to overcome current adoption barriers. Methods: This scoping review, guided by the Arksey and Malley framework, systematically mapped 13 articles published between 2019 and 2024, sourced from five major databases (including CINAHL, Medline, and PubMed). A rigorous, systematic process involving independent data charting and critical appraisal, using the Critical Appraisal Skills Programme (CASP) tool, was implemented, followed by thematic synthesis to address the research questions. Results: AI demonstrates a significant positive impact on both operational efficiency (e.g., optimised resource allocation, reduced waiting times) and patient outcomes (e.g., improved patient-centred, proactive care, and identification of readmission risks). Major implementation hurdles identified include high costs, critical data security and privacy concerns, the risk of algorithmic bias, and significant staff resistance stemming from limited understanding. Conclusions: Healthcare managers must address key challenges related to cost, bias, and staff acceptance to leverage the potential of AI fully. Strategic investments, the implementation of robust data governance frameworks, and comprehensive staff training are crucial steps for mitigating risks and creating a more efficient, patient-centred, and effective healthcare system.
published_date 2025-11-05T05:33:49Z
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