Research agenda for using artificial intelligence in health governance: interpretive scoping review and framework

Ramezani, Maryam; Takian, Amirhossein; Bakhtiari, Ahad; Rabiee, Hamid R.; Ghazanfari, Sadegh; Sazgarnejad, Saharnaz

doi:10.1186/s13040-023-00346-w

Cited by 4 publications

(1 citation statement)

References 102 publications

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“…Moreover, the notion that the complexity of implementing AI as a complement to health management is perceived as both an opportunity and a challenge is well evidenced [39] . As demonstrated, managers expressed conflicting perceptions about the complexity of AI, describing it as both inevitable and indispensable, but reiterating their low understanding and specific training on the subject.…”

Section: Discussionmentioning

confidence: 99%

Use of Artificial Intelligence tools in supporting decision-making in hospital management

Alves,

Seringa,

Silvestre

et al. 2024

Preprint

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Background The integration of Artificial Intelligence (AI) tools in hospital management holds potential for enhancing decision-making processes. This study investigates the current state of decision-making in hospital management, explores the potential benefits of AI integration, and examines hospital managers' perceptions of AI as a decision-support tool. Methods A descriptive and exploratory study was conducted using a qualitative approach. Data were collected through semi-structured interviews with 15 hospital managers from various departments and institutions. The interviews were transcribed, anonymized, and analyzed using thematic coding to identify key themes and patterns in the responses. Results Hospital managers highlighted the current inefficiencies in decision-making processes, often characterized by poor communication, isolated decision-making, and limited data access. The use of traditional tools like spreadsheet applications and business intelligence systems remains prevalent, but there is a clear need for more advanced, integrated solutions. Managers expressed both optimism and skepticism about AI, acknowledging its potential to improve efficiency and decision-making while raising concerns about data privacy, ethical issues, and the loss of human empathy. The study identified key challenges, including the variability in technical skills, data fragmentation, and resistance to change. Managers emphasized the importance of robust data infrastructure and adequate training to ensure successful AI integration. Conclusions The study reveals a complex landscape where the potential benefits of AI in hospital management are balanced with significant challenges and concerns. Effective integration of AI requires addressing technical, ethical, and cultural issues, with a focus on maintaining human elements in decision-making. AI is seen as a powerful tool to support, not replace, human judgment in hospital management, promising improvements in efficiency, data accessibility, and analytical capacity. Preparing healthcare institutions with the necessary infrastructure and providing specialized training for managers are crucial for maximizing the benefits of AI while mitigating associated risks.

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Section: Discussionmentioning

confidence: 99%

Use of Artificial Intelligence tools in supporting decision-making in hospital management

Alves,

Seringa,

Silvestre

et al. 2024

Preprint

View full text Add to dashboard Cite

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The application of artificial intelligence in health policy: a scoping review

Ramezani,

Takian,

Bakhtiari

et al. 2023

BMC Health Serv Res

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Background Policymakers require precise and in-time information to make informed decisions in complex environments such as health systems. Artificial intelligence (AI) is a novel approach that makes collecting and analyzing data in complex systems more accessible. This study highlights recent research on AI’s application and capabilities in health policymaking. Methods We searched PubMed, Scopus, and the Web of Science databases to find relevant studies from 2000 to 2023, using the keywords “artificial intelligence” and “policymaking.” We used Walt and Gilson’s policy triangle framework for charting the data. Results The results revealed that using AI in health policy paved the way for novel analyses and innovative solutions for intelligent decision-making and data collection, potentially enhancing policymaking capacities, particularly in the evaluation phase. It can also be employed to create innovative agendas with fewer political constraints and greater rationality, resulting in evidence-based policies. By creating new platforms and toolkits, AI also offers the chance to make judgments based on solid facts. The majority of the proposed AI solutions for health policy aim to improve decision-making rather than replace experts. Conclusion Numerous approaches exist for AI to influence the health policymaking process. Health systems can benefit from AI’s potential to foster the meaningful use of evidence-based policymaking.

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Use of Artificial Intelligence tools in supporting decision-making in hospital management

Alves,

Seringa,

Silvestre

et al. 2024

BMC Health Serv Res

View full text Add to dashboard Cite

Background The use of Artificial Intelligence (AI) tools in hospital management holds potential for enhancing decision-making processes. This study investigates the current state of decision-making in hospital management, explores the potential benefits of AI integration, and examines hospital managers’ perceptions of AI as a decision-support tool. Methods A descriptive and exploratory study was conducted using a qualitative approach. Data were collected through semi-structured interviews with 15 hospital managers from various departments and institutions. The interviews were transcribed, anonymized, and analyzed using thematic coding to identify key themes and patterns in the responses. Results Hospital managers highlighted the current inefficiencies in decision-making processes, often characterized by poor communication, isolated decision-making, and limited data access. The use of traditional tools like spreadsheet applications and business intelligence systems remains prevalent, but there is a clear need for more advanced, integrated solutions. Managers expressed both optimism and skepticism about AI, acknowledging its potential to improve efficiency and decision-making while raising concerns about data privacy, ethical issues, and the loss of human empathy. The study identified key challenges, including the variability in technical skills, data fragmentation, and resistance to change. Managers emphasized the importance of robust data infrastructure and adequate training to ensure successful AI integration. Conclusions The study reveals a complex landscape where the potential benefits of AI in hospital management are balanced with significant challenges and concerns. Effective integration of AI requires addressing technical, ethical, and cultural issues, with a focus on maintaining human elements in decision-making. AI is seen as a powerful tool to support, not replace, human judgment in hospital management, promising improvements in efficiency, data accessibility, and analytical capacity. Preparing healthcare institutions with the necessary infrastructure and providing specialized training for managers are crucial for maximizing the benefits of AI while mitigating associated risks. Supplementary Information The online version contains supplementary material available at 10.1186/s12913-024-11602-y.

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Research agenda for using artificial intelligence in health governance: interpretive scoping review and framework

Cited by 4 publications

References 102 publications

Use of Artificial Intelligence tools in supporting decision-making in hospital management

Use of Artificial Intelligence tools in supporting decision-making in hospital management

The application of artificial intelligence in health policy: a scoping review

Use of Artificial Intelligence tools in supporting decision-making in hospital management

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