Health-care leaders’ perspectives on AI implementation in Uganda: overcoming barriers, driving innovation and strategic considerations DOI
Mahadih Kyambade,

Afulah Namatovu

Leadership in health services, Journal Year: 2025, Volume and Issue: unknown

Published: April 17, 2025

Purpose The implementation of artificial intelligence (AI) in health care presents significant opportunities for improving efficiency, decision-making and patient outcomes. However, health-care leaders often face resistance multiple challenges adopting AI technologies, leading to slow inconsistent implementation. This study aims explore the perspectives Uganda regarding adoption, focusing on barriers, innovation drivers strategic considerations necessary effective integration. Design/methodology/approach used a qualitative, exploratory approach using semi-structured interviews with 24 from various public institutions Uganda. Data collection took place December 2023 February 2024. analysis was conducted qualitative content an inductive identify key themes related strategies. Findings identified three main categories affecting Uganda’s system: External Constraints, including regulatory gaps, limited funding infrastructure deficits; Institutional Capacity Change Management, highlighting change, lack technical expertise inadequate leadership support; Transformation practices, which includes concerns about AI’s impact job roles, ethical data security. Despite these challenges, acknowledged potential enhance service delivery, improve diagnostic accuracy optimize workflows. Practical implications findings underscore need targeted strategies, investment education training professionals, development clear policies frameworks fostering collaboration between institutions, policymakers technology providers. Strengthening capacity change management ensuring deployment are crucial successful adoption. Originality/value contributes body research adoption perspective developing countries, particularly Unlike previous studies that focus general acceptance, this provides leadership-centric barriers approaches insights generated can inform policymakers, administrators developers designing more tailored resource-constrained settings.

Language: Английский

Resilience and recovery from an environmental disaster: the journey of child survivors of the Kiteezi landfill in Uganda DOI Creative Commons
Mahadih Kyambade, Luke Sewante,

Afulah Namatovu

et al.

Cogent Social Sciences, Journal Year: 2025, Volume and Issue: 11(1)

Published: Feb. 16, 2025

Language: Английский

Citations

1
Impact of social influence, financial literacy, and self-control on saving behavior among micro and small enterprise owners in Uganda DOI Creative Commons
Eva Mpaata, Mahadih Kyambade,

Augustine Matovu

et al.

Cogent Psychology, Journal Year: 2025, Volume and Issue: 12(1)

Published: March 5, 2025

Language: Английский

Citations

0
Health-care leaders’ perspectives on AI implementation in Uganda: overcoming barriers, driving innovation and strategic considerations DOI
Mahadih Kyambade,

Afulah Namatovu

Leadership in health services, Journal Year: 2025, Volume and Issue: unknown

Published: April 17, 2025

Purpose The implementation of artificial intelligence (AI) in health care presents significant opportunities for improving efficiency, decision-making and patient outcomes. However, health-care leaders often face resistance multiple challenges adopting AI technologies, leading to slow inconsistent implementation. This study aims explore the perspectives Uganda regarding adoption, focusing on barriers, innovation drivers strategic considerations necessary effective integration. Design/methodology/approach used a qualitative, exploratory approach using semi-structured interviews with 24 from various public institutions Uganda. Data collection took place December 2023 February 2024. analysis was conducted qualitative content an inductive identify key themes related strategies. Findings identified three main categories affecting Uganda’s system: External Constraints, including regulatory gaps, limited funding infrastructure deficits; Institutional Capacity Change Management, highlighting change, lack technical expertise inadequate leadership support; Transformation practices, which includes concerns about AI’s impact job roles, ethical data security. Despite these challenges, acknowledged potential enhance service delivery, improve diagnostic accuracy optimize workflows. Practical implications findings underscore need targeted strategies, investment education training professionals, development clear policies frameworks fostering collaboration between institutions, policymakers technology providers. Strengthening capacity change management ensuring deployment are crucial successful adoption. Originality/value contributes body research adoption perspective developing countries, particularly Unlike previous studies that focus general acceptance, this provides leadership-centric barriers approaches insights generated can inform policymakers, administrators developers designing more tailored resource-constrained settings.

Language: Английский

Citations

0