The use of artificial intelligence-based innovations in the health sector in Tanzania: A scoping review

Sukums, Felix; Mzurikwao, Deogratias; Sabas, Deodatus; Chaula, Rebecca; Mbuke, Juliana; Kabika, Twaha; Kaswija, John; Ngowi, Bernard; Noll, Josef; Winkler, Andrea Sylvia; Wamala-Andersson, Sarah

doi:10.1016/j.hlpt.2023.100728

Cited by 9 publications

(5 citation statements)

References 29 publications

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“…In a scoping review conducted by Sukums et al [ 35 ] in 2021, a total of 16 publications were identified to have explored the use of AI-driven solutions in Tanzania’s health sector. The review called for Tanzania to establish a national AI policy and a regulatory framework for adopting reliable AI solutions in the health sector in line with the WHO guidance on ethics and governance of AI for health.…”

Section: Resultsmentioning

confidence: 99%

“…It also recognizes the enormous potential of processing large data and has entered public-private funding partnerships to accelerate data infrastructure development and drive innovation. However, as evidenced by the not entirely successful use of machine learning to predict and stem cholera outbreaks, such practices still have weaknesses, and there is a lack of experts skilled in securely collecting, processing, and interpreting large data [ 35 ]. In its latest DHS, Tanzania commits to deepening the competencies of health care workers by intensifying e-learning, training, and new curricula.…”

Section: Discussionmentioning

confidence: 99%

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Tanzania’s and Germany’s Digital Health Strategies and Their Consistency With the World Health Organization’s Global Strategy on Digital Health 2020-2025: Comparative Policy Analysis

Holl,

Kircher,

Hertelendy

et al. 2024

J Med Internet Res

Self Cite

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Background In recent years, the fast-paced adoption of digital health (DH) technologies has transformed health care delivery. However, this rapid evolution has also led to challenges such as uncoordinated development and information silos, impeding effective health care integration. Recognizing these challenges, nations have developed digital health strategies (DHSs), aligning with their national health priorities and guidance from global frameworks. The World Health Organization (WHO)’s Global Strategy on Digital Health 2020-2025 (GSDH) guides national DHSs. Objective This study analyzes the DHSs of Tanzania and Germany as case studies and assesses their alignment with the GSDH and identifies strengths, shortcomings, and areas for improvement. Methods A comparative policy analysis was conducted, focusing on the DHSs of Tanzania and Germany as case studies, selected for their contrasting health care systems and cooperative history. The analysis involved a three-step process: (1) assessing consistency with the GSDH, (2) comparing similarities and differences, and (3) evaluating the incorporation of emergent technologies. Primary data sources included national eHealth policy documents and related legislation. Results Both Germany’s and Tanzania’s DHSs align significantly with the WHO’s GSDH, incorporating most of its 35 elements, but each missing 5 distinct elements. Specifically, Tanzania’s DHS lacks in areas such as knowledge management and capacity building for leaders, while Germany’s strategy falls short in engaging health care service providers and beneficiaries in development phases and promoting health equity. Both countries, however, excel in other aspects like collaboration, knowledge transfer, and advancing national DHSs, reflecting their commitment to enhancing DH infrastructures. The high ratings of both countries on the Global Digital Health Monitor underscore their substantial progress in DH, although challenges persist in adopting the rapidly advancing technologies and in the need for more inclusive and comprehensive strategies. Conclusions This study reveals that both Tanzania and Germany have made significant strides in aligning their DHSs with the WHO’s GSDH. However, the rapid evolution of technologies like artificial intelligence and machine learning presents challenges in keeping strategies up-to-date. This study recommends the development of more comprehensive, inclusive strategies and regular revisions to align with emerging technologies and needs. The research underscores the importance of context-specific adaptations in DHSs and highlights the need for broader, strategic guidelines to direct the future development of the DH ecosystem. The WHO’s GSDH serves as a crucial blueprint for national DHSs. This comparative analysis demonstrates the value and challenges of aligning national strategies with global guidelines. Both Tanzania and Germany offer valuable insights into developing and implementing effective DHSs, highlighting the importance of continuous adaptation and context-specific considerations. Future policy assessments require in-depth knowledge of the country’s health care needs and structure, supplemented by stakeholder input for a comprehensive evaluation.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Tanzania’s and Germany’s Digital Health Strategies and Their Consistency With the World Health Organization’s Global Strategy on Digital Health 2020-2025: Comparative Policy Analysis

Holl,

Kircher,

Hertelendy

et al. 2024

J Med Internet Res

Self Cite

View full text Add to dashboard Cite

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“…We have chosen 2016 as the starting year of the review because while it was a year that showed significant advancement in AI, many were concerned about its ethical implications (Mills, 2016 ; Stone et al, 2016 ; Greene et al, 2019 ). Since AI is fast evolving, the literature from the recent years was used to obtain the emergent and most recent results (Nittas et al, 2023 ; Sukums et al, 2023 ). Figure 1 presents our review flowchart following PRISMA's guidelines (Moher et al, 2009 ).…”

Section: Methodsmentioning

confidence: 99%

Specific challenges posed by artificial intelligence in research ethics

Bouhouita-Guermech,

Gogognon,

Bélisle-Pipon

2023

Front. Artif. Intell.

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BackgroundThe twenty first century is often defined as the era of Artificial Intelligence (AI), which raises many questions regarding its impact on society. It is already significantly changing many practices in different fields. Research ethics (RE) is no exception. Many challenges, including responsibility, privacy, and transparency, are encountered. Research ethics boards (REB) have been established to ensure that ethical practices are adequately followed during research projects. This scoping review aims to bring out the challenges of AI in research ethics and to investigate if REBs are equipped to evaluate them.MethodsThree electronic databases were selected to collect peer-reviewed articles that fit the inclusion criteria (English or French, published between 2016 and 2021, containing AI, RE, and REB). Two instigators independently reviewed each piece by screening with Covidence and then coding with NVivo.ResultsFrom having a total of 657 articles to review, we were left with a final sample of 28 relevant papers for our scoping review. The selected literature described AI in research ethics (i.e., views on current guidelines, key ethical concept and approaches, key issues of the current state of AI-specific RE guidelines) and REBs regarding AI (i.e., their roles, scope and approaches, key practices and processes, limitations and challenges, stakeholder perceptions). However, the literature often described REBs ethical assessment practices of projects in AI research as lacking knowledge and tools.ConclusionEthical reflections are taking a step forward while normative guidelines adaptation to AI's reality is still dawdling. This impacts REBs and most stakeholders involved with AI. Indeed, REBs are not equipped enough to adequately evaluate AI research ethics and require standard guidelines to help them do so.

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“…For inclusion in this review, studies were meticulously selected based on their exploration and analysis of the intersection between Artificial Intelligence (AI) and Big Data within the domain of mobile health (mHealth) concerning healthcare systems. Specifically, studies were included if they discussed the role of AI in healthcare, the deployment of mHealth technologies, the use of Big Data analytics, innovation within healthcare systems, and the challenges within digital health (Sukums et al, 2023). Conversely, exclusion criteria were strictly adhered to, eliminating duplicates, studies outside the healthcare sector, articles not available in the full-text format, and those with a primary focus on industries other than healthcare.…”

Section: Eligibility Criteriamentioning

confidence: 99%

Untitled

2024

JALHE

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This systematic review explores the integration of Artificial Intelligence (AI) and Big Data in mobile health (mHealth) and their transformative impact on healthcare systems. Analysing 25 peer-reviewed articles, the review delves into the utilisation, innovations, and inherent challenges of AI and Big Data in various healthcare settings. The findings reveal that AI and Big Data significantly enhance diagnostic precision, personalise treatment strategies, and streamline healthcare operations. However, this technological advancement is not without its complexities. Key challenges identified include ethical dilemmas, data privacy and security issues, and preserving the human element within healthcare. The review underscores the risk of an over-reliance on AI and the criticality of using unbiased, representative data sets. The integration of AI into clinical practices, while promising, demands rigorous oversight and ethical governance. The review concludes that the successful adoption of AI and Big Data in healthcare hinges on a balanced approach that harmonises technological innovation with ethical, equitable, and human-centred healthcare practices. If managed effectively, this integration offers the potential for significant improvements in patient outcomes and operational efficiency yet requires vigilant management of the challenges to realise its benefits fully.

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The use of artificial intelligence-based innovations in the health sector in Tanzania: A scoping review

Cited by 9 publications

References 29 publications

Tanzania’s and Germany’s Digital Health Strategies and Their Consistency With the World Health Organization’s Global Strategy on Digital Health 2020-2025: Comparative Policy Analysis

Tanzania’s and Germany’s Digital Health Strategies and Their Consistency With the World Health Organization’s Global Strategy on Digital Health 2020-2025: Comparative Policy Analysis

Specific challenges posed by artificial intelligence in research ethics

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