Gaps in AI Implementation in Healthcare: Insights from Recent Research
Recent research conducted by university scholars in collaboration with Thai policymakers has highlighted several obstacles to the effective implementation of artificial intelligence (AI) in the healthcare sector. This initiative forms part of the Association of Pacific Rim Universities’ (APRU) “AI for Social Good” project, which is being executed alongside the United Nations Economic and Social Commission for Asia and the Pacific. The project aims to evaluate the challenges faced in integrating AI technologies within Thailand’s healthcare framework.
Key Findings on AI in Healthcare
The findings from this two-year project, which received funding from Google, stress the necessity for supportive policies to enhance AI capabilities in healthcare. Christina Schönleber, chief strategy officer for APRU, stated that the project aimed to create transparent AI ecosystems that align with sustainable development objectives.
The Role of AI in Healthcare
Research suggests that AI can play a crucial role in improving the efficiency of healthcare services, enhancing patient outcomes, and advancing medical research. Recent innovations in AI, including voice-to-text and generative AI tools for summarizing patient data, have shown considerable promise for healthcare practitioners.
Challenges in Data Sharing
Jasper Tromp, an assistant professor at the National University of Singapore and research lead for the APRU project, pointed to the importance of addressing barriers and facilitators related to data sharing for AI applications in healthcare in Thailand. The project underscored that effective data sharing is vital for the successful deployment of AI technologies, yet many governments remain unaware of the obstacles that impede such initiatives.
Identifying Key Obstacles
The research identified significant challenges, including limited data availability and inconsistent standards for data storage, which hinder the development and implementation of AI solutions in healthcare. One of the project’s objectives, in collaboration with the Thai Office of National Higher Education Science Research and Innovation Policy Council, is to propose guidelines that facilitate data sharing among government agencies and private entities, including companies and academic institutions.
Current Efforts in Thailand
Efforts are ongoing in Thailand to enhance local AI capabilities tailored to healthcare needs, particularly in areas outside of major urban centers. Despite the potential advantages, the implementation of AI-assisted healthcare faces notable challenges, particularly since many existing algorithms are based on datasets that may not accurately reflect the local Thai population.
The Drive for Domestic AI Solutions
Tromp indicated that the push for establishing a domestic AI industry is driven by the need for applications that are contextually relevant and the high costs associated with foreign AI healthcare solutions. Several companies in Thailand are currently developing AI applications, focusing on areas such as chatbots and image recognition technologies.
Addressing Barriers to Data Collection
Research efforts have begun to illuminate specific barriers to data sharing and effective data collection within the Thai healthcare context. Complications arise from the variety of software systems utilized for data collection, disparities in data architectures, and the fragmented nature of healthcare services.
Future Regulatory Recommendations
The final report from the APRU is expected to address an insufficient understanding of the value of data and the challenges associated with data security and privacy. New regulations, including Thailand’s Personal Data Protection Act, have further complicated the landscape of data sharing. The report recommends the establishment of a regulatory ‘sandbox’ that would enable innovation in a controlled environment with reduced regulatory burdens.
Importance of Collaboration
The collaboration between researchers and policymakers is regarded as essential for tackling the unique challenges associated with AI in healthcare and for developing policy frameworks that can effectively support the integration of AI solutions in Thailand.
Source: University World News
