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demographic needs. Policymakers can coordinate with scientists, doctors and researchers to apply the insights gleaned to develop public health solutions that are in sync with local resources and wellness practices. Healthcare information interpreted in dialects and languages comprehensible by the public and patients will empower them to actively participate in their own health decisions. STRENGTHENING THE PUBLIC HEALTH MANAGEMENT ECOSYSTEM Ideally, applications based on generative AI will enable patients’ data and medical records to be easily transferred across various care settings, thereby creating a truly patient-centric health management ecosystem. The health management value chain can extend to both before (ideally) and after acute events in community clinics or at home: patients could attain earlier diagnoses at community clinics, undergo treatment and initial monitoring at hospital, and receive post-treatment prognosis and maintenance care at home or community clinics. Health management systems supported by generative AI applications provide and encourage more contact points between patients and health professionals, making health management a day-to-day event as opposed to acute events only. Continuity of care across different care settings should result in better health outcomes, more efficient allocation of healthcare resources and lower overall healthcare costs for providers. TAP THE BENEFITS OF GENERATIVE AI To get organised to effectively deploy generative AI as a healthcare tool, there are a few obvious requirements: ● Reliable internet access and network security ● Well-documented and labelled electronic medical records, or at least a system to capture case data
consistently going forward while digitising existing records ● A strong community-level primary care or telemedicine network with health professionals that patients trust Furthermore, the public needs to be guided to utilise community-level healthcare resources whenever possible and also be educated on the uses and limitations of generative AI applications in health care. Health solutions should incorporate technical accessibility of the vulnerable and elderly populations. Local data is the key for locally attuned treatment options, population health solutions and biomedical research. Policymakers need to develop regulations that protect patients’ data privacy and information integrity. However, the regulations should be balanced, ensuring they will not stifle the utilisation and mobility of health data for global biomedical R&D and development of tools that advance health equity. GLOBAL COLLABORATION The accuracy of an LLM likely increases with the volume of data it is trained on. Once
Continuity of care across different care settings should result in better health outcomes, more efficient allocation of healthcare resources and lower overall healthcare costs for providers”
countries start to organise their healthcare systems towards digitalisation, available quality data will surge. Access to comprehensive global health data can provide potential insights that are non-achievable with single population data. This can guide health innovations and interventions to areas with the highest needs. Global communities should develop a regulatory framework that enables countries, organisations and individuals to share stratified data and anonymised information across borders. The World Health Organization’s collection and analysis of daily Covid-19 data from countries during the pandemic is one example of a central repository of health data. Generative AI’s potential is immense; a cohesive global coordination in health can further harness and amplify its effectiveness as a tool in promoting public health and global health equity. A POTENTIALLY POSITIVE CATALYST The need to keep healthcare costs under control is a top priority for many governments. Generative AI-based tools, community-based healthcare delivery systems and population health-focused solutions can be key to help manage costs, evaluate treatment effectiveness and improve overall health outcomes. With good policies, effective planning and active participation, in addition to a cohesive global coordination effort, generative AI can be a positive catalyst for better resource allocation into communities that are in greater need and at higher risks. ▪
VANESSA HUANG Vanessa Huang, general partner at BVCF Management, is a member of the WHO Council on the Economics of Health For All, which aims to reframe Health For All as a public policy objective. bvcf.com ZHI YANG Dr Zhi Yang is founder and chair of BVCF Management. He launched the firm in 2005 when he returned to China after two decades studying and working in the United States with the vision to bring the VC-driven innovation model to China. He launched BVCF as one of China’s first venture capital/private equity firms focused on the healthcare sector.
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Health: A Political Choice – From Fragmentation to Integration
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