The use of artificial intelligence (AI) is rapidly increasing in all areas of our lives, which has similarly led to a wave of innovation. Healthcare use from diagnosis to patient management has shown reduced inefficiency and improved patient management, thereby improving the overall quality of healthcare delivery. AI integration is rapidly occurring in developed countries, but developing countries have not yet benefited from their use. Due to limited resources, the lack of healthcare capabilities and weak infrastructure have led developing countries to face unique challenges when integrating AI into their healthcare systems.
Essentially, AI uses advanced algorithms and machine learning models to simulate human intelligence in decision-making, pattern recognition and problem solving. In addition to improving management efficiency, there is a wide range of applications in health care systems, ranging from imaging analysis, diagnosis to personalized treatment recommendations. As healthcare systems are overgrown and largely underfunded in developing countries, AI offers several benefits and opportunities.
AI-equipped diagnostic tools
Diseases such as tuberculosis, malaria, and NCD can be screened earlier with the help of AI-powered diagnostic tools. Rural Health Post can allow you to screen for different illnesses without expensive equipment or professionals. AI-based chatbots and clinical decision support systems help ultimate healthcare professionals provide much-needed guidance, ultimately reducing the need for professionals and costs.
AI can process huge amounts of data in a relatively short period of time to predict disease outbreaks, disease patterns, and suggest appropriate public health interventions. Integration of AI into a telehealth platform can improve the accuracy of diagnosis, patient management, and save lives for rural people whose geographical barriers prohibit them from receiving care in emergencies.
While there are significant benefits to integrating AI into healthcare, there are several barriers that are hindering implementation in developing countries. From uninterrupted power supply to reliable internet connections, to digital record keeping systems, there are several requirements for using AI. Therefore, in order to take advantage of the benefits of AI, you need to have all of these basic requirements.
Medical records exist in developing countries. However, they are almost incomplete, inconsistent, and the digitization process is often slow. The use of AI relies on high-quality data sets and importing them from developed countries may not be appropriate as there are significant differences in disease patterns, genetic diversity, and social determinants. However, initial investments in technology, infrastructure and training limit their use in developing countries. Without a proper plan, once funding is finished, donor-funded pilot initiatives will fail.
AI tools can be cost-effective in the long term, but upfront investments in technology, infrastructure and training can be prohibitive. In many developing countries, there is no legal framework to regulate the use of AI in healthcare. Many issues agree to accountability in the use of AI from patient privacy. Therefore, you need the right policies and frameworks before using AI in healthcare.
Healthcare is a relatively personal issue, and trust in AI technology can be unacceptable at first, especially in developing countries. The fear of unemployment, mistrust of machines, and lack of knowledge with digital systems are barriers that create resistance from both patients and healthcare workers. Therefore, increasing digital literacy and demonstrating its benefits can increase its acceptance.
It is essential for developing countries to adopt context-specific, equitable, sustainable AI systems. The first and most important is to enhance your digital infrastructure, including uninterrupted electricity, reliable internet and cloud systems. Governments should consider public and private partnerships in these efforts. We recommend starting to digitize medical records, standardize reporting systems, and encourage data sharing across hospitals.
Training local healthcare talent is paramount before importing AI tools. By training health professionals, data scientists and policy makers, you can increase your digital literacy, making informed choices and reducing your reliance on foreign technology providers. Similarly, a clear legal framework is required to protect patient rights, privacy and accountability. Therefore, it is proposed to adopt existing guidelines that incorporate local realities.
advantage
It is also recommended that you launch pilot programs in priority areas such as tuberculosis detection, NCDS screening, and maternal health. A successful pilot program can be gradually expanded through the incorporation of local realities. A comprehensive initiative is needed to train and engage all stakeholders, from patients, healthcare workers to policy makers. Rather than replacing healthcare talent, AI tools need to demonstrate that they are for the support of reducing fear and increasing confidence.
The use of AI in healthcare environments in developing countries presents both significant benefits and challenging challenges. It can provide potential benefits in solving problems such as shortages in healthcare talent, delayed diagnosis, and unfair access, but it can also create technical dependencies and exacerbate existing inequality. Therefore, careful planning, careful investment and ethical protection are essential for the use of AI in the healthcare environment of developing countries.
Therefore, it is essential to adopt a practical approach focusing on strengthening digital infrastructure, training local healthcare personnel, and scalable pilot initiatives. Therefore, careful use of AI in healthcare environments can improve the lives of millions of people living in developing countries.
(Dr. Lohanis is clinical director of the Nepal Drug and Poison Information Centre. LOHANIS@gmail.com)
