Jakarta, INTI – Artificial intelligence (AI) is playing an increasingly significant role in transforming various sectors, including healthcare. With technological advancements and broader data integration, AI has enormous potential to enhance the quality of healthcare services, accelerate diagnoses, and support more effective treatments. One of the key factors in the development of AI in the healthcare sector is collaboration among various stakeholders, including the government, academia, startups, and the healthcare industry.
In an exclusive interview conducted by the INTI Media team on March 5, 2025, Mr. Setiaji, Chief of the Digital Transformation Office (DTO) at the Ministry of Health of the Republic of Indonesia, provided in-depth insights into the opportunities for AI development in the healthcare sector.
Collaboration as the Foundation of Digital Healthcare Transformation
The healthcare sector’s success in handling the COVID-19 pandemic demonstrated that collaboration is a crucial factor in the effective implementation of AI. One strategic initiative already undertaken is data integration through the Satu Sehat platform. Currently, more than 40,000 healthcare facilities are connected to this system, enabling patients and doctors to access synchronized medical records across different facilities. With integrated data, healthcare professionals can perform more accurate diagnoses and health analyses.
Beyond data integration, collaboration is also being expanded to include health tech startups, system developers, and academic communities. The goal is to create AI-based innovations that can comprehensively enhance healthcare quality, covering preventive, curative, and rehabilitative aspects.
Digital Health Transformation Strategy 2024-2029
To ensure the long-term utilization of AI, the government is developing a Digital Health Transformation Strategy through 2029. One of the main focuses of this strategy is to improve healthcare service quality by leveraging available health data. AI will be used to analyze treatment effectiveness, predict public health trends, and provide data-driven policy recommendations.
With AI, it is now possible to track the number of patients with specific diseases, such as diabetes or cancer. The next challenge is analyzing the effectiveness of treatments, patient recovery rates, and disease patterns that can be prevented early on. The application of AI in this field is expected to enhance disease prevention and reduce reliance on curative treatments.
AI Applications in Diagnosis and Treatment
The use of AI in disease diagnosis has seen significant advancements. For example, during the COVID-19 pandemic, diagnostic methods evolved from conventional tests that took a long time to AI-based tests that could deliver results within minutes. AI is now also being used in genomic data analysis for more personalized treatment (precision medicine).
One emerging innovation is pharmacogenomics, which utilizes AI to determine the optimal drug dosage for each individual based on their genetic profile. This approach allows for more effective treatments while minimizing side effects. Additionally, the concept of virtual patients is being developed to conduct digital clinical trials before testing on humans, thereby accelerating the research and development of new drugs and therapies.
AI and Disease Prevention
In addition to diagnosis and treatment, AI also plays a role in improving preventive healthcare. Through AI-integrated free health screening programs, individuals can assess their health conditions early and take necessary preventive measures. AI can also link health data with external factors such as environment, pollution, sanitation, and dietary habits, providing a more comprehensive picture of the factors influencing public health.
As a concrete step in AI development for healthcare, an AI Hackathon will be held this year, bringing together startups, investors, and innovators from both domestic and international backgrounds. This event aims to find AI-driven solutions to tackle various healthcare challenges, including tuberculosis (TB), cancer, and other chronic diseases. Furthermore, the innovations generated from this event have the potential to be further developed in an industrial sandbox, an ecosystem that supports AI testing and implementation in the healthcare industry.
Conclusion
AI holds great potential to transform healthcare services in Indonesia. With strong collaboration among stakeholders, optimal data integration, and a sustainable digital strategy, AI can help improve healthcare system efficiency, accelerate diagnoses, and provide more personalized and effective treatments. In the future, AI applications will not only focus on patient care but also on disease prevention and improving the overall quality of life.
With these rapid advancements, AI is no longer just a future technology but a tangible solution that will continue to evolve and bring significant benefits to the healthcare sector in Indonesia.
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