https://intimedia.id/read/ai-in-healthcare-a-great-opportunity-or-a-major-challenge-for-indonesia#:~:text=Jakarta%2C%20INTI%20%E2%80%93%20The%20use%20of,regulations%2C%20and%20patient%20data%20security.
Jakarta, INTI – The use of artificial intelligence (AI) in Indonesia’s healthcare sector is expanding rapidly. AI has great potential to enhance healthcare service efficiency, from diagnosis to medical consultations. However, its adoption faces various challenges, including those related to medical personnel, regulations, and patient data security.
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 pros and cons of AI adoption in the country's healthcare sector.
Challenges in AI Adoption by Medical Professionals
One of the biggest challenges in implementing AI in healthcare is its adoption by medical professionals. Doctors and healthcare workers are divided into two main groups: those who quickly embrace AI and those who require time to adapt. To address this challenge, AI is being directly implemented in healthcare facilities such as hospitals, where doctors can participate in validating AI-generated results. This allows AI models to continuously improve while also enabling doctors to gain a better understanding of this technology.
To support this adaptation, training for medical professionals is a priority. This training is conducted through hands-on AI usage in the field, as well as through webinars and knowledge-sharing sessions with experts. This ensures that healthcare workers can understand the benefits of AI and how to integrate it into their daily practice.
Convincing Senior Medical Professionals
For medical professionals who still rely on conventional systems, AI adoption presents a unique challenge. Many fear that AI will replace their roles. To mitigate this concern, efforts are being made to demonstrate that AI serves only as a supportive tool, not as a replacement for doctors. The World Health Organization (WHO) has established principles for AI utilization in healthcare, including the requirement for doctors to validate AI-generated results.
As a strategic approach, AI is initially introduced in non-clinical areas such as medical record analysis and pre-consultation assessments before being applied to more complex aspects such as diagnosis and patient treatment. By involving doctors in validation processes, they are more likely to accept AI as a tool that enhances their efficiency.
Patient Data Security and Privacy
One of the key concerns in AI implementation in healthcare is patient data security and privacy. Medical records containing information on medications, diagnoses, and medical imaging results (X-rays, MRIs, etc.) are invaluable for AI training. However, their use must be strictly regulated to protect patient privacy.
Several measures have been taken to ensure data security:
- Data Anonymization: Patient identities are removed or masked before being used to train AI models.
- Local Data Storage: Health data must not be stored abroad and must be processed within the country to ensure security.
- Access Control: Only authorized personnel have access to patient data, with strict regulations governing its usage.
These measures aim to balance the utilization of data for improving healthcare services while safeguarding patients' privacy rights.
Regulatory and Infrastructure Readiness
On the regulatory front, the Indonesian government has begun formulating specific policies regarding AI usage in healthcare. The Ministry of Communication and Informatics (KomDigi) has issued AI regulations across various sectors, including healthcare. Additionally, the AI Task Force is drafting sector-specific regulations to ensure a cautious approach to AI implementation.
The healthcare sector differs from industries like banking, where AI errors do not have life-threatening consequences. Given that misdiagnoses can be fatal, stricter and more specific regulations are essential. Beyond regulations, infrastructure readiness is also a critical factor in optimizing AI implementation in Indonesia’s healthcare facilities.
AI Implementation in the Satu Sehat Application
The government has started integrating AI into digital healthcare applications such as Satu Sehat Mobile (formerly known as PeduliLindungi). AI in this application is designed to help users detect health risks such as hypertension through data-based predictions inputted by users. Additionally, a Large Language Model (LLM) is being developed to enable initial online medical consultations before patients visit a doctor.
Conclusion
AI in Indonesia’s healthcare sector presents significant opportunities, but also unavoidable challenges. Medical professionals need adequate education and training to maximize AI’s potential without feeling threatened. Patient data security must be strictly maintained, and clear regulations must be promptly established to mitigate potential risks.
If these challenges can be successfully addressed, AI has the potential to revolutionize Indonesia’s healthcare industry, improving medical service quality and assisting more patients in a more efficient and accurate manner. Is Indonesia ready to embrace this new era?
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