Indonesian stakeholders in the healthcare sector see artificial intelligence (AI) as vital in creating health tech in the future, potentially allowing for quick obtainment of analytical results that can serve as a foundation for shaping public health policies.
Agus Rachmanto, Deputy Chief of the Digital Transformation Office (DTO) at India’s Ministry of Health and Family Welfare (MoHFW), stated on Friday that precise data is significant in forming public health rules.
However, the country’s substantial population and lack of healthcare workers pose challenges, making data collection through research and field surveys laborious and expensive.
For instance, the government’s actions to address malnutrition or stunting in Indonesia require quite a large number of health workers and volunteers to perform studies, visits, and identify affected areas.
Rachmanto said with AI, data gathering and processing can be done faster and more efficiently than manually conducting it.
AI can be used to analyze existing data within the Ministry of Health’s (MoH) applications and platforms, like SATUSEHAT and ASIK, found in community health clinics, hospitals, and government health offices.
Moreover, since SATUSEHAT’s launch in 2022, it has utilized the cloud to keep electronic medical record (EMR) data from thousands of healthcare sites in Indonesia.
The cloud-processed data is expected to aid the government’s observation and monitoring of disease patterns and their spread nationwide.
Rachmanto stated that employing the cloud is aimed at the technology being a reliable method to assist the DTO team’s efforts in business processes, data storing, product development, and application operation.
The Deputy Chief assured that the health data kept in their cloud is secured, encrypted, and backed up properly. He added that stating an application is also made to guarantee it has no security issues, addressing any potential gaps, should there be any.
AI Enables Outbreak Surveillance in Indonesia
According to a report, AI demonstrated a capability to run surveillance of possible disease outbreaks.
Individuals suffering from a particular disease are required to report to health personnel locally, while the healthcare workers relay cases at a provincial level before the case is ultimately looked at by agencies at the central level.
The process from the first reporting stage to finally reaching central health officials often takes a month, slowing down efforts to address an outbreak.
Rachmando underscored the importance of immediate responses during pandemics, calling for the use of AI to aid in recognizing such information earlier for quicker anticipation.
According to his research, outbreak alerts are frequently from social media, as more people tend to share case information via status updates rather than reporting them to health experts.
Rachmando presented the possibility of using social media analysis as an early sign to investigate the potential of an outbreak.
Upon confirmation of the information, the government can take necessary actions, from determining the extent of healthcare resources to be used to the interventions needed to handle the issue.
