Harnessing AI and Big Data in Advancing Southeast Asia’s Predictive Healthcare

Harnessing AI and Big Data in Advancing Southeast Asia’s Predictive Healthcare

Eps. 0 Townhall Muda and the Idea of “Collaborative Hub”

Oct 31, 2023

This article was written by Andy Fernanda Probotrianto

One of the issues that still haunts Southeast Asia’s path to equitable healthcare is the lack of access to quality care. This hardship is mainly driven by the fact that a significant portion of Southeast Asia’s population — almost three-fourths of the region — reside in non-urban areas. Rural remoteness has become a factor that hinders the building of necessary infrastructure and healthcare delivery.

Disproportionate distribution of healthcare talents also adds to the issue. As of 2020, the World Health Organization (WHO) notes that the Southeast Asian region is still below the international threshold of the minimum number of nurses and midwives — 37 per 1,000 population (from the ideal 40 per 1000 population). The health institution hence urged the region to redouble endeavours in increasing number of nurses and midwives’ cadres by 1.9 million to achieve health for all by 2030.

The geographical barriers and talent deficit problem is worrying, considering the region's vulnerability. Having survived two major outbreaks, notably the Avian Influenza A (H5N1) and the recent COVID-19 Pandemic, and with growing numbers of non-communicable diseases (NDCs) cases due to changing lifestyle, essential efforts need to be in place to mitigate healthcare limitations and ensure faster and accurate responses.

Innovation as Catalyst

In the era of disruptions, breakthrough in technological advancement is expected to be the bridge between existing gaps in healthcare delivery. Particularly with the coming of generative artificial intelligence (AI) and Big Data, which brings a new era for predictive and precision medicine. The discourse was heavily discussed during a Site Visit of Global Future Fellows 2023: Advancing Southeast Asia’s Predictive Healthcare to Google Indonesia in Jakarta on 4 October 2023.

Around 40 fellows are actively engaging in knowledge sharing to foster innovative solutions and cross-sector collaborations, drawing from their varied backgrounds and healthcare expertise. Through studying the achievements of Google’s initiatives and their influence on enhancing healthcare in the Southeast Asia region, these fellows are gaining valuable insights into leveraging technology in medical fields.

Image 1. Mr. Anang Efendy, Country Manager of Enterprise and Public Sector at Google Cloud Indonesia, speaking in front of Global Future Fellows during the Site Visit Session at Google Indonesia (Photo by Pijar Foundation)

The usage of BigData has been seen as tremendously essential in facilitating convenience and accessibility of health information exchange (e.g., medical records and data on disease spread), with integration and centrality at its core. This would fill the geographical gap as information could be easily obtained remotely.

At the same time, generative AI would empower health professionals by leveraging its rapid analysis to give a timely response and precision diagnosis. This would be of most use in regions where health specialists are scarce. Provided with sufficient technological savviness, responders and healthcare workers could work hand-in-hand with AI in determining the best course of treatment for patients.

Google Cloud has worked on this technology since they introduced The Healthcare Data in 2021. The technology empowers healthcare leaders, researchers, and clinicians with AI’s interoperability to gather real-time patient data, advanced analytics, and AI capabilities, enhancing the responsiveness and comprehensiveness of healthcare systems.

Mr. Anang Efendy, Country Manager of enterprise and Public Sector at Google Cloud Indonesia, unveils that Google Cloud also uses Med-PaLM 2, which leverages large language models (LLMs) for accurate and safe medical information retrieval. This technology enables healthcare organisations to answer complex medical questions, extract insights from medical texts, and summarise documentation, contributing to informed decision-making. With strong analysis, the future of healthcare capacity would be better equipped to predict the potential coming of diseases and optimising patient care accurately.

Additionally, Mr. Efendy also highlights how the same technology is implemented from the average user side, as it launched Google Bard. The LLM is integrated with other Google features, such as the Google Search Engine and Google Map, to assist users in preliminarily identifying which sort of care they need and referring them to the relevant facilities and professionals.

Future of Healthcare Amid Technological Disruptions

AI has emerged as a game-changer in the healthcare system, revolutionising how medical professionals diagnose, treat, and manage patient care. AI technologies, including machine learning, natural language processing, and computer vision, are making significant inroads into healthcare for many applications.

Image 2. Fellows of Global Future Fellows 2023: Advancing Southeast Asia’s Predictive Healthcare at Google Indonesia (Photo by Pijar Foundation)

The Site Visit to Google Indonesia reaffirms this reality. Ensuring how the healthcare system could benefit the most from technological advancement is one of the central aspects addressed in the fellows’ Collaborative Action Plan — a manifestation of synergy for the future of regional predictive healthcare.

Overall, Google Indonesia welcomes the fellows and the Pijar Foundation to study and use their innovations. This collaboration could contribute to the creation of a more comprehensive and adaptive healthcare system, not only in Indonesia but also in the Southeast Asia region.

The 2023 Global Future Fellow (GFF) with the theme “Advancing Southeast Asia’s Predictive Healthcare” is a collaboration with the Unilab Foundation (ULF) and the ASEAN Business Advisory Council (ASEAN-BAC). Pijar Foundation extends its greatest appreciation to all collaborators, fellows, and supporters for contributing to the success of this site visit.

This article is written by Maria M. Wijaya and Andy F. Probotrianto,

Edited by Cazadira F. Tamzil & Anthony M. Dermawan.

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