AI and Telehealth for Maternal Healthcare in Remote Areas of Indonesia: An Integrative Review

Abstract

Background: Indonesia continues to face one of the highest maternal mortality ratios in Southeast Asia, with the burden falling disproportionately on remote and archipelagic regions, where access to skilled birth attendants, referral systems, and obstetric facilities remains limited. Artificial intelligence (AI) and telehealth have been proposed as complementary strategies to reduce access and quality gaps.

Objective: This integrative review examines how artificial intelligence (AI) and telehealth technologies influence access to and quality of maternal healthcare services in remote areas of Indonesia.

Methods: This review followed Whittemore and Knafl’s five-stage integrative review framework. Literature published between 2015 and 2026 was retrieved from academic databases including PubMed, Embase, and Garuda journals. Eligible sources addressed telehealth, telemedicine, mobile health, or AI-based clinical decision support in maternal, antenatal, or obstetric care in Indonesia.

Findings: Sixteen studies met the inclusion criteria. Artificial intelligence and telehealth technologies represent complementary but unevenly developed strategies for addressing Indonesia's persistent maternal mortality disparities between urban and remote, western and eastern regions. Telehealth has an established decade-long track record of expanding access to antenatal, referral, and postnatal maternal healthcare in rural and remote Indonesian settings, contingent on infrastructure, workforce readiness, and policy support.

Conclusion: AI and telehealth technologies have meaningful, although geographically uneven, potential to improve maternal healthcare access and quality in remote areas of Indonesia. Requiring investment in connectivity infrastructure, workforce digital competency, interoperable data systems and privacy-protective data systems, and locally validated AI models.