Artificial Intelligence in Primary and Community Care: Nursing Interventions to Improve Maternal Health Outcomes

Abstract

Artificial intelligence (AI) is a developing technology that is now being enthusiastically applied to primary and public healthcare, and it embraces transformative potential in maternal health. Change initiatives, such as predictive analytics, isolated care, and customized care plans, are AI-based and intended to enhance the initial identification of pregnancy problems, adherence to prenatal care, and general maternal health outcomes. This evolutionary shape has shifted the scientific interest to AI interventions, which are nurse-led, patient interaction, and the outcome measures like maternal morbidity, prenatal visits compliance, and early complication sources. This research will focus on AI-based nursing interventions in primary and community-based care that impact the maternal health outcomes. Studies included risk-prediction models, wearable care devices, and nurse-decision support systems, all of which involved a minimum of four weeks of maternal care. The results suggest that AI-supported nursing manifests to enhance the early detection of high-risk pregnancies with ease of providing instruments to intervene, and it encourages care provider compliance with prenatal appointments. Maternal complications and patient satisfaction were improved by an improved level of patient education, all-time monitoring, and decision-making based on data. AI-tech results in nursing care in primary and public care are a potential, secure, and real intervention that would increase the maternal health results, but enduring sustainability and the overall implementation of the trend in training still need more examination.