Evaluating Practices, Overcoming Pitfalls, and Integrating Artificial Intelligence for Enhanced Quality in Advancing Ambulatory Care

Abstract

BACKGROUND: For delivering health-care services in addressing preventive care, medical requirements of nonemergency, and the management of chronic diseases, ambulatory care is characterized outside of the hospital setting. The interest in artificial intelligence (AI) integration into ambulatory care settings has increased with the rise of technological advancements. However, by prompting the requirements for systemic assessment across different health-care systems, the AI implementation in ambulatory care is varied. OBJECTIVE: The aim of conducting this study is to investigate the current status of AI in the services of ambulatory care across five Asian countries such as Myanmar, Malaysia, China, Indonesia, and the Philippines. The implications for health-care delivery are discussed and the common challenges are identified during this study. MATERIALS AND METHODS: The descriptive research strategy was employed during this study, and within ambulatory care, the surveys targeting administrators, nurses, and doctors were utilized. For assessing the impact of AI implementation, statistical analysis including quantitative techniques and Likert scale ratings was conducted. The sample size can be validated and the respondents can be selected using the pilot study and purposive sampling. RESULTS: The significant variations in treatment protocols and health-care delivery models across surveyed countries were revealed by the obtained findings. The compromised health-care quality and accessibility issues were identified as a few of the challenges in ambulatory care services that are identified during the findings. For enhancing patient engagement, data management, and decision support, the AI integration into electronic health records was evaluated. DISCUSSION: For enhancing patient outcomes and health-care delivery, the understanding of variation significance in ambulatory care practices is emphasized by the respondents. As an essential aspect of different countries, collaboration among health-care professionals is highlighted. The challenges in ambulatory care services are addressed by system-level interventions. The implications of AI integration are discussed during this study along with its roles in enhancing cost reduction in ambulatory care settings. CONCLUSION: The significance of AI integration in enhancing patient outcomes across diverse health-care systems is underscored. The collaboration among stakeholders is fostered and the complex challenges are addressed by the successful implementation of AI.