AI for Population Health Management: Predicting Health Trends and Improving Community Health

Abstract

An application of the new technological advance is the use of artificial intelligence in population health management where population-level data sources can be used in anticipating health risks, recognizing rising susceptibilities or proactively designing preventive measures. Machine learning and predictive analysis techniques are becoming more prevalent to analyse various health information including, clinical health records, environmental and social health indicators. This paper aims to discuss the importance of AI in improving data analysis, forecast the existing health concerns and develop intervention measures that addresses community needs. The utility of AI is also important for identifying and redressing health inequalities, enhancing the delivery of primary care and generating policies supported by strong evidence. Nonetheless, AI introduced problems in the application to population health management such as privacy, fairness, and accessibility questions. This is especially important in public health as AI is often applied in decision making processes. Finally, the paper examines potential recommendations for future uses of AI in enhancing the health of the public and minimizing the gaps prevalent in health.