Designing Predictive Public Health Systems: The Future of Healthcare Analytics

Abstract

The marketplace of healthcare is changing radically to take a proactive approach rather than a curative approach to health, and the core driver of this revolution is advanced analytics. This article is an inquiry into the theoretical underpinnings and practical examples of predictive healthcare analytics, including such examples of its implementation as the Provider Care management System at Anthem. It delves into how advanced information consumption systems, healthcare alerting systems, and risk prediction models can help healthcare providers detect patients at risk of clinical deterioration before it happens. The talk is about the technical framework behind these systems, comprising machine learning algorithms, natural language processing, and the ability to analyze data using time. The paper also covers the ethical questions and issues of putting predictive analytics into practice, especially on algorithmic fairness, information confidentiality, and the compatibility of systems. Given its vision of future integration with innovative technologies like artificial intelligence, genomic analysis, remote monitoring, and telehealth applications, it expects to be able to foresee negative events and also to prescribe individualized measures based on the unique traits of a patient.