AI technologies in reducing hospital readmission for chronic diseases: a recommended framework

The complex progression, specialised care, and comorbidities of chronic diseases place a financial and health burden on society. In some instances, the high hospital readmission rate is also a result of chronic diseases. There is an emerging trend in deploying technological advancements like artificial intelligence (AI), the Internet of Things (IoT), sensors, wearables, social media, mobile apps, and genomics to decrease hospital readmission. In some instances, predictive analytics, early warning systems, personalised care management, remote monitoring and Telehealth, decision support systems, patient education and engagement, and other areas of artificial intelligence and machine learning have outperformed traditional approaches in lowering hospital readmission. However, the ethical principles relating to AI systems should be considered to achieve autonomy, prevent harm, achieve fairness, and achieve explainability. To this end, this study examines the significant impact on health and the economy of hospital readmission for chronic diseases and the role of AI in reducing readmission. Moreover, we analyse the existing challenges of AI technologies hindering them from reaching their full potential. We further scrutinise these challenges and potential solutions in the context of a fictional case study to provide guidelines for future research endeavours in this context.