Nowadays, with the aim of enhancing the safety of the population by employing targeted strategies, community health management plays a crucial role in this through focused interventions. With the development of new and advance technologies like machine learning (ML), there has been a surge in using data-oriented approaches to optimize community health initiatives has been taken place. This paper explores the various ways of optimizing hospital resource allocations, like Google searches, hospital records, pharmacies, and pharma companies, by using different strategic ways. This study offers a comprehensive overview of current improvements and case studies. This synthesis seeks to develop a roadmap for implementing ML into community health management, which will ultimately enhance public health outcomes and decision-making process.