Optimization Erp Systems In Healthcare Industry Using Artificial Intelligence
Keywords:
Natural Language Processing (NLP), Artificial Intelligence (AI), Healthcare ERP, Machine Learning, Predictive Analytics, Robotic Process Automation (RPA), Operational Efficiency, Clinical Decision Support, Hospital Management, Healthcare AutomationAbstract
The healthcare business is under more and more pressure to provide timely, high-quality, and cost-effective patient treatment while also handling complicated administrative and operational tasks. Traditional Enterprise Resource Planning (ERP) systems are important for bringing together different parts of a hospital, but they typically don't work well when it comes to being flexible, responding quickly, and making smart decisions. This study looks at how adding Artificial Intelligence (AI) to healthcare ERP systems changes the way they work and how well they do their jobs. We look at how important AI technologies like Machine Learning (ML), Predictive Analytics, Natural Language Processing (NLP), Robotic Process Automation (RPA), and Computer Vision can help with decision-making, cut down on mistakes made by people, make the best use of resources, and allow for real-time data analysis. The study also looks at how AI is changing both clinical and administrative ERP modules. It shows how automation, smart forecasting, and inter-module connectivity can improve patient outcomes and the performance of the institution. The results show that AI-powered ERP systems make it possible to go from reactive to proactive healthcare management. This lays the groundwork for better, data-driven, and patient-centered healthcare delivery.
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