AI Integration in Clinical Decision Support Systems Enhancing Patient Outcomes through SMART on FHIR and CDS Hooks

Abstract

There is a potentially game-changing opportunity for improving patient outcomes in the healthcare industry via the incorporation of Artificial Intelligence (AI) into Clinical Decision Support Systems (CDSS). A focus of this study is on the use of SMART on FHIR (Fast Healthcare Interoperability Resources) and CDS Hooks to enhance clinical decision-making processes. The paper investigates the synergy that exists between artificial intelligence technologies and clinical decision support systems (CDSS). With an emphasis on interoperability, SMART on FHIR offers a powerful framework for integrating apps into electronic health records (EHRs). This framework makes it possible to install applications and share data in a smooth manner. on the other hand, CDS Hooks improves decision support capabilities by delivering clinical suggestions in real time that are aware of the environment in which they are being used. These recommendations are based on patient data and clinical processes. In order to analyse huge volumes of patient data, recognize trends, and provide suggestions that are supported by evidence, AI-driven clinical decision support systems (CDSS) make use of sophisticated algorithms and machine learning models. This integration makes it possible to implement therapies that are both personalized and timely, hence enhancing the precision and effectiveness of clinical decision-making. By guaranteeing that artificial intelligence applications may be readily incorporated into preexisting electronic health record systems and clinical processes, SMART on FHIR and CDS Hooks make this process easier to accomplish.