<p>Electronic health records (EHRs) are huge, distributed systems, and usually use different and incompatible standards. Achieving seamless EHR integration is crucial for providing a comprehensive view of patient health and enabling collaborative use of data across healthcare systems. Interoperability, the primary mechanism for achieving such integration, has become a central research topic within the artificial intelligence and medical informatics fields in recent years. Beyond EHR–EHR exchange, interoperability is also required between EHRs and clinical decision support systems (CDSSs), as well as among different CDSSs. This paper presents a comprehensive review of recent research on interoperability in EHR and CDSS ecosystems, focusing on both data and knowledge interoperability. Current survey publications have addressed the idea of interoperability from a narrow perspective, such as standards and technologies, but there have not been any reviews that have looked at interoperability from an architectural integration perspective. This paper broadly reviews recent interoperability literature in data and knowledge interoperability domains. This review provides a background of EHR and CDSS systems and then discusses the different techniques, approaches, and standards to achieve interoperability in EHR and CDSS systems. A new interoperability classification is proposed, including (1) EHR-EHR interoperability, for the global integration within a single EHR system or among heterogeneous EHR systems, (2) CDSS-EHR interoperability, for the integration of EHR data and CDSS knowledge, and (3) CDSS-CDSS interoperability, for the integration of various CDSS knowledge bases. To our knowledge, no prior survey has examined these three dimensions of interoperability together. Achieving these levels of integration is expected to enable smoother EHR systems and facilitate modular, anonymous, and seamless integration of CDSSs within healthcare ecosystems.</p>