JMIR Publications

ABSTRACT

Background:

The use of electronic medical records (EMRs) and clinical registries has transformed healthcare delivery by improving data management, care coordination, and research capacity. However, the full potential of these technologies can only be realized through effective interoperability, thereby reducing the burden of manual data entry and enhancing the utility of real-world clinical data.

Objective:

This review explores existing technologies used to facilitate automatic data capture and transfer methods which promote interoperability between patient EMRs and clinical registries.

Methods:

A search of PubMed, CINAHL, Embase and Web of Science involved three key concepts: (1) “registry”, (2) “electronic medical records”, and (3) “interoperability”. A two-phase screen identified studies utilizing technologies to facilitate automatic data extraction or interoperability within a health context.

Results:

Thirty-five studies met inclusion criteria and were included in the final review. Twelve countries over five continents were represented, addressing a wide range of acute and chronic health conditions. Epic was the most frequently used electronic medical record system, while the most used registry platforms were REDCap, SQL Server Database and EMR-embedded solutions. Various technologies were employed to facilitate automated extraction and transfer of data from the EMR onto clinical registries, with approaches often tailored to align with data formats and institutional requirements.

Conclusions:

The findings highlight the growing global adoption of technological solutions to support data interoperability between EMRs and clinical registries. The selection and subsequent implementation of technologies were consistently shaped by contextual factors, highlighting the need for tailored approaches. While these advancements have reduced reliance on inefficient, error-prone, and resource-intensive manual processes, ongoing challenges in data standardization, seamless integration, and long-term sustainability are compounded by poor and inconsistent reporting across studies. Many studies lacked the methodological detail required for replication or meaningful comparison, and the limited application of implementation science frameworks further hindered the ability to assess real-world effectiveness, feasibility and scalability. To maximize the full potential of EMR-linked registries in driving high-quality research to improve patient outcomes, future initiatives must not only adhere to robust governance frameworks that uphold data security, patient privacy, and regulatory compliance, but also address existing gaps through co-designed, context-sensitive approaches to improve data quality, interoperability, and equitable adoption across healthcare settings.