Understanding EHR-to-EDC Streaming in Clinical Research

Clinical trials play a pivotal role in improving patient outcomes and advancing medical knowledge. However, the process of data collection within these trials has historically been laden with challenges, including data entry errors, site staff burnout, and data transfer delays.

Additionally, the clinical trial landscape has evolved dramatically in recent years, with a considerable increase in the number of data sources and increasingly intricate trial protocols. Compared to a decade ago, the volume of data points requiring collection has tripled, and this trend shows no signs of subsiding.  These developments, while helpful for researchers, exacerbate the workload on study staff and perpetuate the cycle of human error and the need for source data validation (SDV), complications that delay trial timelines and increase trial costs unnecessarily.

Fortunately, the advent of advanced technological solutions, including EHR-to-EDC streaming, offers a beacon of hope, promising to mitigate this burdensome load and introduce new efficiencies to the clinical trial process.

What is EHR-to-EDC Streaming?

In recent years, the integration of electronic health records (EHRs) with electronic data capture (EDC) systems in clinical research has emerged as a promising solution to simplify and streamline the data acquisition and transfer processes within clinical trials. This integration, commonly known as EHR-to-EDC streaming, holds the keys to enhancing the efficiency and accuracy of clinical research and to reducing the workload on clinical trial staff. In this article, we delve into the intricacies of EHR-to-EDC streaming, exploring its value proposition, existing challenges, and potential applications.

EHR-to-EDC streaming automates the process of transferring data from the medical center’s EHR to the trial sponsor’s EDC. By seamlessly transferring data from the source (EHR) to the destination (EDC) database, EHR-to-EDC streaming effectively eliminates transcription errors, provides greater data oversight, and accelerates data entry timelines, all while reducing the burden on clinical trial staff.

Why Hasn't This Problem Been Solved?

Despite the obvious advantages, normalizing EHR-to-EDC systems in clinical research has not been easy. Let’s start by understanding why developing a technical solution has been fraught with difficulties.

• Lack of standardized data coding

Though there is some overlap, most medical centers in the world use proprietary systems for coding their medical data. This creates complexities when it comes to mapping the data and ensuring that every single data point gets to the proper place in the EDC.  Without a standard way of organizing data, it's like trying to fit puzzle pieces from different puzzles together—they just don't match up easily.

• Interoperability challenges

Interoperability poses a significant challenge in the context of EHR-to-EDC streaming. The disparate nature of EHR systems and EDC systems often results in incompatible data formats, structures, and terminology. This lack of harmonization complicates the exchange of clinical trial data, hindering the efficient transfer of patient information between these systems. Without standardized interfaces and protocols to facilitate interoperability, researchers face obstacles in accurately mapping and transferring data, leading to inefficiencies and potential errors in data interpretation.

Currently, many EHR-to-EDC streaming solutions require time-consuming and complex on-premises integrations, which makes data streaming expensive and complicated, especially for large, multi-center studies. A truly effective EHR-to-EDC streaming solution must be able to pull data from any EHR in the world without customized integrations or configurations. Developing this complex and flexible technology is not a simple feat.

• Privacy and security concerns

Privacy concerns add another layer of complexity to the adoption of EHR-to-EDC streaming in clinical research. Balancing the need for data accessibility with patient privacy rights presents a delicate challenge for stakeholders implementing EHR-to-EDC streaming solutions.

Patients rightly expect their medical information to be kept confidential and secure. The process of data sharing across platforms raises concerns about data breaches and unauthorized access. Healthcare organizations must navigate stringent privacy regulations, such as HIPAA in the United States and GDPR in the EU, to safeguard patient data during data transmission and storage. Addressing these privacy concerns requires robust encryption protocols, strict access controls, and data anonymization techniques to protect the most sensitive information.

• Resistance to change

As is the case in many industries, clinical trial professionals are often resistant to change and the adoption of new technology solutions due to several underlying factors. Firstly, there may be a perceived risk associated with implementing unfamiliar technologies, as they entail potential disruptions to established workflows and may require significant time and financial investments in adoption and infrastructure, resources which are scarce in many hospitals and startups.

Additionally, there are often concerns regarding data security and privacy, as mentioned previously. Stagnant organizational cultures and institutional inertia can further hinder the acceptance of novel approaches, with stakeholders preferring the familiarity of existing practices over the uncertainties of innovation. This is especially common in well-established medical centers and pharmaceutical companies that have a longstanding history of doing things in a certain way.

Resistance to change can also stem from a lack of awareness or understanding of the potential benefits that new technology solutions may offer, necessitating comprehensive education and stakeholder engagement efforts to overcome reluctance and foster adoption.

Finally, limited resources and budget constraints often prompt medical centers and sponsors to prioritize short-term financial considerations over investing in cutting-edge technologies such as EHR-to-EDC streaming, even when such solutions can offer significant, measurable long-term benefits.

EHR-to-EDC Streaming Options: On-Site vs. Cloud-Based Solutions

At the time of this writing, stakeholders have a choice between on-site and cloud-based implementations for EHR-to-EDC streaming. On-site solutions involve deploying software within the premises of research sites. These solutions tend to require substantial upfront investments in infrastructure and maintenance, and can be especially complicated in multi-site studies and studies with limited budgets.

In contrast, cloud-based solutions offer scalability, flexibility, and remote access advantages, often while costing less than those requiring on-premises integration. Leveraging cloud infrastructure, sponsors and medical centers can streamline data transfer processes from unlimited sources, reduce IT overhead, and enhance collaboration across geographically dispersed teams. Likewise, cloud-based solutions make it possible for medical centers in remote locations to connect directly to clinical trial EDCs, and for sponsors to widen their pool of candidates to those who would otherwise be deemed geographically undesirable. As a result of their convenience, cost-effectiveness, and inherent scalability, cloud-based solutions are increasingly gaining traction in the clinical research landscape.

Benefits of EHR-to-EDC Streaming

Whether you call it EHR-to-EDC streaming, EHR-to-EDC integration, or just plain data streaming, there is no question that this form of data transfer and interoperability can offer significant benefits to trials of all phases, sizes, and therapeutic areas.

• Decision-makers can benefit from real-time data oversight and the ability to make faster, more informed decisions that can help therapies get to market faster.

• Analysts can discover potential SAEs and protocol deviations earlier and take action faster to keep trial timelines on course.

• Automatic data transfer can significantly reduce the time and expense of SDV.

• Easier access to remote medical clinics makes it possible for sponsors and CROs to attract the most relevant subjects and to allow them to participate without the burden or expense of travelling to a larger medical center.

• EHR-to-EDC integration helps sponsors and medical centers adhere to the FDA’s 2018 guidelines which voiced strong support for pursuing the interoperability between EHR and EDC systems. Specifically, the guidance states: “FDA encourages sponsors and clinical investigators to work with entities that control EHR systems, such as health care organizations, to use EHR and EDC systems that are interoperable or fully integrated. […] FDA encourages sponsors and health care organizations to work with EHR and EDC system vendors to further advance the interoperability and integration of these systems.”

Conclusion

EHR-to-EDC streaming holds immense promise in revolutionizing data acquisition processes within clinical research. By leveraging technology, fostering collaboration, and embracing interoperability, stakeholders can navigate the complexities of modern clinical trials and accelerate the pace of medical innovation.

Through strategic investments in system-agnostic solutions and proactive efforts to address existing challenges, the clinical research community can usher in a new era of efficiency, accuracy, and patient-centricity in clinical trial operations.

‍