6 Common Data Challenges For Clinical Researchers

January, 2024
6 Common Data Challenges For Clinical Researchers

Clinical research coordinators are some of the most hard-pressed professionals in clinical trial execution.

Typically the first point of contact for multiple clinical trials, and responsible for managing the clinical data for those trials, clinical research coordinators are increasingly being asked to do more with less. More trials, more data points, more complex criteria for suitable patients… The role is growing in size and scale, yet with finite resources to complete the tasks.

The pace of change and improvement in the wider industry is encouraging to all of us involved in making clinical trials more efficient. But, the role of clinical researchers remains challenging. Here are six of the perennial challenges clinical trial researchers typically face:

Tedious manual search for data

The vast majority of data required for a clinical trial is collected as part of the day-to-day care of patients. It’s important that clinical teams can go about providing care as seamlessly as possible, so clinical data recorded at the point of care is then identified and re-used in trials, without adding to the data burden for clinicians.

Given that the shift from paper-based notes to digital (or eSource) clinical data is relatively recent, for researchers, this has historically been a significant task, involving leafing through handwritten notes. But even though data is increasingly being recorded in digital formats, the process clinical researchers go through is still highly manual. Searching through databases, scanning for information, and re-inputting data into the study database – all this manual effort means that one short form for a clinical trial can take hours to complete.

Time-consuming, error-prone manual re-keying of data

When it comes to re-inputting data, this typically involves identifying data in the EHR, memorising, then hopping over to the EDC and manually re-keying the data into the appropriate field. It’s a process that is time-consuming, error-prone and tedious for researchers. The potential for errors to creep into the re-typed data is high. This, in turn, leads to another long and time-consuming phase of checking, querying and correcting errors.

Manual translation of data into the required format

As laborious as the above process sounds, it’s not even as simple as that. Often the format required in the sponsor’s system is different to that used in the EHR. Units of measurement may differ, coding and ontologies may not match. So, before re-keying the data, the researcher translates it into the required format. Repeatedly remembering or looking up which format is required and making sure that the data is transformed correctly is tiring and time-consuming for researchers. Not to mention, it’s not the type of work many would say they dreamed of when entering the world of clinical research.

Juggling multiple systems and protocols

All of this manual process of taking data from one system to another is typically completed with an inefficient, outdated setup of multiple or split screens. Separate systems don’t ‘talk’ to each other, the researcher needs to log in to (and remember credentials for) multiple different systems, and they spend their time switching back and forth between systems continually.

Added to this, clinical researchers manage multiple tasks at any given time, each with differing protocols. The number of trials is open-ended and can vary considerably, but the clinical research coordinators we speak to typically manage an average of 7-8 active trials at once. Each protocol will have its own nuances in the data required and researchers are constantly jumping between these, trying to keep on top of different requirements. This is a huge contributing factor for fatigue setting in, as well as for errors creeping in.

Poor quality data and time spent searching for missing data

One of the biggest frustrations across the board in healthcare and clinical research is poor quality data. High quality data is essential for clinical trials, as well as for improving healthcare for patients. But all too often, clinical researchers are faced with missing or incomplete data. When data in the study database is flagged to be queried, researchers spend time re-checking EHR data to identify whether there is a transcription error, missing data, an error in the source data, or otherwise. And when data is found to be missing in the EHR, this has to be queried with the clinical team, which can add days or even weeks to the time taken to complete a form.

Slow, poorly designed systems and interfaces

Clinical systems deal with huge amounts of complex, often sensitive data. While the leading current systems have done much to alleviate the complexity of handling and storing this data, unfortunately, the user experience is often lacking when it comes to using them for research purposes. Clear navigation, intuitive design and smooth operation are not common features of the user interfaces clinical researchers are faced with.

This means training on new systems can be an arduous task, and processes are slowed down due to design factors.

Archer: The solution designed to change the experience of clinical researchers

Archer is the eSource-to-sponsor data solution that finally relieves clinical researchers of the tedious manual data work that takes up so much of their time.

Designed to address the challenges study sites face with bringing clinical data into sponsors’ study databases, Archer is the solution researchers love to use. With speed, accuracy and ease of use, researchers can retrieve, review and export relevant data in a few clicks.

Archer’s powerful mapping engine means lighting quick retrieval of all the relevant data from the EHR, automated transformation of data into the correct format, and one click to confirm the export of data into the study database. One easy-to-use system, no trawling for data, and accurate, clinically validated, normalised data available to researchers in seconds. Any data that is missing from the EHR is clearly highlighted, meaning no time is wasted searching for data in the wrong place. And the mental drain of switching between trials and their nuances is removed.

With Archer, clinical researchers can focus their time on ensuring quality, resolving the more complex queries and taking more time to identify and speak to patients.

Find out more about how Archer transforms the day-to-day work of clinical researchers. Contact us and ask for a demo.


About IgniteData

IgniteData is transforming the future of clinical trials through its cloud-based Virtual Research Assistant, Archer. A system-agnostic solution, Archer brings modern interoperability between EHR and key research applications, such as EDC. Providing seamless, secure transfer of clinical data, Archer is the global EHR-to-sponsor solution for modern clinical trials.

If you would like to find out more, contact our team.

All content 2024 IgniteData. All rights reserved, Registered in England and Wales number 09054143

Terms & Conditions | Privacy Policy | Cookie Policy

Call Us

Contact Us

Get Started