Clinical trials: considerations for designing and building an electronic data capture system

Part 2: with sponsors/CRO in mind

Part 2: Considerations for designing an electronic data capture system for clinical trials with sponsors/CRO in mind. Read our previous post, considerations for designing an electronic data capture system with users in mind, here.

In clinical trials, electronic data capture (EDC) systems are widely used to collect data such as patient outcomes, laboratory test results, medication use, adverse events, etc. A well‑designed EDC system makes it convenient for clinical trial sponsors or trial managers to track trial progress, monitor site compliance, query data, create reports of various trial parameters, and export data in easily used formats for analysis. Below are some best-practices to be considered for designing and building an EDC system that provides a positive experience for the sponsor/CRO.

Easy Navigation

An EDC system is primarily composed of a series of Case Report Forms (CRF). One of the keys to building an effective EDC system is using a design that is easy to learn and navigate. Typically, this is done by creating CRFs where each form covers a single aspect of the study, e.g., demographics, medical history, procedure, results and follow-up. A well planned CRF reflects the central elements of the protocol and is designed to facilitate data analysis. The CRF should not request extraneous data (i.e., “nice-to-have” rather than “need-to-have”). The EDC system’s framework itself should be clear and succinct such that it can be intuitively understood. Unlike a labyrinth of inadequately planned routes that require several clicks through menus and sub-menus that leave users confused and frustrated, the system’s organization should allow the user to quickly find what is needed. In addition, the EDC system should be helpful without being intrusive, giving input as the user navigates through the system. There should be an indication where the user is within the framework by means of a navigation scheme, enabling users to effectively return to a previous page. An advantage of using a framework that is simple to learn is the ability to train others easily, for example, site staff. Finally, to enhance easy understanding and accurate data entry, CRF organization within the EDC system should be uncrowded.

Efficient Workflow

The efficiency of EDC design is directly related to its structure. An effective framework enables sponsor/CRO staff to review data entry in less time. A good way to prevent erroneous data from being entered in the database and to minimize the need for subsequent queries is the judicious use of edit checks.  Edit checks are automated triggers within the system that ensure the data entered are complete and within the expected ranges. One should consider using edit checks that request clarification of the data when needed, but allow the user to continue to the next item or form after a clarifying comment is made, even if the required data are not provided. Another efficiency is to program certain fields to automatically calculate a value from the data already entered. This will improve accuracy and preclude the monitor from verifying calculations performed by site staff, thus, saving time during the data review process and minimizing queries.

Built-in Reports and E-mail Notifications

Some EDC systems include at least a rudimentary set of standard reports, which may be used by the trial manager to monitor various aspects of the clinical trial such as patient enrollment, outstanding data, or reported events. Additional specific, configurable reports are desirable for robust study oversight and management. As with building the EDC system, the design of reports should be well considered and planned prior to the start of the study. Well-designed reports can support compliance by directly comparing the trial’s requirements with the sites’ performance. For example, by creating custom reports, trial managers can analyze which CRFs receive the most queries, potentially identifying errors in the CRF design or other flaws that can be adjusted during the trial. When the clinical trial is completed, all of the reports should be easily exported along with the rest of the study data. MED Institute builds EDC systems with customizable reports that can help track various metrics in study oversight and management to complete trial more efficiently.

The EDC system should include automatic notifications for events of interest such as Serious Adverse Events or new subject enrollment. These notifications help the trial manager to directly access the pertinent information and to react in a timely manner without having to search the system to find the information.


It is essential to consider the configuration of the data in the back-end database, to ensure the data can be easily exported into and manipulated in other third-party programs (e.g., statistical programs). Executing a consistent data collection approach includes standardizing the definitions for the data that will be collected across the study. Implementing independent and conventional open standards, such as those created by CDISC, encourage compatibility and can lessen overall study build time. EDC systems should have an option to follow CDISC standards and for datasets to be aligned with CDASH guidelines so that the data are ready for convenient analysis in the future. This can be time-saving and efficient as non-CDASH data may need to have the data architecture re-worked to meet CDISC standards upon regulatory submission1. As end users become accustomed to basic standardized forms, they will require less training, deliver more reliable data, and shorten the data collection time.

Implementing a well-designed EDC system can have tremendous financial and productivity benefits for your clinical study and study team. As EDC designers at MED Institute Inc., we use time-tested best practices to help you meet EDC requirements to accelerate your study.

If you have any questions about how to design more efficient, cost-effective clinical trials, please call us at 855.463.1633 or visit our website


  1. Hume, Sam et al. “Current applications and future directions for the CDISC Operational Data Model standard: A methodological review.” Journal of Biomedical Informatics vol. 60 (2016): 352-62. doi:10.1016/j.jbi.2016.02.016

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