The Essential Guide to eCRF (Electronic Case Report Form) for Medical Devices

In clinical investigations, investigators traditionally use paper Case Report Forms (CRFs) to collect data from participating patients, including patient characteristics and demographic data, adverse events, and the results of experimental treatments.

When a study is completed, paper CRF forms are boxed and shipped from the study site to the study sponsor, where the data will be cleaned, prepared, transformed, and transcribed into a computer database prior to analysis.

Paper-based CRFs have been standard practice in clinical investigation for decades, but medical device companies in recent years are increasingly choosing to digitize the data collection process with a new kind of CRF: electronic Case Report Form (eCRF).

In this essential guide, we’ll cover all the basics about eCRFs in clinical trials for medical device companies. You’ll learn what they are, how to design an effective eCRF, and the benefits of choosing eCRF instead of paper-based CRF for your next study.

FREE RESOURCE: Click here to download your free PDF copy of 7 best practices for how to design an electronic case report form.

What is an eCRF?

An eCRF (electronic case report form) is the digital version of a paper-based case report form - it’s a digital questionnaire completed by researchers to collect and report data from participating patients in a clinical trial.

While paper CRFs require physical storage, security, and transportation, collecting clinical data in a digital format with an eCRF means that the data can be securely uploaded to the cloud and shared with other stakeholders in near-real time. 

As a result, switching from paper-based data collection to eCRF can help medical device companies execute clinical studies in less time, with less risk, and at a lower cost.

Is eCRF the same as Electronic Data Capture (EDC)?

eCRF and Electronic Data Capture (EDC) are semantically similar terms that relate to data collection in clinical studies, which explains why certain sources are using these terms interchangeably. 

Still, eCRF and EDC are not the same thing and clinical study managers should understand the difference between them.

We’ve already defined eCRFs above as the digital version of a case report form that researchers will complete during a clinical trial.

An EDC system is a software solution, purpose-built to enable data collection as part of a clinical study. EDC systems allow sponsors to design eCRFs and provide a graphical user interface where researchers can complete and submit eCRFs as part of a clinical study. 

EDC systems can also enable other forms of data collection, including automatic transmission from electronic health records (EHR) and connected medical devices. 

Plus, EDC systems enable software-based controls on data entry and data access that help ensure the accuracy, authenticity, and security of clinical data. Click here to find out what other advantages to using an EDC system are and why it is a good idea to use an EDC made for medical devices.

Can I copy my paper CRF directly to the eCRF?

Concerned about the impact of adopting eCRF on clinical workflows? You might be wondering whether you can simply transcribe paper CRF documents into eCRF instead of requiring researchers to record data in a digital format.

You absolutely can choose to transcribe data into eCRF from paper source documents, however:

1. You will need to design a paper CRF and a matching eCRF to streamline the data entry process.

2. You will need to retain the source data in paper format to satisfy regulatory requirements.

3. The transcription process will introduce data entry errors that negatively impact data quality.

If your goal is to use eCRF in your study, designing your eCRF in a digital format is highly recommended, as your digital CRF can easily be transposed to a paper copy if needed. In contrast, it is often both time-consuming and costly to design a paper CRF and recreate it in a digital format. 

However, we recommend designing your eCRF from scratch, instead of copying the design from the paper-based CRF. Download our eCRF template to get the design of your eCRF right. 

How to design an eCRF

eCRFs are designed by clinical trial sponsors to collect data from a clinical investigation that can be used to test the experimental hypothesis and answer research questions that are relevant to the study. 

A common mistake in eCRF design is trying to collect too much data. Including more data fields on your eCRF means more time and money spent on data collection, entry, preparation, and analysis. A well-designed eCRF should capture just the data needed for the study, without any time-consuming extras that lengthen the data collection process without adding anything useful.

To achieve this, trial sponsors should plan their clinical investigations and data collection activities in detail before designing an eCRF. Here’s how to start designing a high-quality eCRF:

1. Craft a Clear Hypothesis

The first step to designing an eCRF is to craft a clear research hypothesis for your clinical investigation. Your hypothesis should include a prediction for how your medical device will help patients in the treatment group. 

Establishing a hypothesis is a critical step towards clarifying what data you must collect to support or refute your hypothesis, and what other data can safely be ignored in the context of your investigation.

2. Design a Statistical Analysis Plan

After establishing a hypothesis, you should prepare a Statistical Analysis Plan (SAP) describing how the data you collect during the clinical trial will be analyzed. This is when you’ll list exactly what data must be collected, and when, to enable a sound analysis that will either support or refute your research hypothesis.

Your SAP may also include descriptions of specific graphs, charts, or other visuals you hope to create using the data collected in your clinical trial.

3. Define Your Data Collection Plan

A data collection plan defines the specific questions you will ask to collect the data that’s needed to support or refute your research hypothesis. You can also document how those questions will be asked and how they might be formatted on a digital case report form (eCRF).

You can download our eCRF template to help you start documenting specifications for your eCRF as part of your data collection plan. 

4. Plan your Data Collection Activity

Planning data collection activities means describing how researchers will collect, capture, and store data during your clinical trial. To solidify your plan, you’ll need to document the answers to questions like:

• What data is available?

• What data will be collected?

• How much data will be needed?

• How will the data be collected?

• When will the data be collected? 

• Who will collect the data?

• Where will data be recorded or stored?

• How will data be shared?

By crafting a research hypothesis and establishing clear plans for gathering and analyzing your clinical data, you should be able to avoid the common mistake of collecting more data than is needed to test your research hypothesis. 

This is only one of the 7 most common pitfalls in clinical data collection for MedTech that we have identified along the years. If you want to learn how to avoid tripping over these pitfalls (you may not even know you're doing it already), we suggest you check out our blog post, here.

5. Follow 7 Principles of Good eCRF Design

SMART-TRIAL EDC gives our customers the ability to design and customize eCRFs for medical device clinical investigations, clinical performance, post-market clinical follow-up (PMCF), and post-market performance follow-up (PMPF) studies.

To share our expertise, we’ve authored a white paper detailing the most important best practices in eCRF design. In the paper, we identify the seven principles behind a Good eCRF design and how you can apply them to create a perfectly optimized eCRF for your next clinical study.

What are eCRF completion guidelines?

An eCRF is only as useful as the data entered into it. Even a well-designed electronic case report form can produce inconsistent, incomplete, or difficult-to-analyze data if study personnel are not aligned on how each field should be completed.

eCRF completion guidelines are the instructions that tell investigators, site staff, monitors, data managers, and other study personnel how to complete, correct, review, and sign an eCRF. These guidelines should explain how data should be entered, how missing or unavailable data should be handled, how corrections should be made, which fields are conditional, and how the eCRF should be reviewed before submission.

For medical device clinical investigations, completion guidelines help connect the study protocol, statistical analysis plan, data management plan, and EDC configuration. The goal is to ensure that every required data point is captured consistently, traceably, and in a way that supports the study’s endpoints.

Strong eCRF completion guidelines can help teams:

• Reduce avoidable data queries
• Improve consistency across study sites
• Clarify how to handle missing, unknown, or not-applicable data
• Standardize how adverse events, concomitant medications, visit dates, deviations, and clinical measurements are recorded
• Support cleaner downstream analysis
• Improve audit readiness through clearer data traceability

What should eCRF completion guidelines include?

There is no universal template that works for every clinical investigation because eCRF requirements depend on the study protocol, device type, endpoints, visit schedule, and EDC system. However, most effective eCRF completion guidelines should address the following areas:

• Field-level instructions: Define how each field should be completed, including required formats, units, allowed values, and conditional logic.
• Source data expectations: Clarify where the data originates and how site staff should transcribe, verify, or directly enter source data.
• Missing or unavailable data: Explain when to use values such as “Not Done,” “Unknown,” or “Not Applicable,” and when a comment or deviation entry is required.
• Date and time formats: Standardize date/time entry across sites to avoid ambiguity and downstream cleaning.
• Measurements and units: Specify units, decimal places, acceptable ranges, and whether values should be rounded.
• Adverse events: Define how adverse events should be recorded, including terminology expectations, onset/resolution dates, severity, relatedness, and action taken.
• Concomitant medications: Specify whether to use generic or trade names, how to record dose/frequency/route, and how to handle ongoing medications.
• Conditional fields: Explain when certain fields should appear or be skipped based on previous answers.
• Data corrections: Define how corrections should be made, who may make them, and what justification is required.
• Review and signature: Clarify when investigator review or electronic signature is required and what the signature represents.
• Training requirements: Identify which study roles must be trained before completing the eCRF and when retraining is needed after protocol or form changes.
• Version control: Explain how updates to the guidelines are reviewed, approved, distributed, and controlled within the quality system.
  
  

Note: The FDA’s guidance on electronic source data addresses source data used to fill predefined eCRF fields and emphasizes reliability, quality, integrity, and traceability from electronic source through regulatory submission.

Examples of eCRF completion guidelines

The examples below illustrate the type of field-level instructions that may be included in eCRF completion guidelines. These should be customized to the study protocol, EDC configuration, and data management plan.

• Demographics – Date of birth: Enter the participant’s date of birth in the required study format. If partial date collection is required by the protocol, follow the predefined partial-date convention and document any missing components.
• Visit information – Visit date: Enter the actual date the visit occurred, not the scheduled visit date. If the visit occurred outside the protocol-defined window, document the reason in the appropriate deviation or comment field.
• Vital signs – Blood pressure: Enter systolic and diastolic values in mmHg. Confirm that the values are within the protocol-defined acceptable range before submission.
• Laboratory results – Hemoglobin: Enter the result using the unit specified in the eCRF. If the test was not performed, select the appropriate missing-data value and provide the required explanation.
• Concomitant medications – Medication name: Enter either the generic or trade name according to study convention. Include dose, route, frequency, start date, and stop date or mark as ongoing where applicable.
• Adverse events – Event description: Use standardized medical terminology where possible. Avoid unnecessary free text when a controlled option is available.
• Device-related data – Device use or performance field: Enter the observed result according to the protocol definition. If the device was not used as expected, document the reason and link to the appropriate deviation or adverse event field if required.

Best practices for writing eCRF completion guidelines

Effective eCRF completion guidelines should make correct data entry the easiest path for study personnel. The best guidelines are clear, specific, role-aware, and maintained as controlled study documents.

1. Place instructions where users need them. When a field requires specific instructions, definitions, formatting rules, or conditional logic, place the guidance close to the field itself so users don’t have to search a separate document.
2. Use clear, concise, non-leading language. Explain how to enter data without influencing clinical judgment, and avoid ambiguous wording, jargon, and assumptions about EDC familiarity.
3. Define terms and data conventions. If the study uses specific conventions for missing data, partial dates, protocol deviations, device deficiencies, adverse events, or endpoint assessments, define them before data collection begins.
4. Align the guidelines with the protocol and SAP. Every field in the eCRF should have a reason to exist, and the guidelines should reinforce how each data point supports the protocol, endpoints, safety reporting, or statistical analysis plan.
5. Train users before data collection begins. All personnel responsible for completing or reviewing the eCRF should be trained on the guidelines before the study starts, with retraining when protocol amendments, form changes, or EDC workflow changes affect data entry.
6. Control guidelines within the QMS. Because completion guidelines affect clinical data quality, treat them as controlled documents with a defined, traceable process for creating, revising, approving, distributing, and retiring them.
7. Use EDC functionality to reduce manual instruction burden. Where possible, configure the EDC system to enforce required fields, accepted ranges, skip logic, edit checks, data formats, and role-based permissions so the system guides correct entry.

eCRFs, traceability, and regulatory expectations

For regulated clinical investigations, eCRF design and completion should support data integrity, traceability, and inspection readiness. In practice, sponsors should understand where each data point originates, who entered or changed it, when changes occurred, and how the final record was reviewed or signed.

Electronic records and electronic signatures may also need to meet applicable requirements for trustworthiness, reliability, and equivalence to paper records and handwritten signatures. FDA’s 21 CFR Part 11 establishes criteria for electronic records and signatures, including system validation, record protection, access controls, audit trails, training, written policies, and signature/record linking. Broader GCP context, such as FDA’s E6(R3) Good Clinical Practice guidance, can also be referenced while keeping the article focused on medical device clinical investigations.

What are the benefits of eCRF vs. Paper-based Reports?

1. Eliminate Unnecessary Data Duplication

Medical device companies doing paper-based data collection must maintain a physical copy of the original source data for security and compliance purposes. Using eCRF in clinical trials eliminates the need for data duplication and allows medical device companies to satisfy these requirements by storing data securely in the cloud with appropriate back-ups.

2. Reduce or Eliminate Transcription Errors

Paper-based CRF forms must be transcribed into a computer database before analysis, which introduces the potential for transcription errors. Collecting data electronically with eCRF eliminates transcription errors and results in better quality data.

3. Streamline the Data Collection Process

When researchers complete paper CRFs in a study, those records must be packaged, shipped, and transcribed before the data can be analyzed. With eCRFs, any data collected by researchers during a subject visit is available for review and analysis in near-real time - just as soon as it’s entered into the EDC system. 

Streamlining access to data accelerates the completion of clinical studies, provides a faster feedback loop for researchers, and enhances data access for all research stakeholders.

4. Facilitate Good Clinical Compliance

Collecting clinical data with eCRF can help medical device companies facilitate good compliance with clinical investigation standards like ISO 14155:2020. EDC software can also deliver automatic warnings and notifications to help companies comply with Good Clinical Practices (GCP) as outlined by the International Conference on Harmonization (ICH).

Greenlight Guru Clinical's EDC software offers SMS and email notifications and comes with SOP and QA templates to facilitate ISO 14155:2020 and GCP compliance.

5. Facilitate Remote Data Monitoring

Clinical study monitors are responsible for ensuring that studies proceed in compliance with the experimental protocols, GCP, and relevant regulatory requirements. They also work to ensure that the rights of subjects are protected, and that study data is accurate and complete.

Using eCRF enables monitors to remotely access documentation from the clinical study over the Internet as an alternative to supervising the study in person. Remote monitoring reduces costs and increases the efficiency of clinical studies.

6. Enable Real-Time Data Access

Data recorded on eCRF is not constrained to a single physical location. Instead, the data is uploaded to the Internet where it can be accessed almost immediately by other stakeholders with the appropriate authorization and access credentials.

7. Mitigate Security Risks of Physical Paper

Paper CRFs are subject to a number of physical risks, including loss, theft, fire and water damage. Medical device companies can eliminate these risks by collecting data with eCRF and storing the data in a secure cloud environment.

8. Preserve Clinical Data for Audits

When clinical data is collected using eCRF in clinical trials and securely stored in the cloud, a digital data trail is created and preserved for inspector audits and regulatory review.

9. Reduce the Cost of Clinical Studies

Scientific research on the impact of choosing eCRFs over paper-based data collection have suggested that eCRFs accelerate the completion of clinical studies and reduce the cost of data collection. In one research paper that analyzed data collection in 27 clinical studies between 2001 and 2011, those using eCRF had a total cost of 374€ (381 usd)  per patient, while those with paper-based data collection cost 1,135€ (1156 USD) per patient.

10. Reduce Downstream Data Queries and Corrections

A well-designed eCRF can reduce data quality issues before they occur. When completion guidelines are combined with EDC features such as required fields, edit checks, range validation, skip logic, and automated alerts, study personnel receive clearer direction at the point of entry. This reduces the likelihood of missing, inconsistent, or incorrectly formatted data, and reduces the number of manual data queries that monitors or data managers must issue later in the study, helping clinical teams move more efficiently from data collection to review, cleaning, analysis, and reporting.

FREE RESOURCE: Click here to download your free PDF copy of 7 best practices for how to design an electronic case report form.

Design Your eCRF and Collect Clinical Data with Greenlight Guru Clinical

Greenlight Guru Clinical (formerly SMART-TRIAL) is an EDC system that enables clinical study sponsors to digitize the process of collecting, integrating, and securely storing data for clinical investigations, in-human studies, and post-market surveillance activities.

With Greenlight Guru Clinical, medical device companies can design highly customized eCRFs, then deploy those eCRFs in clinical studies to replace paper-based data collection, eliminate the risk of transcription errors, and reduce the cost of running the study.

As the first and only electronic data capture software designed for Medical Devices and Diagnostics, Greenlight Guru Clinical provides capabilities for gathering data in clinical studies, performance studies, PMCF/PMPF studies, surveys, registries, cohorts, case series, as well as from connected devices and wearables.

Ready to learn more? Contact us for a customized demo.