It can be said that a successful medical device clinical study is defined by its results. To achieve the best possible outcome it is necessary to generate quality data. As Electronic Data Capture (EDC) becomes the new standard, the focus is on these systems to have built-in features that make the entire data management process easier. One such built-in feature and the focus of this blog post is the importance of queries for eCRF data. This post highlights the query functionality, how it works and what the benefits are of using it.
What is a Query?
Prior to the adoption of EDC systems, queries were collected using paper. Queries were raised manually using spreadsheets which were extremely time-consuming and not to mention the complication of accidental data being entered or removed. Furthermore, the spreadsheets could be accessed by one person at a time complicating the whole process. In several cases, this erroneous data led to altered analysis.
Now, the use of EDC is much more common and these types of data entry errors can be dealt with at the source through Queries.
According to the CDISC a query is, “A request for clarification on a data item collected for a clinical trial; specifically, a request from a sponsor or sponsor’s representative to an investigator to resolve an error or inconsistency discovered during data review”. Subsequently the management of a query is an, “Ongoing process of data review, discrepancy generation, and resolving errors and inconsistencies that arise in the entry and transcription of clinical trial data”
Why you should use queries in your studies?
- With an EDC system, Query management can be done continuously with up-to-date data because the system is continuously updated which saves time and resources.
- In the case of incorrect data, electronic queries are generated automatically on values outside the user-defined range and can be answered immediately by the investigator.
- As opposed to paper, all users with the right permissions have access to the queries generated and can respond quickly.
- An example that highlights the benefits of queries is that the data can be monitored remotely, and check for instance: if the medication registered at a later stage might be in conflict with the inclusion/exclusion criteria and then consider whether the subject should be excluded from the study, or they remain included.
- Furthermore, fully validated EDC systems document all corrections made to the data which allows the users to keep track of the status of the query.
How do queries work in SMART-TRIAL?
The way it works is that if data entry staff have entered data that is inaccurate a certain red flag or ‘QUERY’ is raised. In SMART-TRIAL there are two types of Queries:
The first type of query is ‘system-generated’ which acts as a red flag that is automatically generated when the data entered falls outside the predefined values. This type of query needs to be marked as ‘closed’ for it to be resolved and is added into the Query overview view.
The second type of query is ‘manually-created’ and starts when an investigator or monitor finds inaccurate or missing data. These are queries that the system cannot automatically generate. Similar to system-generated these queries need to be resolved for it to be completed.
How to use Queries in SMART-TRIAL?
In SMART-TRIAL queries can be raised in the form of comments or a message on specific eCRF data points. All studies in SMART-TRIAL have access to queries, but only users with the ‘Query permission’ will be able to access them. These users receive email and in-app notifications when any query related activity takes place.
Creating system-generated queries in SMART-TRIAL
System generated queries in SMART-TRIAL are triggered when Validation Rules are added during Form creation. This automatically compares the entered data in an eCRF against the values set in the Validation Rule. When creating a Validation Rule you choose between different operators like ‘larger than’ or ‘smaller than or equal to’ to create checks on numerical and date- and time-based inputs. When the Validation Rule is triggered, you ask SMART-TRIAL to create a Query. And it is denoted as ‘System Generated Query’
Additionally, similar to commonly known ‘edit checks’, SMART-TRIAL can validate if an answer from a specific Form violates a condition which is related to another answer. For example, you can create a Reference Rule, which checks if an answer is ‘greater than or equal to’ another answer in a previous completed Form (or Data Event).
Responding to system-generated queries requires the investigator or monitor to review the entered data. By choosing to respond to the query the user will have to specify in the dialogue box the reason for accepting and/or editing the entered data.
By setting up system generated queries you will improve data quality by minimizing confusion and eliminate input errors.
Watch a short how-to video to see System generated queries in action ⬇️
Creating manual queries in SMART-TRIAL
With the query permission, creating a manual query in SMART-TRIAL is easy. When you encounter inaccurate Form answers you can create a query. On choosing to create a query a dialogue box will appear where you are to ask a question or make a comment.
Once you have added in your comment the query will appear underneath the question with the Name, Date, and Time-stamp. The query will be added to the Query overview and study personnel will get notified that a query has been created.
Responding to the query requires you to either respond or decline in either case you need to fill in a comment based on your activity. If you choose to respond then similar to creating a query, the dialogue box will appear and you are prompted to fill in your comment/reasoning. This process continues until the involved study personnel comes to an agreement. On coming to an agreement the query can be closed. Queries need to be marked as ‘Closed’ for them to be completed. All actions are documented and accessible from the Audit log and query overview view.
Both types of queries are available in the ‘queries overview view’. This gives you control over the queries and provides you with an outline of their status as shown in the image below.
Watch a short how-to video on manually generating queries in SMART-TRIAL ⬇️
In conclusion, clinical study outcomes are very much dependent on the collection of accurate quality data. However, we are all prone to make mistakes, it can happen! But if there are several inconsistencies in the data collected this can impact the entire study negatively. To ensure that you are collecting accurate and compliant data there are several procedures that you can implement and Queries is one such proven way.
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