Streamline and Optimize Research Workflow in Eligibility Queries While Searching for Patients

Quieries in Clinical Trials

Clinical researchers are not developers. This is why they are often reluctant to use commercial tools used for operational purposes.

But they can repurpose them for research!

For example, let us look at the workflow engine. 

CR uses a very primitive tool:

  • Inquiries one by one, one at a time;
  • It takes a very long time to find the right patients (for example, diabetes overweight 65+);
  • Every inquiry takes 5-10 minutes, and in the end, the result can be zero… so it can take weeks.

One interesting solution is creating a more sophisticated process:

  • We can set up automated inquiry after inquiry based on the results;
  • And we can make a report and send the results to the researcher’s email.

We end up with not just process automation but an aggregated workflow to optimize the researcher’s work. Finding cohorts of patients that meet the eligibility criteria becomes so much easier. As a result, you lower the pressure on technical resources too.

What is Query Management?

Queries are communication tools used in the clinical trial process to clarify and resolve discrepancies and discrepancies found in the data. Clinical trials are essential in driving scientific discovery, but they are just as valuable as the quality of the data they produce.

You can see automation examples at various stages:

  • Data entry into a centralized database;
  • Monitoring data closely instead of verifying all data;
  • Using electronic data capture systems (EDCs) consistently;
  • Integrating electronic health records (EHRs) so data can be transferred quickly and checked automatically;
  • Remote access: if you can get data from a hospital without having to go there in person, it will take less time to check it and make sure it is safe for the patient;
  • Using wearable devices and biosensors.
Query Management in Clinical Trials

Query formation, management, and resolution

Queries are questions that come up during validation checks. The sponsor (the person or organization paying for the research) or someone working for the sponsor creates the queries. Then the queries are sent to the site (the place where the research is being done) responsible for answering the question or fixing the error. Once the query is responded to and completed, the information is sent back to the sponsor so they can put it in their database.

In the past, queries were created when people working on clinical research or clinical trial (CRAs or CTMs) would go through all of the data, paperwork, and other forms to check for any mistakes. Any discrepancies were then noted on a spreadsheet and manually checked to ensure they were resolved before being updated to a completed status.

This process was crucial for clinical trials, but it was often done inefficiently and was expensive in terms of resources and time. The problem was that it relied on the skills of the individuals without standardization between all sponsors.

Some ways we have improved the process include getting data directly from devices like blood pressure and blood sugar monitors and having more than one person enter data from paper forms into one central database. The software we use for the database is often designed to find things that don’t make sense – like an impossible date of birth for a patient or values that wouldn’t be possible for a person to have – and then bring those discrepancies to the attention of site staff so they can double-check. 

However, we still need people to verify the data and do on-site visits because it’s only sometimes accurate. Now, we’re using technology to make it easier to manage data and improve the trial process.

What are the benefits of queries?

  • Compliance with the protocol;
  • A completed collection of data;
  • Patient Safety;
  • Data quality assessment at each trial site;
  • Getting ahead of other errors;
  • Ensuring successful regulatory audits.

What’s Next?

Query management is essential to clinical trials, ensuring that the trial follows all the rules and regulations and that the data collected is accurate and valid. In the past, this process has been inefficient and expensive, but new digital solutions and centralizing data management can help clinical trials produce life-changing solutions more quickly and cheaply.

Anatoly Postilnik

Head of the Healthcare IT Practice at First Line Software

Anatoly has more than 30 years of technology, product development, and solutions delivery experience, including over 20 years in the Healthcare Industry. Anatoly resides in Boston, MA. He is an avid hiker and has reached numerous mountain tops in Europe, Eastern and Western United States, and Asia.

Anatoly Postilnik

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