Finding out where the right patient cohort exists for your research can often feel complicated before a study has even begun.

The new Cohort Discovery Service, available through the , has been redesigned to make that process simpler, faster and more intuitive 鈥 whether you鈥檙e completely new to Cohort Discovery or an experienced researcher building complex queries.

Here鈥檚 a look at what鈥檚 changed, and how the new service is helping researchers move from initial idea to meaningful insights more quickly, and with less complexity along the way.

Start with everyday language, not technical terms

One of the biggest changes is the introduction of natural language search. Instead of needing detailed knowledge of the (OMOP CDM) terminology or complex query logic, researchers can now begin a search using plain English. For example, typing 鈥渁dults under 35 with asthma鈥 into the search bar.

Screenshot of the Cohort Discovery Service application. A search box contains the query 鈥渁dults under 35 with asthma.鈥 Below, the query builder area includes options to add a rule, add AND/ OR logic, add an age rule, or add a group. There鈥檚 鈥淐lear Query鈥 and 鈥淩un Query鈥 buttons on the right.
Cohort Discovery query builder interface showing a natural language search for “adults under 35 with asthma”, with options to add rules, age criteria, and groups before running the query across selected collections.

The service automatically translates this into relevant clinical concepts and helps users refine the meaning as they go. From there, additional filters can be applied through the interface such as age ranges, event dates, inclusion or exclusion criteria, or additional conditions through the interface.

This means researchers can start exploring cohort feasibility immediately, without needing specialist technical knowledge to get started. Once a search has started, the platform also provides support throughout the query-building process.

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Guidance that appears when you need it

The new interface includes built-in support throughout the query-building process. As users move through the service, the guidance panel updates dynamically depending on what they are doing. Whether refining a condition, adding filters or building more advanced queries, relevant help appears automatically alongside the workflow.

Screenshot of the Cohort Discovery query builder. The query describes people diagnosed with mild asthma and aged between 18 and 35 years. In the central workspace, a diagnosis rule is configured to include individuals with 鈥淢ild asthma (OMOP 4155468).鈥 Buttons allow users to add a timeframe or age criterion to the rule. A side panel titled 鈥淒iagnosis Rule鈥 shows the inclusion setting selected and provides additional controls for adding age and timeframe parameters. 鈥淐lear Query鈥 and 鈥淩un Query鈥 buttons are displayed in the top-right corner.
Cohort Discovery query builder displaying a diagnosis rule that includes people with mild asthma, with options to add age and timeframe criteria before running the query.

There are also videos, guidance panels, and help shortcuts available throughout the platform, helping users feel supported and making it easier for first-time users to explore the service independently.

Screenshot of the Cohort Discovery Help section on the 鈥淨uery Building Tutorials鈥 tab. The page is part of the General Guidance area and includes navigation tabs for Overview Tutorials, Query Building Tutorials, Results Tutorials, History Tutorials, and Collection Admin Tutorials. Two tutorial video cards are visible: 鈥淗ow do I build a simple query?鈥 labelled Beginner, and 鈥淗ow do I build an advanced query?鈥 labelled Advanced. Each card includes a video thumbnail and play button.
Cohort Discovery Help page displaying query-building tutorial videos, including beginner and advanced guides to help users create queries.

Build simple or advanced queries

The redesigned query builder supports both simple and highly detailed cohort searches. Users can:

  • start with natural language
  • build queries manually
  • combine multiple conditions
  • select several matching search terms at once (for conditions, observations, etc.)
  • apply age and date filters
  • create grouped logic using AND/ OR rules
  • use OMOP vocabulary-based searching where needed

This balance between simplicity and flexibility was a key focus of the redesign. A researcher can begin with a simple, plain English language query, whereas experienced users might build more advanced, logic-based searches using advanced tools when needed.

The redesign also focuses on helping researchers work more flexibly once queries have been created.

Compare and revisit searches more easily

The updated query experience also makes it easier to refine and compare cohort queries. Users can:

  • save, export, and revisit previous searches
  • open multiple query tabs at once to easily compare results
  • duplicate and refine previous queries
  • re-run previous queries against newly available and/ or updated datasets

This makes it easier to test ideas, refine questions, and return to previous work without needing to rebuild searches from scratch. The goal is to support rapid feasibility assessment, helping researchers understand whether suitable cohorts exist before beginning full data access requests.

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A clearer path from discovery to data access

Once users identify relevant cohorts, they can move directly to the corresponding dataset metadata pages on the Gateway. The experience has been streamlined to make next steps clearer and more consistent, helping users move from discovering potential cohorts to exploring relevant datasets and beginning formal data access requests directly from the Gateway. Rather than presenting multiple possible actions, the service now guides users toward the most relevant next step in the research journey.

Infographic explaining the Cohort Discovery Service for researchers. A three-step process shows how researchers can explore relevant data across multiple datasets quickly and securely (Step 1), identify the right data custodians to contact (Step 2), and submit stronger data access requests (Step 3). Illustrations indicate example cohort sizes of approximately 350 and 40 participants from different datasets. A benefits panel highlights time savings from using a single query, early visibility of approximate cohort sizes, improved confidence through finding relevant datasets, and the ability to submit more informed requests that speed up research. The design uses blue, teal, green, and orange colours and includes icons representing data, people, health information, and geographic location.
The Cohort Discovery Service helps researchers explore potential study cohorts across multiple datasets, identify the appropriate data custodians, and submit stronger data access requests with greater confidence and efficiency.

Open source and community-driven

Another significant development is that the new Cohort Discovery Service is now open source. Organisations can use the platform in either an integrated model connected to a Gateway-style system, or a standalone deployment within their own environment.

This means collaborators can adopt, extend, and improve the service for their own research ecosystems without needing to build a cohort discovery platform from scratch, for example for their own rapid internal feasibility searches in response to user queries.

Designed to keep improving

The new Cohort Discovery Service has been built to make cohort feasibility assessment more accessible, intuitive and efficient for researchers at every stage of the process. From natural language searching and dynamic guidance to flexible query building and improved workflows, the service is designed to help users spend less time navigating technical complexity and more time exploring research possibilities.

As the platform continues to evolve through user feedback and ongoing development, future enhancements will further support clinical trial planning, dataset exploration and collaborative research across the health data ecosystem.

Ultimately, the goal is simple: making it easier for researchers to discover whether the right data exists to support the next stage of a study.

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Explore what’s possible with Cohort Discovery and book a personalised demo to learn how the service can help you build queries, explore potential patient populations and assess research feasibility with greater ease.

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