REDCap data for shared research questions
Databasin helps researchers examine REDCap observations alongside the clinical records relevant to their study. Our team connects the sources and prepares the relationships, measures and applications. Researchers can explore the joined records in a shared view or ask questions in plain language, with the SQL available to inspect.
Study records in research context
Design, Build, Run
We take responsibility for the work from defining the outcome through implementation and ongoing support.
Design
We define the outcome, current processes and expected return with your stakeholders. A working example shows how Databasin would answer your business questions.
Build
We get your first use case live in 90 days. Communication, rollout, training and success measurement are included in the work.
Run
Choose the help you need after launch. We can run the solution for you, provide monthly support hours or stay on call.
Results from customer work
- 20+ systems unifiedDatabasin brought WashU Medicine's financial data together.
- Infrastructure costs at 1/3 of the traditional approachWashU Medicine's result from changing its data infrastructure.
18%
Higher grant proposal success
Measured at a research institution working with Databasin.
“What used to take weeks or sometimes even months now happens in minutes.”
Tools for ongoing research work
Scheduled preparation
Pipelines prepare records from the connected sources before the next scheduled study review.
Viewer permissions
A shared Data App runs its queries using the current researcher's data access.
Run records
Status and logs show the outcome of each run preparing the research records.
Source layers
The retained extracts let analysts examine the source of a prepared study measure.
SQL workspace
SQL gives analysts direct access to inspect permitted records and their calculations.
Private deployment
Databasin Private keeps the platform within the institution's Azure storage and network environment.
Example: Connected study analysis
Reviewing a cohort
A cohort review combines study observations and relevant encounters under the identifiers and periods defined for that research question.
Monitoring study measures
A study application presents shared measures, with filters and underlying observations available when colleagues need to investigate a finding.
Examining institutional research
An institutional research view uses defined measures from several connected sources to examine a question beyond any one study database.
What happens next
We would like to hear where your team wants to make progress with data and AI. We can discuss a project you have in mind or explore where Databasin could help with the work.
What happens next
Book a demo
Book a conversation about your organization and the work you want to improve. Questions about where to start are welcome.
Explore the opportunity
We show a working example that answers your business questions, then discuss what it would take to deliver it for your team.
Get the first result
After agreeing the first use case, we implement it with your team. We train the people using it and measure how it performs.
FAQ
Does connecting REDCap move study data collection into Databasin?
No. REDCap continues to collect and manage the study's information. Databasin reads the available records for analysis across sources. We build the research views and applications around those combined questions, leaving the study's existing data collection process in place.
What access does a REDCap project need for this connection?
The catalog specifies an API key. We configure the route with the project owners and establish what it can read. That access determines the source records available for preparation; we then set the analytical view's permissions for its intended researchers.
Will the connector automatically match participants to Epic patients?
The match is part of the model we implement with the study team. We establish the identifiers, relevant periods and relationship between records for that research question. Those choices determine which observations can be examined together. A connection supplies records; the prepared model expresses how they relate.
Can one research view include more than one study source?
Yes. Databasin can prepare a view over connected research sources. We establish which records and measures can be used together, then implement their relationships and access. The resulting application follows those definitions, so researchers can examine the combined question without treating unrelated observations as equivalent records.
Does sharing a study application expand access to its data?
No. The application runs queries with the permissions of the person viewing it. Sharing provides a place to examine measures; it does not grant broader access to the underlying records. We prepare the application audience and data permissions together for the researchers who will use the shared view.
How current will the study measures be during a review?
They reflect the records available after the relevant source refresh and preparation. We establish that schedule around the study's review and the other sources it uses. Pipeline status and run details help the team operating the application determine whether the expected preparation completed before researchers examine the measures.
Can you change a research view when the study definition changes?
Yes. We examine the revised definition and the mappings, calculations and views it affects with the study team. We implement the changes and review the resulting measure. Retained source and prepared records let the team follow the revision through the analysis.
Can analysts work directly with the prepared research tables?
Yes. SQL and notebooks support direct analysis of governed research tables. We establish the views and permissions for that work. Analysts can inspect records and calculations in detail while using the same study definitions as colleagues reviewing the shared application.
Talk about your research questions
We can discuss what your researchers want to understand and how study and clinical records contribute to that question. Our team can explain the connections, definitions and shared applications that would support the work in your environment.