Epic reporting
Your clinical, finance and research teams can explore Epic data, ask follow-up questions and share the findings in applications they can use again. Databasin prepares the source records and measures, then builds the solution around your department's work. Our team handles implementation, rollout and training, with support after launch.
Epic records prepared for investigation
We prepare Epic records around the measures and questions your department uses. Our team connects Clarity and available Caboodle data, applies local mappings and builds the definitions used in analysis. People can then explore those records through reports and plain-language questions.
Databasin was built in production at WashU Medicine. That experience informs the source work, while each implementation reflects the institution's own Epic configuration. A measure such as length of stay needs the local rules behind it, so the application represents the work being examined.
Ways to use Epic data
Investigate a question
Ask about the prepared Epic records and inspect the SQL behind the answer with an analyst.
Explore shared measures
Review the departments and periods in a Data App using the measures prepared for that work.
Repeat the preparation
Schedule the source refresh and calculations so the department can use the prepared view in its next review.
How can a department investigate further?
A Data App lets the department examine a measure and ask questions alongside the view. A filter change reruns its queries and updates the result. Databasin One returns an explanation with the sources and SQL. The reviewer can examine how the figure was calculated before deciding what it means for the work.
Reusable preparation for recurring reviews
A department can return to the views we prepare for its recurring review. Those views hold the mappings and calculations used in reports and questions. Scheduled preparation refreshes the source records for the next use of the application.
Training explains the measures, their reporting period and the evidence available for inspection. Databasin can then operate the solution, provide monthly support hours or stay on call after rollout. The department has help as it continues the review and identifies new questions.
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
How do you choose between Clarity and Caboodle?
We begin with the required records and local source coverage. Clarity provides a detailed relational model. Caboodle contains curated subject-area data, but its coverage varies with the institution's implementation. Those differences help determine the source for the application.
Will an Epic reporting view show events as they happen?
Clarity-based views reflect its last completed refresh, generally from the previous night. We show the relevant period in the application so people can interpret the available records. Extracting them more often does not make Clarity a live feed.
Does this analysis query the operational Chronicles database?
No. Databasin uses Clarity and available Caboodle reporting sources for this analytical path. They supply records separately from the operational Chronicles database, which supports the institution's clinical processes.
Where do FHIR resources fit in an Epic reporting project?
FHIR supplies the standard resources it exposes. We can use those to supplement reporting data. Questions requiring local Epic fields or broad cohort and revenue-cycle records may need Clarity, so we examine coverage before choosing the source.
Can an existing institutional metric be used in the application?
Yes. The preparation can include the metric's reporting period, encounters and exclusions. We establish the intended definition and implement those rules in its calculation. An analyst can inspect the resulting measure when reviewing a report.
How can an Epic upgrade affect the prepared records?
Source columns and tables can change during an upgrade. Databasin keeps schema versions with raw extracts and detects changes during ingestion. The team can use that history to identify affected mappings and adapt them for subsequent reports.
Can the analysis combine Epic with finance or research sources?
Yes. Workday, REDCap and other connected sources can contribute to the same analysis. We define the relationships and calculations the question needs, including period-appropriate history when it concerns earlier records.
Will analysts be able to query the prepared tables directly?
Yes. The prepared tables can be queried through SQL, notebooks and supported BI tools. Analysts can inspect records and calculations there while colleagues use the application to explore measures or ask questions.
What role does our institution have in approving source access?
Your institution decides which source permissions to grant. We help specify the required records, connection route and deployment with its IT and security owners. The implementation follows that approved access design.
Can the reporting application run within our Azure tenant?
Yes. Databasin Private runs in your Azure environment using your storage, keys and network. We design the source access and application within the selected deployment, including the model endpoint where AI is used.
Talk about your Epic reporting
We can talk through the reports and investigations your teams rely on, including where access, definitions or repeated preparation slow the work. Together, we can explore how Databasin would help people use the data more directly.