Data Explorer allows users to build reports without writing code. You can pull in various pieces of data and combine them in powerful ways. Here’s an example of what you can create:
An unduplicated list of patients whose
- primary caregiver is Dr. A or Dr. B;
- who have a diabetes diagnosis;
- and who have had a medical visit within the past year
You can then add all sorts of data to this list, including the following examples:
- each patient's latest A1C lab result;
- each patient's most recent nutrition screening date; and
- details of each patient's next upcoming medical appointment.
How it works
Step 1: Configure a base element
Every data explorer has a base element, which describes the type of list we want. The most common base element is Patients, which produces an unduplicated list of patients.
But let's say you want a list of all Tobacco Use Screens performed in the past year. If a patient was screened three times, you want to see three rows in the report. In this case, the base element should be Tobacco Use Screens.
Once you choose a base element, you can use the configuration sidebar to add filters, choose what columns to display, and more. Here's a brief video showing these features, following our example from above:
Step 2: Add additional elements
The real power of Data Explorer comes when you add additional data elements. Following our example, let's say we want to add data about A1C lab results, nutrition screenings, and upcoming medical appointments to our list of diabetic patients. Here's a brief video showing how this works:
Additional data elements can be configured just like the base element, by adding filters and choosing which columns to display. They also have two additional pieces of configuration: "Join Behavior" and "Reducer" options.
Join Behavior. Let's say we have a list of 10,000 diabetic patients. Now we want to pull in their latest A1C lab results... but only 8,000 of these patients actually have any A1C results. What should we do for the 2,000 patients who don't have any A1C results? We could keep them in the report, just not show any data in the A1C columns. Or we could trim down the list of patients, so the report only includes the 8,000 patients who do have an A1C result.
You can choose between these two options in the "Join Behavior" section of the configuration sidebar, as pictured below. (For SQL users, this question is equivalent to the choice between "left join" and "inner join.")
Reducers. Additional data elements are designed to return at most one result per patient. To ensure this is the case, you'll need to specify whether you want, for example, a patient's most recent A1C result or their earliest A1C result. This decision is made in the "Reducer" section of the configuration sidebar. Here's an example:
Tips and tricks
- Show care gap, risk score, and quality measure information. Among the columns available to display in Data Explorer are information regarding Care Gaps, Risk Scores, and Quality Measure warnings.
- Use populations for filtering. The Relevant project team at your health center can create useful "populations" that define groups of patients. These populations can then be used as filter options in Data Explorer.
What data is available?
Not all data from the EHR is available in Data Explorer. The screen is based on Data Elements, which are the building blocks used in various screens across Relevant. Each of these data elements is mapped from the EHR and then validated by your health center’s Relevant project team. There are currently around 200 data elements that have been defined by Relevant. We're adding more of them over time.
By default, only data elements that contain data show up in the dropdown list for Data Explorer. If you're searching for a data element in the sidebar and can't find it, try unchecking the "Hide empty data elements" option, as pictured below. The dropdown menu will then expand to show all of the data elements that have been defined by Relevant, including those that are currently empty.
If you find an empty data element for a report you need, contact your health center's Relevant project team. They may be able to help map this element, which will allow it to then be used in Data Explorer.
Frequently asked questions
Q: How come I can't find the data I'm looking for?
A: Not every data point in the EHR is available in Data Explorer. It's based on the Data Elements that have been mapped. See the help section "What data is available?" on this page for more details.
Q: I see generic data elements like “Labs Results,” and also more specific ones like “A1C Labs.” Which should I use?
A: Start by looking for a specific data element that meets your needs. These specific data elements, like "A1C Labs", have been specifically mapped and validated by your health center's Relevant project team. In some cases they may pull data from multiple areas of the EHR to provide the most accurate data. If a specific Data Element is not available for a particular concept, then we recommend trying the more generic data elements, like Lab Results, Medications, and Patient Diagnoses.
Q: I need Visit Diagnoses Codes and Visit Billing/Procedure Codes. Where are they?
A: These items are not currently available in Data Explorer. We know they are important and hope to make them available in the future.
Q: How does Data Explorer relate to Population Explorer?
A: Data Explorer can do everything Population Explorer can do, and more. Over the long term, we plan to spend more time and energy improving Data Explorer, and ultimately we may decide to retire Population Explorer. (Of course we'd give you plenty of notice, and consult closely with health center teams, before doing so.)
Q: For additional data elements, are filters applied before or after the reducer?
A: Currently, filters are always applied before the reducer chooses a value. Consider a patient with A1C results of 8.2 on 2/1/22, 9.2 on 3/1/22, and 8.5 on 4/1/22. In the example filter and reducer setup pictured below, the 9.2 value from 3/1/22 will be returned, because it's the latest of the lab results which satisfy the filter criteria of ≥ 9. In the future, we may add an option that allows you to specify whether the reducer runs before or after filters are applied.
Q: Can I see the SQL query that's generating the Data Explorer?
A: Behind the scenes, most data explorers don't rely on a single SQL query: instead, queries are run for each data element that is part of the report, and the results are then stitched together before displaying on the screen. You can see these individual queries by clicking 'Edit' on a data element, then clicking 'Show SQL'.
Intro to Data Explorer Webinar