Questions with Answers & Rationales (Clarity
Reporting Analyst) – Latest Update This Year Instant
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Coverage:
This 200-question practice exam is designed for Epic Clinical Reporting (CLN 251/252)
certification candidates. It covers core Clarity data model concepts, ETL processes,
reporting tools (Report Writer, SlicerDicer), joins, metrics, filters, security, and common
clinical reporting scenarios (ADT, orders, labs, procedures, events, assessments). Each
question includes a clear answer and a concise explanation to reinforce understanding.
Ideal for analysts preparing for the CLN 251/252 final exam or seeking to strengthen their
Epic Clarity reporting skills.
Q1. In the Epic Clarity data warehouse, which table type primarily stores
point-in-time snapshots of patient encounters?*
Answer: Encounter fact tables primarily store point-in-time snapshots of patient
encounters.
Explanation: Fact tables like CLARITY_ADT store encounter-level events used for
reporting.
,Q2. When designing a Clarity report, which Epic reporting tool is most commonly
used to build ad-hoc queries directly against Clarity tables?*
Answer: SlicerDicer and Report Writer are most commonly used for ad-hoc Clarity
queries.
Explanation: Report Writer allows direct SQL-like query building on Clarity tables.
Q3. In Clarity, which column is most often used as the primary key in dimension
tables?*
Answer: The PAT_ID or ENC_ID column is most often used as the primary key.
Explanation: These identifiers link patients and encounters across multiple tables.
Q4. Which ETL process in Epic is responsible for extracting operational data from
Hyperspace and loading it into Clarity?*
Answer: The Clarity ETL (Extract, Transform, Load) process is responsible.
Explanation: Clarity ETL moves data from Epic operational databases into the
reporting warehouse.
Q5. When joining two Clarity tables, which relationship type is most common
between a fact table and a dimension table?*
Answer: A one-to-many relationship is most common between fact and
dimension tables.
Explanation: One dimension record (e.g., patient) relates to many fact records
(e.g., encounters).
,Q6. In Clarity reporting, which object is used to simplify complex joins by
predefining relationships between tables?*
Answer: Reporting Workbooks and Join Paths are used to simplify complex joins.
Explanation: They define how tables relate so report writers don’t rebuild joins
each time.
Q7. Which Clarity table would you most likely query to find a patient’s date of
birth and sex?*
Answer: The PATIENT dimension table would be most likely queried.
Explanation: Demographics like DOB and sex are stored in patient dimension
tables.
Q8. In Epic Clarity, what is the primary purpose of the CLARITY_ADT table?*
Answer: The primary purpose is to store admission, discharge, and transfer
events.
Explanation: ADT data tracks patient movement and encounter status over time.
Q9. Which type of column in Clarity is most useful for filtering reports by clinical
department?*
Answer: Department dimension columns (e.g., DEPT_NAME, DEPT_ID) are most
useful.
Explanation: These columns link encounters to specific care areas for filtering.
, Q10. When building a report on medication administration, which Clarity table
is most essential?*
Answer: The CLARITY_MED_ADMIN table is most essential.
Explanation: This fact table stores medication administration events and
timestamps.
Q11. In Clarity, which ETL status indicator shows that a data load completed
successfully?*
Answer: A “Completed” or “Success” ETL status indicator shows successful load.
Explanation: ETL logs track job status; completed without errors indicates success.
Q12. Which Epic reporting object allows end users to interactively filter and
visualize Clarity data without writing SQL?*
Answer: SlicerDicer allows interactive filtering and visualization of Clarity data.
Explanation: SlicerDicer provides drag-and-drop exploration of metrics and
dimensions.
Q13. In Clarity, which type of table stores reference values like diagnosis codes
and descriptions?*
Answer: Dimension (or master file) tables store reference values like diagnosis
codes.