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Clarity Data Model & Chronicles Item
Structures Practice Exam 2026/2027: 105
Questions with Answers & Explanations for
Epic Clarity Certification
Description: Master the Clarity Data Model and Chronicles Item Structures with this comprehensive 2026/2027 practice exam featuring 105 expert-crafted questions, detailed answers, and in-depth explanations. Perfect for Epic Clarity certification candidates, healthcare IT professionals, and report writers seeking to understand add types, response types, ETL processes, and Caboodle change tracking. Download now and ace your Clarity certification exam!
Clarity Chronicles Exam Prep 2026
Section 1: Chronicles Item Characteristics and Add Types Question 1 Which add type stores data at the record level and is considered true for all contacts on that record? A. Response Each Time B. Lookback C. No-Add D. Overtime Answer: C. No-Add Explanation: No-Add items store data at the record level rather than at the contact level. This means the data is considered current and valid for all contacts associated with that record. Examples include Social Security numbers and birth dates, which remain constant regardless of when the patient was seen. Question 2 A Chronicles item stores blood pressure readings for a patient. Each encounter has its own blood pressure value, and if a value is not recorded for a specific encounter, it should be considered unknown rather than carrying forward a previous value. Which add type best describes this item? A. No-Add B. Lookback C. Response Each Time D. Single Response Answer: C. Response Each Time Explanation: Response Each Time items store data separately on each contact record. When a value is blank for a particular contact, it is considered unknown rather than inheriting a previous
Section 2: Response Types and Data Storage Question 5 A Chronicles item can store multiple values for a single record, with each value appearing on a separate line. This behavior is characteristic of which response type? A. Single Response B. Multiple Response C. No-Add D. Networked Answer: B. Multiple Response Explanation: Multiple Response items can store more than one value for a single record, with each value stored on its own line. This is in contrast to Single Response items, which can only store one value per record. Multiple Response and Related Group items are collectively referred to as multiple response types. Question 6 Which of the following response types stores data on a single line and cannot hold multiple values? A. Multiple Response B. Related Group C. Single Response D. Category List Answer: C. Single Response Explanation: Single Response items can store only one value per record. When combined with an Overtime add type, a Single Response item can store one value per contact, but never multiple values for the same record or contact. Multiple Response and Related Group items, on the other hand, can store multiple lines of data.
Question 7 You are researching a Chronicles item and discover it stores data on the record level and can hold only one value. Based on these characteristics, what would be the primary key for the Clarity table that extracts this item? A. Record_ID B. Record_ID, Line C. CSN D. Record_ID, CSN Answer: A. Record_ID Explanation: For a Single Response, No-Add item, the data is stored at the record level with only one value per record. Therefore, the Record_ID alone serves as the primary key in the Clarity table extracting this item. Additional components such as Line or Contact Serial Number (CSN) would only be needed if the item could store multiple values or if data was stored at the contact level. Question 8 What is the primary key for a Clarity table that extracts a Single Response, Overtime item? A. Record_ID B. Record_ID, Line C. Record_ID, Contact Date Real (CDR) D. CSN Answer: C. Record_ID, Contact Date Real (CDR) Explanation: For a Single Response, Overtime item, data can be stored separately for each contact on a record. Since it is a Single Response item, only one value exists per contact, so the combination of Record_ID and CDR (or alternatively CSN) uniquely identifies each row. The CDR consists of the number of days since December 31, 1840, followed by a two-digit decimal that identifies multiple contacts on the same day.
options. Alternatively, it could be a Networked item where the records or contacts in the destination master file serve as the list of options. Question 11 How can you identify whether a networked item points to a record or a contact? A. By examining the Network section within the Item Editor B. By checking the Clarity Dictionary C. By using Ctrl+Click and viewing the Item Information window D. By reviewing the Record Viewer Answer: A. By examining the Network section within the Item Editor Explanation: The Item Editor provides detailed information about Chronicles items, including how they behave. Within the Network section, you can determine whether the item points to a record or a contact. If the first field displays "Record pointer?", the link is to a record. If it displays "Contact pointer?", the link is to a contact. I ORD 226: Patient CSN is an example of a networked item that points to a contact. Question 12 You need to see all possible values for a category list item, but the Item Editor only displays the first 100 values. Which tool should you use? A. Clarity Compass B. Category List Maintenance C. Record Viewer D. Analytics Catalog Answer: B. Category List Maintenance Explanation: Category List Maintenance provides access to the complete list of defined values for a category item, unlike the Item Editor which only displays the first 100 values. This tool is essential when you need to see all available options for a category item or when you are trying to understand the full range of values that might appear in your data.
Question 13 What is a category list in Chronicles? A. A list of all items that can be extracted to Clarity B. A list of defined values that can be stored in a Chronicles item C. A list of all master files in the system D. A list of all contacts for a specific record Answer: B. A list of defined values that can be stored in a Chronicles item Explanation: A category list is a predefined set of values that can be selected and stored in a Chronicles item. When an item is defined as a category, it can only store values from its associated category list, which helps ensure data consistency and simplifies reporting by providing standardized values. Section 4: Clarity Tools and Data Research Question 14 A clinical administrator requests a query to include data for patients on the Lung Cancer Screening registry. She is unsure of the INI and Item number but knows the patient is on this specific registry. Which tool would you use to find the INI and item number? A. Clarity Compass B. Record Viewer C. Item Editor D. Category List Maintenance Answer: B. Record Viewer Explanation: The Record Viewer allows you to view actual patient records in Chronicles, including the values stored for various items. By finding a patient known to be on the Lung Cancer Screening registry and examining their record in the Record Viewer, you can identify which Chronicles item stores registry information and obtain its INI and Item number.
Question 17 A colleague shows you a table you have never seen before in their report. You search for it but cannot find it in the Clarity Dictionary. Where should you look instead? A. Record Viewer B. Clarity Compass within Hyperspace C. Item Editor D. Category List Maintenance Answer: B. Clarity Compass within Hyperspace Explanation: The Clarity Compass, accessible within Hyperspace, contains comprehensive information about all database objects that can potentially be extracted to Clarity, including custom tables and columns that may not be documented in the Clarity Dictionary on the UserWeb. This is particularly useful for finding customizations specific to your organization. Question 18 What information can be found in the Report Repository? (Choose all that apply) A. Epic-released Crystal reports B. Customer-written reports C. Category values for Epic released category lists D. Primary and foreign key relationships E. Table and column descriptions Answer: A, B Explanation: The Report Repository provides reference information for both Epic-released and customer-written reports. It is a valuable resource when looking for existing reports that might meet your reporting needs. The Clarity Dictionary on the UserWeb, not the Report Repository, contains information about category values, primary and foreign keys, and table and column descriptions.
Question 19 Which tool would you use to find the table and column that extracts EPT 18864: Attending Provider? A. Record Viewer B. Item Editor C. Column Search in Clarity Compass D. Database Object Search in Clarity Compass Answer: C. Column Search in Clarity Compass Explanation: Column Search is specifically designed to look up Clarity table and column information using Chronicles INI and Item numbers. By entering the INI and Item number for the Attending Provider item, you can quickly find the corresponding Clarity table and column where this data is stored. Section 5: Clarity Data Model and ETL Process Question 20 What is the role of the Clarity Compass in the ETL process? (Choose all that apply) A. Contains a list of all possible database objects that can be extracted B. Defines what production data will be extracted C. Schedules the extract from Chronicles into Clarity D. Defines the structure of Clarity tables including primary keys E. Displays information about previously run extracts Answer: A, B, D Explanation: The Clarity Compass defines the structure and mapping of data from Chronicles to Clarity. It contains a comprehensive list of possible database objects, defines what production data will be extracted, and specifies table structures including primary keys. The Clarity Console, not the Clarity Compass, schedules extracts and displays information about previously run processes.
Question 23 How are dates, times, and instances stored in Clarity after the ETL process? A. As strings in their original format B. As integers representing seconds since epoch C. As datetimes D. As separate date and time columns Answer: C. As datetimes Explanation: During the ETL process, dates, times, and instances are transformed into datetime format in Clarity. Dates are extracted as midnight on the date, while times are extracted as the time on January 1, 1900. This standardization ensures consistent handling of temporal data across the database. Question 24 Why might you see empty grids in Column Search when looking up a specific Chronicles item? A. The column extracts data that is not stored in a Chronicles item B. The column extracts calculated data C. The column has been deprecated D. Both A and B Answer: D. Both A and B Explanation: Column Search may display empty grids when the column extracts data that is not directly stored in a Chronicles item or when the column contains calculated data. This does not necessarily mean that the column will extract no data, but rather that the data is derived through other means or represents aggregated information. Question 25 What is the significance of load frequencies in the Clarity ETL process? A. They determine how often data is extracted from Chronicles B. They specify which data is extracted
C. They control the order in which tables are loaded D. They indicate the priority of different tables Answer: A. They determine how often data is extracted from Chronicles Explanation: Load frequencies in the Clarity ETL process specify how frequently data is extracted from Chronicles to Clarity. Different tables may have different load frequencies, with nightly incremental loads being most common, and weekly full executions typically occurring on Sunday nights to minimize performance impact. Understanding these frequencies is crucial because data in different tables may be from different points in time. Section 6: Views, Derived Tables, and Performance Considerations Question 26 Compared to views, derived tables generally take less time to run because: A. They are stored procedures that execute faster B. The data has been stored on the database C. They contain less complex logic D. They are optimized for reporting Answer: B. The data has been stored on the database Explanation: Derived tables, also called materialized views, are populated from queries that run against data already contained in the databases. These are stored procedures called during the Clarity ETL process, meaning the data is physically stored in the database. Views, on the other hand, are saved queries that execute each time they are accessed, which can impact performance for complex queries. Question 27 Why might you choose to query tables directly rather than using a view in Clarity? A. Views in Clarity are not supported for reporting B. Views are always slower than tables
C. In the Scripts tab of the Clarity Compass D. In the Report Repository Answer: C. In the Scripts tab of the Clarity Compass Explanation: The Clarity Compass provides detailed information about database objects, including views and derived tables. The Scripts tab contains the actual code defining the view or derived table. For example, V_PAT_FACT uses CASE statements to calculate patient age, and this logic can be reviewed in the Scripts tab to understand exactly what the view does. Section 7: Audit Trails and Change Tracking Question 30 A manager needs to know who has made changes to patient demographics in the last six months. Will Caboodle's snapshot change tracking likely be able to meet this report request? A. Yes, Caboodle change tracking captures all data changes B. No, Caboodle change tracking does not track who made changes C. Yes, but only for system administrators D. No, Caboodle does not support historical reporting Answer: B. No, Caboodle change tracking does not track who made changes Explanation: Caboodle's snapshot change tracking is designed to show the state of data at different points in time, but it does not track who made changes. The snapshot tables capture the values of columns over time but lack user identification information. When audit reports require knowing who made changes, other audit structures must be used. Question 31 What is the purpose of AUDIT_ITM tables in Clarity? A. To provide a complete change history for all Chronicles items B. To audit any item in Chronicles for which auditing is turned on
C. To track all user access to patient data D. To store category list definitions Answer: B. To audit any item in Chronicles for which auditing is turned on Explanation: AUDIT_ITM tables are designed to audit any Chronicles item for which auditing has been enabled. These tables store the audit trails themselves, which are maintained separately from Chronicles items on the operational server. Once audit data is purged from the operational server, it would only exist in Clarity. AUDIT_ITM tables typically include columns for Record_ID, Change_Time, Item, User_ID, and columns ending in _value (storing old and new values). Question 32 Which of the following accurately describes the ACCESS_LOG and ACCESS_WRKF tables? A. They are designed for auditing demographic changes B. They use a generic event auditing structure for tracking user activities C. They store clinical documentation history D. They track medication administration records Answer: B. They use a generic event auditing structure for tracking user activities Explanation: ACCESS_LOG and ACCESS_WRKF are part of Epic's generic event auditing structure used to track user activities in the system. They are appropriate for report requests involving understanding what specific users are doing in the system or who accessed certain patient data. The tables focus on different event types, with ACCESS_LOG containing events with an Access History log type and ACCESS_WRKF containing events with a Workflow Activity log type.
Chronicles for audit reporting if they are available, with item auditing tables used as a last resort. These tables provide detailed change history for specific data elements, including old and new values and which user made the change. Section 8: Clarity Data Model and Relationships Question 35 What is the cardinality of a relationship in the Clarity data model? A. The number of tables involved in the relationship B. The numerical relationship between rows in parent and child tables C. The direction of data flow between tables D. The type of join required to link tables Answer: B. The numerical relationship between rows in parent and child tables Explanation: Cardinality describes the numerical relationship between tables, typically expressed as one-to-one, one-to-many, or many-to-one. Understanding cardinality is essential for constructing accurate queries, as it affects how tables should be joined and what results will be returned. Question 36 What is the difference between mandatory and optional existence in relationships? A. Mandatory existence requires the foreign key to have a value, while optional existence allows null values B. Mandatory existence allows null values while optional existence does not C. Mandatory existence is for identifying relationships while optional existence is for non- identifying relationships D. There is no practical difference Answer: A. Mandatory existence requires the foreign key to have a value, while optional existence allows null values
Explanation: Mandatory existence means it is not possible for the foreign key in the child entity to have a null value, establishing a "one to X" cardinality. Optional existence allows the possibility of a null foreign key, resulting in "zero or one to X" cardinality. For example, an encounter must have a patient (mandatory), but may not have a primary care provider (optional). Question 37 What characterizes an identifying relationship in an ER diagram? A. The primary key of the parent is contained in the primary key of the child entity B. The relationship is indicated by dashed lines C. The foreign key may be null D. The relationship is many-to-many Answer: A. The primary key of the parent is contained in the primary key of the child entity Explanation: In an identifying relationship, the primary key of the parent entity is included in the primary key of the child entity. This is indicated by solid lines in ER diagrams and means that the child entity cannot exist without the parent entity. Non-identifying relationships, indicated by dashed lines, have the parent primary key as a foreign key but not as part of the child's primary key. Question 38 When writing a report that joins multiple tables, what is a key question to consider? A. What is the meaning of one row in my results? B. Which tables have the most recent data? C. How many columns are in each table? D. Which tables are extracted most frequently? Answer: A. What is the meaning of one row in my results? Explanation: Understanding the granularity of your results is essential when writing reports. When constructing queries, you need to consider how the cardinality of joins or the presence of filters may modify your report's granularity. It is generally better to write reports from the most granular level and then aggregate as needed.
