Chapter 2 - Information Integrity and Data Quality

Question 1

primary data source

Answer 1

data derived from the original source of information, such as the patient encounter as recorded by the healthcare professionals involved

Question 2

secondary data source

Answer 2

data derived from a primary data source; essentially, they are sources that make it possible to analyze data from primary sources, one example being a cancer registry that identifies what kinds of cancers are present in a state and how many cases there are

Question 3

data capture

Answer 3

the process of recording healthcare-related data in an electronic health record system or clinical database

Question 4

direct data entry

Answer 4

Any number of manual data entry methods such as keyboard, mouse, or other devices for entering data into the information system (IS). A number of data field types are available for use in an IS. Some of these field types can contribute to data quality by limiting the number of choices, by limiting the appropriate entries, and further specifying the data required.

Question 5

hot spot

Answer 5

also known as a pop-up text; it is a type of help message that is triggered when the cursor is placed on top of a data field

Question 6

unstructured data fields

Answer 6

data fields that use data elements that allow for free text entry, which means that the user can type in any data that he or she chooses

Question 7

structured data fields

Answer 7

data fields that guide the user during the data entry process, limiting what a user can enter into the field

Question 8

template based data entry

Answer 8

A cross between unstructured and structured data entry. The user can pick and choose data that are entered frequently, thus requiring the entry of data that change from patient to patient. It assists the healthcare provider by providing direction in what is to be documented.

Question 9

speech recognition

Answer 9

also known as voice recognition; it is technology that translates speech to text

Question 10

front-end speech recognition (FESR)

Answer 10

speech recognition where the one dictating is also the one who edits the document afterwards; more accurate but can take time away from seeing patients in the case of physicians

Question 11

back-end speech recognition (BESR)

Answer 11

the specific use of speech recognition technology in which the physician dictates in the traditional manner and an editor (someone else) listens to the audio and reviews the document created to ensure it was created correctly

Question 12

natural language processing (NLP)

Answer 12

the technology that converts human language (structured or unstructured) into data that can be translated then manipulated by information systems

Question 13

data quality

Answer 13

the reliability and effectiveness of data for its intended uses in operations, decision making, and planning

Question 14

data integrity

Answer 14

the extent to which healthcare data are complete, accurate, consistent, and timely

Question 15

edit check

Answer 15

also referred to as an edit test; something that checks data entered into a data entry system for validity (e.g. cannot give a patient an impossibly high body temperature such as 254 degrees)

Question 16

data quality management

Answer 16

the business processes that ensure the integrity of an organization’s data during collection, application (including aggregation), warehousing, and analysis

Question 17

data accessibility

Answer 17

the extent to which data items are easily obtainable by authorized users

Question 18

aggregation

Answer 18

the formation of a number of things into a cluster

Question 19

quantitative analysis

Answer 19

a review of the health record to determine its completeness and accuracy. It is used by health information management (HIM) professionals as a method to detect whether elements of the patient’s health record are missing. In quantitative analysis, the reviewer determines whether or not the reports are present or absent from the health record.

Question 20

qualitative analysis

Answer 20

a review of the health record to ensure that standards are met and to determine the adequacy of entries documenting the quality of care. While reviewing a health record, the reviewer considers whether the health record appropriately documents the care provided.

Question 21

concurrent

Answer 21

existing, happening, or done at the same time

Question 22

data comprehensiveness

Answer 22

a standard that means that the patient’s health record must be complete, meaning that all required data are included

Question 23

physician advisor (PA)

Answer 23

Someone hired by the healthcare organization to act as a liaison between the HIM department or others and the patient’s physician. The PA reviews health records for various reasons, including qualitative reviews, utilization reviews, quality reviews, surgical case and tissue reviews, other pathological reviews, and a host of blood and laboratory reviews for various medical staff and hospital committees. Typically, several physicians serve as PAs on an annual basis and are usually from diverse backgrounds, such as pathology, surgery, medicine, and other disciplines so that reviews can be a true peer review.

Question 24

data consistency

Answer 24

a standard that ensures that like data are the same on each document or computer screen. For example, in the paper health record, the patient’s date of birth is listed on many different documents. It is easy for someone to write the wrong age on a document, which would create different ages on different documents. With the EHR, the date of birth is entered once and is displayed on multiple screens.

Question 25

data currency

Answer 25

(currency as in current, not as in money) a standard that ensures that data are up to date. A data value is up to date if it is current for a specific point in time, and it is outdated if it was current at a preceding time but incorrect at a later time. Patient care must be provided based on current information. For example, a patient’s chest x-ray study from six weeks ago has little to no value when a physician is treating the patient’s pneumonia. The physician needs a current chest x-ray study to evaluate the patient’s current condition.

Question 26

data definition

Answer 26

the specific meaning of a healthcare-related data element

Question 27

data granularity

Answer 27

the level of detail at which the attributes and values of healthcare data are defined. The required level of detail depends on the circumstances of the patient’s care. For example, the documentation in the health record for a patient who is being treated for cardiac disease will describe the patient’s cardiac condition in much more detail than if the patient had a disease in another body system.

Question 28

data precision

Answer 28

how consistent data results are when measurements are repeated

Question 29

data relevancy

Answer 29

the extent to which healthcare-related data are useful for the purposes for which they were collected

Question 30

data timeliness

Answer 30

a standard that means that data should be recorded in an appropriate period of time after the event and should be available to the user when needed

Question 31

data cleansing

Answer 31

also called data scrubbing; the process of checking internal consistency and duplication as well as identifying outliers and missing data, and correcting any issues. In other words, data cleansing means looking for errors or problems with the data, such as duplicate patients, and addressing the discrepancy so that the errors can be corrected.

Question 32

outliers

Answer 32

an extreme statistical value that falls far outside the normal range. For example, if a research study has captured the number of continuing education hours that RHITs report and most reported somewhere in the range of 20 and 250 hours but one reported 1,500 hours, then the 1,500 hours would be an outlier. An outlier is not necessarily an error, but it should be evaluated for accuracy because of the impact that it has on the mean and other statistical analysis of the data.

Question 33

data mapping

Answer 33

the process of extracting data fields from one or multiple source files and matching them to their related target fields in the destination

Question 34

addendum

Answer 34

an item of additional material, typically omissions, added at the end of a book or other publication

Question 35

patient identification error

Answer 35

an error that occurs when patient A’ s health information is accidentally documented in patient B’s health record