Health Information Create a file of five records that contain name, address, and telephone numbers. Begin by defining the fields in data dictionary format, and then show how you would represent these fields if you were trying to explain them to someone else. You may elect to place a sample template record in a Word document and complete by filling in the data related to the imaginary patient.
Data Dictionary
Field: Name
Definition: The field that stores the name of the individual.
Data Type: Alphanumeric
Length: Variable
Example: John Smith
Field: Address
Definition: The field that holds the address of the individual.
Data Type: Alphanumeric
Length: Variable
Example: 123 Main Street, City, State, ZIP Code
Field: Telephone number
Definition: The field that stores the telephone number of the individual.
Data Type: Numeric
Length: Variable
Example: 123-456-7890
Sample Template Record
Name: John Smith
Address: 123 Main Street, City, State, ZIP Code
Telephone number: 123-456-7890
Introduction
In health information management, it is important to maintain accurate and up-to-date records. One common type of record is a file that contains information such as name, address, and telephone numbers of individuals. These records are commonly used for various purposes, including patient registration, billing, and communication. In this assignment, we will create a file of five records and provide a data dictionary for the fields. Additionally, we will demonstrate how to represent these fields using a sample template record.
Data Dictionary
A data dictionary is a document that provides a detailed description of the data elements or fields used in a database or file. It includes information such as the field name, definition, data type, and length. Let’s define the fields for our health information file and create a data dictionary for each field.
Field 1: Name
The “Name” field stores the name of the individual. It is an alphanumeric field, which means it can contain both letters and numbers. The length of this field is variable, as it can accommodate names of various lengths. For example, the name “John Smith” can be stored in this field.
Field 2: Address
The “Address” field holds the address of the individual. Like the “Name” field, it is an alphanumeric field with a variable length. The address can include multiple components, such as the street number, street name, city, state, and ZIP code. For example, the address “123 Main Street, City, State, ZIP Code” can be stored in this field.
Field 3: Telephone number
The “Telephone number” field stores the telephone number of the individual. It is a numeric field, which means it can only contain numbers. The length of this field is variable, as telephone numbers can have different formats. For example, the telephone number “123-456-7890” can be stored in this field.
Representing the Fields
Now that we have defined the fields and their characteristics, let’s demonstrate how to represent these fields using a sample template record. The template record will serve as a guide for filling in the data related to the imaginary patient.
Sample Template Record:
Name: John Smith
Address: 123 Main Street, City, State, ZIP Code
Telephone number: 123-456-7890
In this sample template record, we have filled in the data related to the imaginary patient. The “Name” field contains the name “John Smith,” the “Address” field contains the address “123 Main Street, City, State, ZIP Code,” and the “Telephone number” field contains the number “123-456-7890.” This representation allows for easy identification and retrieval of information when working with the records.
Conclusion
In health information management, maintaining accurate and well-organized records is crucial. Creating files that contain essential information such as name, address, and telephone numbers is a common practice. By defining the fields in a data dictionary and representing them using a sample template record, we ensure clarity and consistency in the storage and retrieval of this information. This approach promotes efficient operations and contributes to the overall quality of health information management.