DIKW: Data, Information, Knowledge, Wisdom

DIKW

• DIKW stands for Data, Information, Knowledge, and Wisdom.

Topic Outline

• What is Data
• Data Types
• Data Hierarchy
• Databases
• Data Warehouse
• States of Data
• Data Processing
• Types of Processing
• Data Processing Cycle
• Data to Information
• Information
• Knowledge
• Wisdom
• DIKW
• The Nelson Data to Wisdom Continuum

Objective

• Define and differentiate Data, Information, Knowledge and Wisdom
• Categorize data types and data hierarchy
• Discuss databases and data warehouses, and their importance in healthcare
• Elaborate data processes, the types of processes, and the data processing cycle
• Describe the relationship between data to wisdom continuum and database systems

What is Data?

• Data represents a collection of facts in a raw or unorganized form.
• Examples include images, audio, video clips, numbers, letters, or characters.
• Data is raw materials to be processed by a computer.
• Observations and recordings are done to obtain data

Data Types

• Computer-Based Data Types include Numeric Data, Character Data, and Graphical Data.
• Numeric Data represents data in the form of numbers, including digits 0-9, a decimal point (.), +, /, and – sign.
• Character Data includes String Data with a sequence of characters, such as English alphabets, numbers, or spaces like alphabetic data and alphanumeric data.
• Graphical Data represents data like pictures, charts, and maps.

Data Hierarchy

• Data is organized in layers, classified in a hierarchy in computing.
• Each higher level of data consists of one or more items from the lower level.

Data Hierarchy Levels

• Bits are either 0 or 1 and represent the smallest unit of data.
• Bytes consist of eight bits; one byte makes one character.
• Fields represent a combination of bytes.
• Records combine fields related to one person.
• Files are the combination of records, usually related to different subjects.
• A database is a collection of files and the largest collection of data.

Databases

• A database is an organized collection of related data or any record that a practitioner maintains in paper form or on a computer.
• Anything that a medical practitioner collects from a patient forms part of the database, including encounter forms, discharge forms, or any other registries.

Importance of Databases in Healthcare

• Healthcare databases are an important part of running the entire operations that includes labs, finances, patient identification, tracking, billing, payments, among others.
• Efficiency is achieved through well-designed hospital databases by providing relevant information with a click-of-a-button.
• Hospitals exchange healthcare data anytime there is a requirement.
• Database function integration through things like patient identification is important.
• Database systems provide an important way of monitoring and improving the value of healthcare services, resulting in better well-being for patients.
• Quality experts use hospitals' databases to assess healthcare quality.
• Healthcare databases can provide medical providers with an important tool for tracking healthcare use.
• Other uses include assistance with documentation and billing and reduction in medical facility running costs due to less paperwork and clerical staff.

Data Warehouse

• Data Warehouse is a large collection of data imported from several different systems into one database.
• The source of the data includes not only internal data from the institution, but also data from external sources.

Data Warehouse Example

• Patient digital profile that rounds out a full picture of patient health with: patient reported outcomes, 7x24 biometric data, claims data, healthcare encounter data, consumer data, socio economic data, genomics data, epigenetic data, microbiome data, etc., beyond the traditional encounter and beyond the EHR.

States of Data

• There are three states of digital data: data at rest, data in transit, and data in use.
• Data at rest is data that is not being accessed and is stored on a physical or logical medium, such as files stored on file servers, records in databases, documents on flash drives, or hard disks.
• Data in transit is data that travels through an email, web, collaborative work applications, instant messaging, or any type of private or public communication channel.
• Data in use happens when data is opened by one or more applications for its treatment or and consumed or accessed by users.

Data Processing

• Data processing is any operation or set of operations performed upon data, whether or not by automatic means, such as collection, recording, organization, storage, adaptation, or alteration to convert it into useful information.
• Collected data is processed to convert it into useful information repeatedly until the accurate result is achieved, defined as the data processing cycle.

Types of Processing

• Manual Data Processing involves human intervention.
• Electronic Data Processing (EDP) involves processing of data by a computer.
• Real-Time Processing is a continual input, process, and output of data, requiring the data to be processed in a small stipulated time period.
• Batch Processing is an efficient way of processing high volumes of data.

Data Processing Cycle

• The data processing cycle involves four basic activities: Input, Processing, Output, and Storage.
• Input: Collect data is transformed into a form that a computer can understand including the steps verification, coding, and storing.
• Processing is the actual data manipulation with techniques such as classification, sorting, calculation, and summarizing.
• Output represents anything that comes out of a computer after processing, including retrieval, conversion, and communication.
• Storage involves storing the inputted data and processed information for future use, including storage and retrieval activities.

Data to Information

• Processing data transforms it into information, consisting of processed facts with shapes and patterns.

Information

• A collection of data conveys some meaningful idea.
• Data gains significance when collated or organized, thus becoming information.
• Information relates to description, definition, or perspective and answers the questions "what", "who”, “when”, and "where".
• Hospital Information Systems are computer-based software applications integrating many medical, nursing, administrative, and miscellaneous functions of hospitals, by combining computer technology and communications to acquire and integrate financial and clinical data.
• Nursing Information Systems are computer systems that manage clinical data from a variety of healthcare environments and made available in a timely and orderly fashion to aid nurses in improving patient care.

Knowledge

• Knowledge is the appropriate collection of information, obtained when a student memorizes information.
• Knowledge is an organization and processing to convey understanding, experience, and accumulated learning.
• Knowledge comprises strategy, practice, method, or approach and answers the question "how?".
• Clinical Decision Support Systems (CDSS) are computer software tools designed to facilitate decision-making through connecting evidence with patient status.
• CDSS supports decision-making in time-limited circumstances leading to improved patient outcomes.
• Expert systems represent the present and future vanguard of nursing informatics.
• Expert systems use artificial intelligence to model a decision that experts in the field would make.
• Expert systems convey the concept that the computer has made the best decision based on criteria that experts would use.

Wisdom

• Wisdom involves the possession of knowledge such that one can observe patterns of information within data, make intelligent connections between different patterns, and feel the principles which underlie the patterns themselves.
• Computers lack human quality of wisdom.
• Wisdom answers the question "why?".
• NK is nursing knowledge.
• W stands for wisdom.
• IB is the individual nurse's integration and synthesis of nursing knowledge through the cognitive, psychomotor, and affective/spiritual domain of self.
• P represents the breadth and depth of practice.

DIKW

• DIKW progresses from Raw Data to Derived Information, then to Relevant Knowledge, and culminates in Guiding Wisdom.

The Nelson Data to Wisdom Continuum

• The Nelson data to wisdom continuum by Dr. Romana Nelson, depicts movement of data to information to knowledge to wisdom with constant interaction within and across these concepts as well as the environment.