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Data, Information and Knowledge

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Data, Information and Knowledge Yaseen Hayajneh, RN, MPH, PhD – PowerPoint PPT presentation

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Title: Data, Information and Knowledge


1
Data, Information and Knowledge
  • Yaseen Hayajneh, RN, MPH, PhD

2
Quotes
  • Data is not information, Information is not
    knowledge, .. Cliff Stoll Gary Schubert
  • Business isnt complicated. The complications
    arise when people are cut off from information
    they need. John F. Welch, CEO of GE

3
Objectives
  • Understand the meaning of data, information and
    knowledge (DIK)
  • Be able to distinguish between DIK.
  • Be able to give examples of DIK
  • Understand the Value of DIK in health
    informatics.

4
DATUM
  • Value of specific parameter for a particular
    object at a given point in time.
  • Examples
  • Blood sugar level of patient DM (object) this
    morning (point in time) was 190
  • Judging this this reading as HIGH, requires more
    data knowledge.
  • Datum is singular of data. Data is plural. But
    you will see it frequently dealt with as single.

5
DATA Definitions 1
  • Facts represented in a readable language (such as
    numbers, characters, images, or other methods of
    recording).
  • Empirical data are facts originating in or based
    on observations or experiences.
  • Raw facts representing events occurring in
    organizations before they have been organized and
    arranged into a form that people can understand
    and use.

6
DATA Definitions 2
  • Factual information (as measurements or
    statistics) used as a basis for reasoning,
    discussion, or calculation
  • Data Representations of reality
  • Data are Raw Facts Figures

source Webster's Dictionary
7
DATA
  • Data on its own carries no meaning.
  • Data must be processed before becoming
    meaningful.
  • Data are not Information until they have been
    organized for analysis or display.
  • Processed Data are Information

8
Data Types
  • Qualitative (Categorical) vs. Quantitative
    (Numerical) Data
  • Discrete vs. Continuous Data

9
Qualitative (Categorical) Data
  • Raw data that are labels or categories
  • Examples
  • Class Standing (Fr, So, Ju, Sr)
  • Section (1,2,3,4,5,6)
  • Auto Make (Ford, Nissan)
  • Questionnaire response (disagree, neutral, agree)
  • Qualitative data can be only discrete

10
Quantitative (Numerical) Data
  • The raw data that are numerical
  • Examples
  • Value of Age , Height, Weight ,
  • SAT Score,
  • Number of students arriving late for class,
  • Time to complete a task.
  • Quantitative data can be discrete or continuous.

11
Discrete Data
  • Data that can be divided into categories
  • Only certain values are possible (there are gaps
    between the possible values.
  • Generally, discrete data are counts.
  • Examples
  • Number of students late for class (Three students
    and half is a not a possible value)
  • Number of crimes reported to SC police
  • Number of times the word number is used.

12
Continuous Data
  • Data with a potentially infinite number of
    possible values along a continuum.
  • Examples
  • Age ((Patient age is 3 years, 4 months, 2 days, 6
    hours, 32 minutes, 26 seconds, 14 nanosecond ...)
  • Height, Weight
  • Time to complete a homework assignment

13
Processing of Data
  • Input Raw Data
  • Processing of data can be done by a computer or
    human mind.
  • Processing Convert raw data to information

14
Data to Information
15
Information
  • A collection of facts organized in such a way
    that have additional value beyond the value of
    the facts themselves.
  • Data that has been interpreted, translated, or
    transformed to reveal the underlying meaning
  • Intelligence resulting from the assembly,
    analysis or summary of data into a meaningful
    form.
  • Information is data in context.
  • It can be understood it has a meaning.

16
Information
  • Information Data that has been processed into a
    form that is useful.
  • Info. Data which provides relevant clues or
    news
  • A collection of facts from which conclusions may
    be drawn "statistical data"

17
Information
18
Characteristics of Valuable Information
  • Accurate Accurate information is error free. In
    some case, inaccurate information is generated
    because inaccurate data is fed into
    transformation process.
  • Complete Complete information contains all of
    the important facts. Example, a patient report
    that does not include all important diagnostic
    results is not complete.

19
Characteristics of Valuable Information
  • Economical Information should also be relatively
    economical to produce. Decision makers must
    always balance the value of information with the
    cost of producing it.
  • Relevant Relevant information is important to
    the decision maker. Information that infusion
    pump prices might drop is not relevant to the
    medical records archiving clerk.

20
Characteristics of Valuable Information
  • Flexible Flexible information can be used for a
    variety of purposes . For example, information on
    the number of planned open heart surgeries can be
    used by purchasing officer to plan buying
    supplies, by a nurse manager to determine
    staffing levels, by marketing manager to use in
    marketing efforts and by the CEO to brag about.

21
Characteristics of Valuable Information
  • Reliable Information that can be depended on.
    Reliability of information depends on the
    reliability of data collection methods and
    source of the information.
  • Simple Sophisticated and detailed information
    may not be needed. Information overload happens
    when a decision maker has too much information
    and is unable to determine what is really
    important.

22
Characteristics of Valuable Information
  • Accessible Information should be easily
    accessible by authorized users to be obtained in
    right format and at the right time to meet their
    needs.
  • Timely Timely information is delivered when it
    is needed. Knowing patients morning blood sugar
    result the next day will not help when trying to
    determine insulin dosage today.

23
Characteristics of Valuable Information
  • Verifiable You can check it to make sure it is
    correct, perhaps by checking many sources for the
    same information.
  • Secure Information should be secure from access
    by unauthorized users.

24
Knowledge
  • Knowledge is information which has been
    intellectually processed, by man or by machine.
  • It has an immediate value without any further
    processing.
  • Knowledge is used to interpret information
  • Medical diagnosis based on patient diagnostic
    information requires knowledge.
  • Modern health care needs structured knowledge for
    reference and decision support.
  • Knowledge enables HCOs to anticipate events

25
Knowledge
  • is a mix of experiences, concepts, beliefs,
    values, contextual information, and expert
    insight that provides a framework for evaluating
    and incorporating new experiences and information
    and that can be shared communicated.
  • It originates and is applied in the mind of
    knower. In organizations, it often becomes
    imbedded not only in the documents or
    repositories but also in organizational routines,
    processes, practices, and norms.

26
Where is Knowledge?
  • You can find knowledge in
  • Documents
  • Processes
  • Policies Procedures
  • Rules
  • Guidelines
  • IT Applications
  • Management systems
  • Individuals Minds behaviors

27
Data Management
  • The planning, development, implementation, and
    administration of systems for the acquisition,
    storage, and retrieval of data.
  • It involves strategic data planning, data element
    standardization, information management control,
    data synchronization, data sharing, and database
    development. Active data management increases
    system effectiveness and improves the accuracy
    and timeliness of data to derive maximum benefit.

28
Information Management
  • The administration, use, and transmission of
    information and the application of theories and
    techniques of information science to create,
    modify, or improve information handling systems.
    Filing systems, cognitive maps, manuals, and
    electronic databases are examples of devices that
    can prove useful in information management. A
    network of consultants is an additional way to
    ensure that necessary information will be readily
    available.

29
Knowledge Management
  • A discipline used to systematically leverage
    expertise and information to improve
    organizational efficiency, responsiveness,
    competency, and innovation.
  • It involves gathering, organizing, sharing, and
    analyzing knowledge in terms of resources,
    documents, experts, lessons learned documents,
    best practices, and people skills.

30
Database
  • An organized collection of logically related
    data patient names, gender, insurance converge,
    etc.
  • It usually refers to data organized and stored on
    a computer that can be searched and retrieved by
    a computer program.
  • Turns raw data into structured data
  • Webster Definition a usually large collection of
    data organized especially for rapid search and
    retrieval (as by a computer) .

31
Database Management
  • Tools and techniques to manage sets of
    alphanumeric data. Typically this involves the
    design of database systems and the programming to
    perform the desired functions.
  • Future systems will clearly also be required to
    handle images, audio, and video data.

32
Information base
  • Database containing information (e.g. reports,
    documents, interpreted data) see also
    information repository.
  • Information Base Example

33
Knowledge base
  • A knowledge base embodies knowledge about how to
    solve a problem in some problem domain.
  • Expert system (ES) A computer system that
    facilitates solving problems in a given field or
    application by drawing inference from a knowledge
    base developed from human expertise.

34
Value of Data Information
  • Record events
  • To improve quality of care
  • Fast access to urgently needed information.
  • To improve operations
  • To save money
  • Just In Time ordering
  • Aid management decisions

35
How Valuable are Data?
  • To help you know the value of data, Imagine that
    you are the CEO of a hospital that just lost
    permanently the following Data
  • Patient lists
  • Payroll information
  • Accounting details
  • Transaction details
  • Records of who owes you money
  • it would be catastrophic
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