Lecture 3 - Healthcare data, Information, and knowledge Flashcards
Data
Symbols or observation or observation ps reflecting differences in the world
Information
Data with meaning
ICD- 9 code means type 2 diabetes
Knowledge
Info justifiably true
Obese more likely to develop type 2 diabetes
Wisdom
Why, alternative reasoning
International classification of diseases ICD
International standard diagnostic tool for epidemiology, using standardised codes. Therefore, the code of the medical case in Kuwait will be the same as the US of the world
Data
Computers do not understand Only input store process and output Zero is off One is on these are binary units 0/1 a bit 8 bits are a byte
Data type
Integers
Floating (decimal)
Characters y/n
Character strings
File formats
Data can be aggregates to formats
Common standard is of important need to charge data and info
Standard format is important for communication between computer systems
Computer programmes do not understand data on the DISC or any storage device,
Important it accepts file format
Types of files
Image jpg gif png
Text txt doc
Sound wav mps
Video mpg
IT vs health informatics vs computer
It: more concerned about data, no matter what they mean, algorithm and number
Health informatics: concerned with the meaning of data, information, knowledge, and tools that retrieve and manipulate info such as in PAVS.
Manipulate info
Information retrieval: find relationship between aspirin and heart attacks
Challenge is identifying documents that contain certain meaning
Comp sci: database searching and data info retrieval
Informatics: vocabulary ontologies, information, info retrieval
Data to information
No computer, only human interpretation is necessary
Vocabularies help convert data to info
Make data meaningful
Interoperability
Transmition of information that require consistence of interpretation for the purpose that all information systems are using the same standard and can accept and show the same interpretation
Information to knowledge
Information makes knowledge
Experience is knowledge
Carrying out research to investigate correlation
Knowledge can only be formed thru information, not data directly
Make sense of clinical data
Clinical data are collected via EHR
These records are composed of
Structured data:
exact numbers, data e.g aspirin 400 mg
Easy to manage and retrieve
Unstructured data: Free text Clinical notes Natural language- difficult to process Natural language processing
Van der lei 20 years ago
Data shall only be used for the purpose collected
If no purpose was defined prior to the collection of data, data won’t be used
You have to know what data you want to collect, why and how to collect them
Healthcare DIK: object oriented models
Object
Unique real world phenomena we want to model
Healthcare DIK: object oriented models
Field/ State/ Attribute
A piece of data that describes the object
Healthcare DIK: object oriented models
Method/ behaviour
What the object does or what we do to it to change states
Class
A common form/ template to describe unique objects
Inheritance
Baby of classes
Parent may be age
Child may be paedriatrics/geriatric
Clinical data warehouse
Shared database that Collects Integrates Stores Clinical data from a variety of sources including EHR radiology
Main source of all EHR
MASTER DATABASE
Supports queries for groups
Staging
Extract, transform, and load into a common database
EHR
Designed for real-time updating and retrieval of individual data
Facts
Pieces of information queried by users
Diagnosis
Demographic
Lab tests
Dimension
Describe facts
Us tiki see using summary statistics
Count, mean, median
CDW as a clinical resource
Monitor Identify Help Conduct Build
Can recognise records for patients with illness
Info to knowledge
Tools eg simple descriptive analysis
Monitor
Quality of a query measuring specific population
Identify
Trends of clinical and transitional research to link r3search with clinical practice
Help
Specialist to track pathogens
Faster reporting in electronic CDW
Conduct
Surveillance for natural or man made illness to public health agencies
Build
Platform of informatics
One made by Harvard medical school
Warehouse of clinical data from multiple resources, so queries can be made from one platform to retrieve data from multiple institutions eg integrating biology and the bedside i2b2
Why is informatics difficult?
Banking is easy as gap in data and information is narrow
Healthcare concepts are poorly defined as systems are connected
Data is poorly managed
Semantic gap
The difference between data and information as Med is only using data
Obstacles of informatics in healthcare
Incomplete info- missing data but may be obtainable
Uncertain info- not sure true or false
Imprecise info- info not as specific
Vague info- unclear info
Inconsistent info- can’t hold both beliefs at the same time
We need to design in an accurate and purposeful way
Future trends
Data processing to info processing
Introduce cognition and abilities (mental processing)
Creating systems that store specific information specific eg only cancer patients from population
Expert system
