Management & Knowledge Generation Flashcards
(120 cards)
Quantitative Data
Numbers within a statistical format
Gathered after the design of data collection is outlined
Primary or secondary data
Qualitative Data
Verbal, graphic, subjective
Time-intensive to gather
Useful at beginning of design process for data collection
Primary Data
Quantitative data collected for a particular purpose
Secondary Data
Quantitative data originally collected for another purpose
Data Management
Use of computers to store, access, and secure patient information
Stored as tables in relational databases
Data Warehouses
Used to store results from clinical trials or insurance companies
Not required on a daily vasis
Used by management to make decisions
Data Warehouses
Used to store results from clinical trials or insurance companies
Not required on a daily vasis
Used by management to make decisions
Frees space and increases response time
Knowledge-Based Data
Training, support, research, practice guidelines
Comparison Data
Internal or external comparisons to benchmarks or best-practice guidelines
Analog Data
TV, radio, telephone, recorded
Continuous waveform signals varying in intensity
Binary Code
Comprised of strings of 1s and 0s
1s stored in magnetized areas (on), 0s in non-magnetized areas (off)
Data converted into bits for digital transmission
1 Byte
8 bits
256 character
1 Kilobyte
1000 bytes
1 Megabyte
1 million bytes
1 Gigabyte
1 billion bytes
1 Terabyte
1 trillion bytes
American Standard Code for Information Interchange
Most common binary coding scheme for English and European languages
Hexadecimal Coding System
2 hexadecimal characters represent 1 byte
Base of 16 and 16 symbols (1-9 and A-F for 10-15)
1 digit = 1 nibble
1 byte = 1 octet
Binary code 1000 = Hexadecimal code 8
Unicode Standard Coding Scheme
Standardized coding system that has a large capacity and can represent most languages, including Asian languages
110,000 characters
Users can assign values as needed
Data Aggregation
Collection and summation of data for further use
May be used to collect data about one topic or person from multiple sources
Data Aggregation Criteria
Apps should integrate with existing
Apps should be flexible and use industry standards
Fast and reliable performance
Scalable results
Efficient implementation with little training
Requires little increase in hardware, software, and stoarge
Cost-effective for organization
Subject-Oriented Data Warehouse
All events or objects that are the same are linked in a traceable manner
Time-Varient Data Warehouse
Ability to see information changes as a function of time
Non-Volatile Data Warehouse
Information can never be deleted or manipulated in a way that can cause loss