Digital Data Base

• Big data across the federal government
• Health-related agencies with big data projects


  • Department of Veterans Administration
  • Department of Health and Human Services
  • National Institutes of Health
• Other government agencies with big data projects

  • Department of Defense
  • Department of Homeland Security
  • The Office of Basic Energy Sciences
• The Federal Government is using data and especially the big data revolution to advance scientific discovery and innovation in a number of areas including the delivery of quality healthcare and personalized healthcare
• Modern healthcare


  The process of moving from data collection to implementing and evaluating the care provided to individuals, families, and communities is highly dependent on automated database systems
• Goal of healthcare and the movement to big data and data analytics

  To drive quality care at lower costs through reducing overutilization of services, improve coding and billing practices, empowering patients, measuring trends, predicting outcomes, and examining how improved work-flow and productivity can influence quality outcomes
• Data


  Raw, uninterrupted facts without meaning
• Information


  Data that has meaning, e.g. recorded and labelled vital signs
• Approaches to organizing and naming data

  • Classifying
  • Summarizing
  • Calculating
• Data states


  • Data at rest
  • Data in motion
  • Data in use
• Data at rest


  Data on storage devices that rarely changes, such as patient's past medical records
• Data in use


  Data that a database program is currently reading or writing, residing in the computer's temporary memory
• Data in motion


  Data moving between applications, over the network, or over the Internet
• Database


  An organized collection of related data
• Database formats


  • Paper database
  • Electronic database
• Factors affecting information retrieval from databases

  • Data naming (indexing) and organizational schemes
  • Size and complexity of the database
  • Type of data within the database
  • Database search methodology
• Information system


  Refers to computer systems, manual information systems, and human information systems (the human brain)
• Approaches to classifying data in a database system

  • Conceptual view (how users will use the data)
  • Computerized data type
• Conceptual data types


  Reflect how users view the data, based on the source or the event the data is attempting to capture
• Computer-based data types


  • Alphanumeric
  • Numeric
  • Logic
• Alphanumeric data


  Include letters and numbers in any combination, cannot perform numeric calculations on the numbers
• Numeric data


  Can be used to perform numeric functions including addition, subtraction, multiplication, and division
• Logic data


  Data limited to two options, e.g. yes/no, true/false
• Database management systems (DBMSs)


  Computer programs used to input, store, modify, process, and access data in a database
• Three interacting parts of a DBMS

  • The data
  • The designed database
  • The query language
• Advantages of automated database management systems

  • Decrease data redundancy
  • Increase data consistency
  • Improve access to all data
• Data redundancy


  Occurs when the same data is stored in the database more than once or in more than one interrelated database
• Database structure


  Fields, records, and files
• The Office of the National Coordinator for Health Information Technology (ONC) initiated a collaborative patient matching initiative and three months later some preliminary findings to include standardized patient identifying attributes
• Functions of a DBMS

  • Store the data
  • Update the records
  • Provide easy retrieval of the data
  • Permit report generation
• Database models


  • Hierarchical
  • Network
  • Relational
  • Object-oriented
• New database models for large-scale data

  • Massively Parallel Processing (MPP)
  • Column-oriented database
  • Stream processing (ESP or CEP)
  • Key-value storage (MapReduce)
• Hierarchical databases


  Structured like an inverted tree, with access starting at the top of the hierarchy or root
• Network model


  Allows a child node to have multiple parents, enabling representation of many-to-many relationships
• Relational database model


  Consists of a series of files set up as tables, with columns representing attributes and rows representing records
• Object-oriented database


  Has evolved to overcome limitations of the relational model
• Network Model


  • Child node is not limited to one parent
  • Able to represent many-to-many relationships
  • Presence of multiple links between data makes it more difficult if data relationships change and redesign is necessary
• Relational Database Models (RDM)


  • Series of files set up as tables
  • Each column represents an attribute
  • Each row is a record (also called a tuple)
  • Intersection of row and column is a cell
  • Datum in cell is the manifestation of the attribute for that record
  • Each cell may contain only one piece of datum
  • Datum must be atomic or broken down into its smallest format
• Relational database


  Joins any two or more files and generates a new file from the records that meet the matching search criteria
• Object-Oriented Model


  • Evolved because the relational model has limited ability to deal with binary large objects (BLOBs)
  • BLOBs are complex data types such as images, sounds, spreadsheets, or text messages
  • BLOBs are large nonatomic data with parts and subparts that a relational database cannot easily represent
  • Entity as well as attributes of the entity is stored with the object
  • An object can store other objects