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“Victor Babes” UNIVERSITY OF MEDICINE AND PHARMACY TIMISOARA

“Victor Babes” UNIVERSITY OF MEDICINE AND PHARMACY TIMISOARA. DEPARTMENT OF MEDICAL INFORMATICS AND BIOPHYSICS Medical Informatics Division www.medinfo.umft.ro/dim 2004 / 2005. MEDICAL DATABASES. COURSE 2. Opera tions with informa tions. Generation

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“Victor Babes” UNIVERSITY OF MEDICINE AND PHARMACY TIMISOARA

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  1. “Victor Babes” UNIVERSITY OF MEDICINE AND PHARMACY TIMISOARA DEPARTMENT OF MEDICAL INFORMATICS AND BIOPHYSICS Medical Informatics Division www.medinfo.umft.ro/dim 2004 / 2005

  2. MEDICAL DATABASES COURSE 2

  3. Operations with informations • Generation • Acquisition – dep. on information nature • Storage – data bases, knowledge bases • Processing – for interpretation • Commitment • Protection • Use

  4. 1. PACIENT RECORD

  5. 1.1. Terminology:EHR - ELECTRONIC HEALTH RECORDEPR - ELECTRONIC PATIENT RECORDCPR –COMPUTERIZEDPATIENT RECORD

  6. 1.2. PACIENT RECORD • a. ON PAPER • AVANTAGES / DISADVANTAGES • EASY TO CARRY, EASY TO “BROWSE” • LOW COST, FREE FORMAT • FAST DATA ENTRY • ACCESSFROMONE PLACE ONLY • b. ELECTRONIC • AVANTAGES / DISADVANTAGES • ACCESSFROMDIFFERENT PLACES, MORE PERSONS • EASY TO READ, EASY TO SEARCH INFORMATION • GOOD BASEFOR DATA ANALISYS, FOR TAKE DECISSION • NEED FOR TRAINED PERSONNEL • REQUIRE MORE TIME FOR DATA ENTRY • HIGHER COST

  7. 1.3. EHRSTRUCTURE • IDENTIFICATION DATA (apart file!!!) • EVENTS: consultation, hospitalisation, surgical intervention, X-ray, etc • time scale • ACTIONS • OBSERVATIONS: case history, lab.results, investigations – signals, images • DECISIONS: diagnosis • INTERVENTIONS, THERAPY : prescriptions • RELATIONS

  8. 2. DATA FILES

  9. 2.1. DATA FILES • DEFINITIONS: • DATA = formalized representations of concepts or facts, appropriate for processing (both human or automatic processing) • FILE = an organized set of data

  10. 2.2 TYPES OF DATA • QUALITATIVE – Case history (descriptive) • NUMERICAL – Laboratory Investigations • GRAPHICS – Biosignals (EKG, EEG…) • SOUNDS: Phonocardiogram • STATIC IMAGES : x-ray, NMR • DYNAMIC IMAGES – movies (“MULTIMEDIA” FILES)

  11. DATA FILE STRUCTURE - scheme

  12. 2.3. DATA FILE STRUCTURE • a) RECORDS (+ Header + EOF) • b) FIELDS • NAME • TYPE: • NUMERICAL • CHARACTER • LOGICAL ( Y / N ) • DATE • COMMENT • SIZE

  13. 2.4. PATIENT RECORD

  14. 3. DATA BASES • 3.1. GENERAL NOTIONS • DEFINITION: DATABASE = a structured set of data - comprises both data and relations between data • STRUCTURE: • FILES (with at least 1 common field - ID) • RELATIONS between records and/or data • PROPERTIES: independence on physical support or language

  15. 3.2. Creating DataBases • Data collecting • Record Structure • Coding • Staff training for filling in • Data validation • Field type • All possible relations

  16. 3.3. Coding and classification • Thesaurus - terms list • Nomenclature - associatedcode list • Types of codes: • numerical, mnemonical, hierarchical, juxtapositional • Taxonomy – classifications rules • Taxonomic axes • Nosology - classification in medicine

  17. 3.4. Classification Systems • ICD - International Classification of Diseases (10) • ICPC - International Classification for Primary Care • SNOMED – System of NOmenclature in MEDicine - multiaxial • Specialized: Mental, Oncology, Procedures • MeSH / UMLS - Medical Subject Headings Unified Medical Language System • DRG - Diagnostic Related Groups – for finance Case-Mix

  18. 3.5. DB CLASSIFICATION • On data distribution: • Local DB (all on 1 computer) • Distributed DB (on several computers) • On structure: • RELATIONAL DB • HIERARCHICAL DB • NETWORK DB

  19. a) RELATIONAL DB • Logical structure (rows & columns) • Several searching criteria • Easy changes • b) HIERARCHICAL DB • Tree structure: each element is subordinated to only one element • Fast search and processing • No flexibility for procedure changes

  20. 4. DBMSDataBase Management System • a) DEFINITION: • DBMS = a set of software tools for: • building a DB • control access to data • assure data security and integrity • Represented by: • specialized languages • dictionaries, nomenclature

  21. b) DBMS Functions • DESCRIPTION: • data structure • relations • access conditions • DATA MANIPULATION: • create, delete, update a record • search, sort, edit virtual records • USE FUNCTION: • USER - DB dialogue

  22. c) RELATIONAL MODEL FOR DATA REPRESENTATION - DBMS Languages • Languages based on relational algebra • Languages using relational operators • ( >, $, ", L etc) • Transform oriented languages (SQL) • Graphical relational languages (QBE, Paradox) • Examples: dBase, Foxpro, Access, Oracle

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