Introduction to the programme A.Hasman. Medical Informatics The study concerned with the understanding, communication and management of information in.

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Presentation transcript:

Introduction to the programme A.Hasman

Medical Informatics The study concerned with the understanding, communication and management of information in healthcare

Understanding Which concepts/terms are used What do they mean How can the concepts be represented formally How can information and knowledge be represented How to formalize processes Research

Ontology Pressure Intra-vascular Pressure Arterial Pressure Systemic Applies to Whole body Systolic Arterial Pressure Has phase Heart cycle phase Has phase Systolic phase Diastolic Arterial Pressure Has phase Diastolic phase Blood Pressure Has units ISO pressure units Has units Mm[Hg] Has position Body postion Is a Part of Other relation Standardization!!!!

Semantics

Domain knowledge Clinical knowledge examples: –Models of “clinical statements”: BP measurement ECG result Discharge summary –Workflow process descriptions –Protocols / Guidelines –Terminologies, ontologies, e.g. Galen, Snomed

Communication Domain specific: –How to design messages that can be understood by the receiving system –Standardization of terminology and messages, archetypes Domain independent –Technical communication between computer systems (the 7-layer Open Systems Interconnection (OSI) model)

Terminology is insufficient Terminology can tell you that “systolic blood pressure" is “the pressure of the blood in an artery at the systolic heart phase" But terminology cannot describe the structure you will use to capture the BP measurement information, for that archetypes are defined Instrum. Pat. Pos. cuff method systolic diastolic values BP measurement Terminology = ?

Seven layer OSI model

Communication

Management How to represent the data –Textual (free or formalized text) –Diagrams –Signals –Images How to store the data –Database models How to maintain the data –Information systems –Updating, archiving

Data-information-knowledge Data: the raw material Information: interpreted data Knowledge: network of related information chunks

Data-information-knowledge example Data: echocardiogram of Mina Tanenbaum Information: Statements about specific individuals. For example, the statement “Mina Tanenbaum (2y) has an atrial septal defect, 1 cm x 3.5 cm” is a statement about Mina Tanenbaum, and no-one else Knowledge : statements about classes of entities, e.g. the statement “a hole in the atrial septum can lead to dilatation, cardiac insufficiency and pulmonary hypertension”. Fragments of knowledge are models developed by studying populations of individual statements

Programme

Information systems History of monolithic and modular ISs (AH) Personal health records, mobile systems and smartcards (AH) National healthcare infrastructure (RC)

General overviews Implementation of ISs (AH) CPOE and implementation strategies (NdK) Telemedicine (NdK) Role of standardization (RC) Data reuse (RC) Medical safety and medical informatics (SE)

Evaluation (NdK) Evaluation of information systems –Quantitative vs qualitative research, study designs, outcome measures, pitfalls Evaluation of quality of care –Prognostic models, registries, quality indicators

Decision support Decision support (AH) –Guideline implementations –Types of CDSS (non(critiquing) person(non) specific Examples of decision support systems (SE) –Development, implementation and evaluation

Standards Terminology systems (RC) –Types of systems Health Level 7 (RC) Round up (AH)