introduction to the programme

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-vascularPressure

ArterialPressure

Systemic

Applies to

Whole body

Systolic ArterialPressure

Has phase

Heart cyclephase

Has phase

Systolicphase

Diastolic ArterialPressure

Has phase

Diastolicphase

BloodPressure

Has units

ISO pressureunits

Has units

Mm[Hg]

Has positionBody

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 = ?

0..11

0-1000

0-1000

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-knowledgeexample

• 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)