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1 Medical Informatics Dr. Shahram Yazdani © 2002 ATGCI
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Page 1: 1 Medical Informatics Dr. Shahram Yazdani © 2002 ATGCIATGCI.

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Medical Informatics

Dr. Shahram Yazdani

© 2002 ATGCI

Page 2: 1 Medical Informatics Dr. Shahram Yazdani © 2002 ATGCIATGCI.

2 Dr. Shahram Yazdani© 2002 ATGCI

Medical Informatics

Medical informatics is the application of computers, communications and information technology and systems to all fields of medicine-medical care, medical education and medical research

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Biomedical Information

Care Providers

Patients

DatabasesSearch enginesValue added Pub.EB Pub.POEM collections

Information masteryCritical appraisal

Data acquisition

Data storage

Vocabularies

Organization of data

Machine interfaces

Data retrieval

Data

Dx/T

x

Research

Information

Electronic medical records

Laboratory IS

Digital imaging and

Radiological IS

Patient monitoring systems

Medical information

directed to:

–a specific need

–at the right time

–in the right place

–to the right person

Decision-Support Systems

Diagnosis / Interpretation

Therapy / Management

Automated reminders and alert systems

Electronic prescription and order entry

Drug IS and Automated dispensing

Telemedicine

National health databank

National health code

National health card

Computer Assisted InstructionWeb Based Learning

Clinical JudgmentDiagnostic ReasoningTherapeutic Planning

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Medical Informatics is Multidisciplinary

Medicine/ Biology Mathematics Information Systems Computer Science Statistics Decision Analysis Economics/Health Care Policy Psychology

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Medical Records

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Investment in medical records

In UK, the cost of medical records units run between 2% and 6% of NHS turnover

Healthcare providers spend 20-75% of their time reading, writing, sorting and searching through the notes

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Shortcomings of the paper medical record

Find the record (lost, being used elsewhere) Find data within the record (poorly organized,

missing) Read data (legibility) Update data Record fragmentation Moving records Redundancy (re-enter data in multiple forms) Statistics and Research (can not search across

patients) Passive (no automated decision support)

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Benefits of electronic medical record

Access, Availability, transfer and retrieval Legibility, Abstraction, reporting Saves time: find data 4 times faster Reduced data entry (reuse data) Better organization by imposing structure Storage space Allow multiple views including aggregation Automated checks on data entry (spelling

checks,k=50, sum of WBC, pregnant man) Data quality and standards Automated decision support Statistics and research

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Images

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Picture Archiving and Communications System

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Image management Traditional Film libraries

– Expensive – Inefficient – Film can only be in one place– Problem in interpretation (20% on detection, 10-

50% on diagnosis)

Digital image library – Less expensive– More efficient– Tele-radiology– Automated interpretation

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3 Dimensional Imaging

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Medical Errors and

Point of Care Delivery of Information

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Lots of lives to save Medical error is the 3rd largest cause of death in

the U.S. exceeded only by heart disease and cancer. (JAMA, July 26, 2000, p 483)

– 12,000 deaths/year from unnecessary surgery– 7,000 deaths/year from medication errors in hospitals– 20,000 deaths/year from other errors in hospitals– 80,000 deaths/year from nosocomial infections in

hospitals– 106,000 deaths/year from adverse effects of

medications (4th leading cause of death) 50-90% of medication errors can be eliminated

at time of installation of automation at the point of care.

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Source: Wireless and Mobile Computing. First Consulting Group, Oct 2001.

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Point of Care Automation Results

Malcolm, BEliminating Medication Errors Through Point of Care Devices. Proceedings of HIMSS 2000, Session 73, Dallas.

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PDA Medical Record All essential medical data on a

Palm Pilot or PocketPC. Designed to integrate with

global medical data system.

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Decision Support Systems

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Levels of Automated Support

(Van Bemmel and Musen, 1997)

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Computerized reminders

Computerized reminders can improve compliance with recommended guidelines– Increase preventive services– Increase use of appropriate medications – Increase use of other interventions

Hunt et al. JAMA. 1998; Shea et al. J Am Med Inform Assoc. 1996

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Computerized decision support

Computerized decision support can improve quality – Prevention of venous thromboembolism– Use of antibiotics

Durieux et al. JAMA. 2000; Teich et al. Arch Intern Med. 2000;

Evans et al. N Engl J Med. 1998

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EMR with Decision Support Electronic medical records with decision

support can reduce costs – Reducing medical errors and adverse events– Recommending equally effective but less costly

alternative interventions– Reducing the use of inappropriate tests– Reducing the ordering of redundant tests

Teich et al. Arch Intern Med. 2000; Bates et al. JAMA. 1998; Glaser et al. Proc Healthcare Information and Management Systems Society Annual Conf. 1996

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de Dombal’s System Domain: Acute abdominal pain Input: Signs and symptoms of patient Output: Probability distribution of diagnoses Method: Bayesian Evaluation: an eight-center study involving 250 physicians

and 16,737 patients Results:

– Diagnostic accuracy rose from 46 to 65%– The negative laparotomy rate fell by almost half– Perforation rate among patients with appendicitis fell by half– Mortality rate fell by 22%

Results using survey data consistently better than the clinicians’ opinions and even the results using human probability estimates!

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Electronic Prescription

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Prescription warning messages generated by computerised system from October 1998 to August 1999 

CategoryNo of warning

messagesNo (%) of prescriptions

completed

Disallowed     58 0  Contraindications     37 0  Interactions     21 0Password level warnings    749    322 (43)  Contraindications    141    103 (73)  Interactions     99     84 (85)  Maximum recommended single dose

exceeded   206     89 (43)

  Maximum recommended daily dose exceeded

   303     46 (15)

Low level warnings 16 607 15 350 (92)  Contraindications    793    677 (85)  Interactions 15 743 14 635 (93)  Maximum recommended single

dose exceeded    46     25 (54)

  Maximum recommended daily dose exceeded

    25     13 (52)

BMJ 2000;320:750–3

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Computerized order entry Computerized order entry systems can

reduce medication errors – Improve drug prescribing– Improve drug dosing– Drug-drug interactions– Drug allergies

Bates et al. JAMA. 1998; Bates et al. J Am Med Inform Assoc. 1999; Teich et al. Arch Intern Med. 2000

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Automated Dispensing

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Card Technologies in

Health Care

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Functions of health care cards

Identification Access control Data carrier (portable record) Information transfer Authentication Encryption/Decryption

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Card technologiesCard technologies Unit cost($) Major benefits

Paper with barcode 0.01- 0.04 Inexpensive, bar code

Plastic, embossed 0.1- 0.15 Familiar, paper transfer

Serial memory card 1.5- 4.0 Additional storage

Computer chip card 3.5- 15.0 Additional data security, difficult to copy

Optical card 6.0- 8.0 Much more storage

IC optical card 10.0- 15.0 Large storage and data security

PC card 50.0- 100.0 More storage and computational capacity

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Computer Literacyamong Physicians

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Barriers are neither technology nor cost, Barriers are cultural: the doctors

Michael L.

Millenson

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Do you personally use a computer?

Personal Computer Use      % of the NOs who plan to do so in the next 12 months

Total YES NO No response

Overall 3128 78.6% 20.2% 1.2% 100.0% 37.2%

Females 938 73.0% 25.9% 1.1% 100.0% 42.0%

Males 2190 81.0% 17.7% 1.3% 100.0% 34.3%

< 35 320 76.3% 22.2% 1.6% 100.0% 43.7%

35-44 1033 84.2% 15.1% 0.7% 100.0% 44.2%

45-54 957 83.4% 15.3% 1.4% 100.0% 33.6%

55-64 585 72.1% 26.3% 1.5% 100.0% 39.0%

65+ 233 53.6% 44.6% 1.7% 100.0% 25.0%

GP/FP 1685 74.7% 24.0% 1.4% 100.0% 38.4%

Med Spec 1035 84.6% 14.3% 1.1% 100.0% 38.5%

Surg Spec 408 79.7% 19.4% 1.0% 100.0% 29.1%

Rural 302 73.8% 24.2% 2.0% 100.0% 38.4%

Urban 2826 79.1% 19.7% 1.1% 100.0% 37.1%

CMAJ - October 19, 1999

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Barriers Lack of technology infrastructure Lack of standards Cultural barriers

– Eminence-based medicine– Tradition– Resistance to change

Complexity of medicine Workflow issues Human factor issues

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Web Based Learning

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Transformed view of knowledge

Dynamic, open ended, multidimensional,

and public

Static, finite, linear, and private.

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Defining web-based teaching & networked learning

materials + human interaction

materials + human interaction

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Online learning, Teaching, Tutoring

Classroom teaching

Tutor enhanced online learning

Computer-enhanced classroom teaching

Independent online learning

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Online learning, Teaching, Tutoring

Classroom teaching

Computer-enhanced classroom teaching

Tutor enhanced online learning

Collaborative and independent

online learning

Distance learning

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Advantages of CAI and WBL

Self directed learning Interactivity Privacy Individualized to student:

– Pace– Weak area

24 hr access Social interaction and Group work

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Immediate Feedback Permanent record Economy of scale Promote active engagement Multimedia Access to global resources Information retrieval

Advantages of CAI and WBL

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Uses of CAI in clinical medicine

Focus on diagnosis and therapy rather than on facts

Encourage experimentation and exploration Greater scope-see outpatient cases Prototypic cases that are not complex Include rare cases Better measure of competency than multiple

choice test

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Can experiment without danger to patient

Follow course of patient over time Uses physiologic models, production

rules, …

Uses of CAI in clinical medicine

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Virtual Reality

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Using the MIST system (Mentice Medical Simulation AB, Gothenburg, Sweden) for training and assessment of psychomotor skills for minimally invasive surgery

BMJ VOLUME 323 20 OCTOBER 2001

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The da Vinci Surgical System (Intuitive Surgical, California, USA) for performing minimally invasive surgery. The surgeon sits at a control console with 3D visualization of the surgical field and the robotic surgical instruments

BMJ VOLUME 323 20 OCTOBER 2001

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Virtual Reality

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Virtual Reality

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Goals of Collaborative eHealth:

Saving Time, Saving Money,

Saving Lives

Turning the Promise of Mobile Computing into a Reality