1

Clinical Decision Support Systems (CDSS)

Sunil NairDalhousie Health InformaticsNovember 1, 2007

2

Artificial Intelligence in Medicine Quest for “electronic brain” Early research – “”doctors in a box” More emphasis on Diagnosis “Medical Artificial Intelligence is primarily

concerned with the construction of AI programs that perform diagnosis and make therapy recommendations”

3

What are CDSS’s

“active knowledge systems which use two or more items of patient data to generate case-specific advise”

[Wyatt J, Spiegelhalter D, 1991].

4

Clinical Decision

5

CDSS - Definition

“the provision of Clinical Knowledge and Patient related Information, intelligently filtered or presented at appropriate times, to enhance patient care”

Osheroff JA, Pifer EA, Sittig DF, Jenders RA, Teich JM. Clinical decision support implementers' workbook. Chicago: HIMSS, 2004. www.himss.org/cdsworkbook.

6

Evolution: Early Systems.1972 AAPHELP –Leeds Abdominal Pain System

1974 INTERNIST 1 – diagnosis

1976 MYCIN – Infection management -Rule based, IF and THEN rules.PUFF – LIS for interpretation of Pulmonary function test.

1980 HELP – HIS integrated with CDSS

1989 DXplain – CDSS – Diagnosis aid

Current Systems

7

Why CDSS’s?

Knowledge at the point of care Apply the best evidence Serve as a peripheral brain – assist Decision making – enhance communication. Improve Healthcare processes and

Outcomes.

8

The Information Overload

9

Clinical decision makingPaul Gorman, Medical Decision Making 1995

10

Clinical Workflow: How does CDSS fit?

11

CDSS application areas

12

CDSS - Applications Alerts and reminders Diagnostics Assistance Therapy critiquing and planning Prescribing decision support systems Information Retrieval Image recognition and interpretation Diagnostic and educational systems

13

CDSS Functions - trend

Administration Managing clinical complexity details Cost control Decision support

14

An Effective CDSS should: Speed

Anticipate/Suggest

Fit in to user’s Workflow

User friendly-interface-rules

Alerts should be descriptive

Changing direction

15

Effective CDSS features contd. Simple guidelines

Prompt Additional Information only when required

Monitor impact, feedback and respond

Manage and maintain Knowledge Based system

Ten Commandments for Effective Clinical Decision Support: Making the Practice of Evidence-based Medicine a Reality. David W. Bates, MD, MSc, Division of General Medicine and Primary Care, Brigham and Women's Hospital, May 27, 2003

16

CDSS Goals

Patient Safety – Error Reduction/prevention Cost Reduction – without compromising care Promoting best practice – Enforcing

compliance (Practice Guidelines)

17

What makes CDSS possible? Machine Learning Systems/Expert Systems

Create new knowledge Expressed as RULES or decision aids. KARDIO – for interpreting ECGA Study in Deep and Qualitative Knowledge for Expert Systems

Ivan Bratko, et al., Nov 1989http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=5059 Data Mining and Knowledge Management

systems KNOWLEDGE MANAGEMENT, DATA MINING, AND TEXT MINING IN

MEDICAL INFORMATICS., Hsinchun chen et al., http://ai.arizona.edu/hchen/chencourse/MedBook/Chapter_01.pdf

18

CDSS - Benefits Improve patient safety

Reduce medical errors Improved medication and test ordering

Improve quality of care Application of Clinical Pathways and Guidelines Evidence based Medicine Improved Clinical documentation Increase quality time for direct patient care

Improve efficiency in Healthcare delivery Reduce costs, reduce test duplication, decrease

adverse events

19

CDSS: Computerized Physician Order Entry Growing evidence that CPOE reduce medical

errors and adverse drug events.Effects of Computerized Physician Order Entry and Clinical Decision

Support Systems on Medication Safety Rainu Kaushal,MD,MPH et al Arch Intern Med. 2003 http://archinte.ama-assn.org/cgi/content/full/163/12/1409

Effects of Computerized Clinical Decision Support Systems on Practitioner Performance and Patient Outcomes

Garg et al JAMA. 2005http://jama.ama-assn.org/cgi/content/full/293/10/1223

20

Opposing views…

CPOE facilitate medication error ‘risks’, create new errors.

Role of Computerized Physician Order Entry Systems in Facilitating

Medication Errors. Ross Koppel,PhD et al. JAMA. 2005 http://jama.ama-assn.org/cgi/content/full/293/10/1197

Computer Technology and Clinical Work Robert L. Wears et. al. JAMA. 2005;293:1261-1263. http://jama.ama-assn.org/cgi/content/full/293/10/1261

21

CDSS: Drawbacks

22

CDSS Issues: Success or Failure

Careful evaluation of user needs Leadership Integration Issues Human-Computer interface

23

Why does CDSS fail?

Belief that Diagnosis is the dominant decision making issue “what does this patient have?” vs. “how can I help

this patient” Cognitive factors – different people

understand differently. Human-Computer interaction.

http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=130077

24

CDSS reasons for failure.

Dependence on electronic patient record. Challenging task of interaction between

technologies and organizations. Only as effective as the underlying

Knowledge base, needs constant updating. Additional effort (already busy, overworked) Resist to Change Computer Literacy

25

CDSS Integration Objectives:

Critical Evaluation Identifying main factors involved Understand that Healthcare is Complex and

Patient focused Efficient Data Management Tracking the “Alerts” Standardization/Interoperability

26

Evaluation

Problem Definition

Potential for Errors

Change Issues

Measure Outcomes

Implementation

27

CDSS: Summary

Possible in a complex healthcare environment

Has to fit in to the workflow Enhance patient safety features

28

Conclusion

The future of CDSS depends on removal of barriers to implementation.

Continue to have profound effect on medical education

Trained clinicians will always be required, the key is cooperative relationship between physician and computer based decision making tool

29

Discussions CDSS recommendation

to clinician results in patient harm, who is responsible?

Questions

30

Thank you!