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Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

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Page 1: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

Joining up Computation and Thinking in Clinical

Medicine

David GlasspoolSchool of Informatics, University

of Edinburgh

Page 2: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

Outline

• What impact has computation had on clinical thinking?

• What impact has clinical thinking had on computation?

• The opportunities for real impact in medicine.

Page 3: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

What impact has computation had on clinical thinking?

• Computation has had a massive impact on medicine itself.– Tools (CT scans, dose calculators, risk calculators)– Resources (large trials)

• IT will have a big impact on administration.– NHS CfH plans.

• Some impacts on clinical thinking already.– Ease of looking up information.– Conjunctive search – Impossible with paper

resources.

Page 4: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

Why not more?

• Conservative field– Dealing with life & death.– Long established profession – tried and tested

procedures.

• Computer systems that try to go further than administrative support have a sad history of failure after deployment– Disuse, protest, boycott.– Because they hinder the work of the clinician.

Page 5: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

The problems

• Growth of medical knowledge

Pile of 855 guidelines in general practices in the Cambridge and Huntingdon Health Authority

Hibble et al., BMJ 1998

Page 6: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

The problems

• Adverse events– Over 10% of patients admitted to NHS hospitals

experienced an adverse event; – Around half of these events were judged

preventable with ordinary standards of care.– A third of adverse events led to moderate

disability or death. Vincent et al., BMJ, 2001

Page 7: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

“The application of what is known already will have a greater impact on health and disease than any single drug or technology likely to be introduced in the next decade.”Sir Muir Gray, Director of Clinical Knowledge, Process and Safety, NHS Connecting for Health

“Medicine is a humanly impossible activity.”Alan Rector, University of Manchester

“The power of the unaided mind is highly overrated. Without external aids, memory, thought, and reasoning are all constrained.”Donald Norman, “Things That Make Us Smart” [472, ch. 3]

Page 8: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

What to do about it?

• Because of this, computational assistance is unavoidable.

• But to do this effectively (to augment clinicians' thinking, not hinder it), we must understand:

– Range of things clinicians think about

– Way they represent problems

– Their workflow, and points of high load

Page 9: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

Clinical thinking as a domain for theories of thinking

• Clinical medicine is an excellent domain for studying thinking.– Covers the full gamut of cognitive processes.– The various processes are relatively explicit.– Their operation and relationships can be studied.– Plenty of domain material for case study.

• I will outline approach at three levels:1. Knowledge representation and Decisions

2. Framing decisions

3. Plans of action include multiple decisions

Page 10: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

1. Knowledge representation and Decisions

Page 11: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

Decision making

• Much work on how evidence should be weighed in making a decision.

• Largely concentrated on normative models.

Page 12: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

Normative approaches

“... there is essentially only one way to reach a decision sensibly. First, the uncertainties present in the situation must be quantified in terms of values called probabilities. Second, the consequences of the courses of action must be similarly described in terms of utilities. Third, that decision must be taken which is expected, on the basis of the calculated probabilities, to give the greatest utility.”

Dennis Lindley.

Page 13: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

Descriptive approach

• How do clinicians really make decisions in the non-idealised world?– Numbers are hard to come by– Evidence is often qualitative– Need to weigh different types of evidence– Need to make a decision that's “good enough”,

quickly.• In our experience, the structure of the

evidence is more important to the clinician than the numbers.– Clinicians are good at making decisions. Not at

having the latest facts at their fingertips.

Page 14: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

MyocardialInfarct

Chlopidogrel

aspirin

Trial

gastritis

S1

S2

Argument logic approach

Page 15: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh
Page 16: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh
Page 17: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh
Page 18: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

Why argumentation?

• Scalability– Many different types of evidence & knowledge.

• Quantitative vs qualitative– Large quantity of knowledge – Filtering issue.

• Presentation– Acceptable to (generally welcomed by)

clinicians.– Easy to absorb quickly.– Conveys the structure of the argument quickly.– Explanation is built in.

Page 19: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

2. Framing decisions

Page 20: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

Embedding decision making in a complete decision cycle

Identification of problem

Option generation

Information search

Appraisal and choice

Implementation and monitoring

Pre-selectional phase

Selectional phase

Post-selectional phase

Page 21: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

The “Domino” (Fox & Das, 2000)

Page 22: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

What the “domino” gives us

• A wider perspective.- Treat all these processes with equal weight.

• A framework for relating these processes to other fields.- Cognitive psychology.- Neuroscience.

• A framework for targeting cognitive overload.- And more tools in our toolkit for mitigating it

(not just “make the decision for the user”).

Page 23: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

Areas of high load – Triple Assessment example

Page 24: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

3. Plans of action include multiple decisions

Page 25: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

A scenario

A woman tests positive for a mutation to one of the two known genes predisposing to breast cancer (BRCA1/BRCA2). If no action is taken to mitigate the risk, the chances are high that she will contract a potentially fatal cancer during her lifetime.

A genetics counsellor works with the woman to plan a strategy of intervention.

Page 26: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

No “correct” plan of action

Plan will reflect individual needs and plans of patient. E.g:

•Planning to have children: Need to avoid oophorectomy and drugs like Tamoxifen.

•People vary widely in their willingness to consider mutilating surgery.

•Timing of oophorectomy and some drugs relative to each other and to menopause affects their action.

Page 27: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

1. Hold plan in memory.

2. Identify options at each step.

3. Identify pros and cons.

4. Track constraints & dependencies.

5. Track effect of plan with respect to its goals.

Cognitive demands of planning

Page 28: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

REACT(Risks, Events, Actions & Consequences over Time)

Page 29: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

Areas of high load – Treatment planning example

Identify

options

Identify pros & cons

Maintain plan in memory

Track constraints, dependencies,

outcomes

Page 30: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

Summary• Demands of clinical workload and rapidly

increasing knowledge base are serious.• Computational systems can help by freeing

clinicians to think about the aspects they are skilled at.

• They must:– Target specific areas of high cognitive load.– Allow “offloading”, but don't impose it.– Bring the relevant clinical knowledge to the

clinicians' fingertips.

• ...if computational systems are to allow clinicians to be masters of the data, rather than slaves to it.

Page 31: Joining up Computation and Thinking in Clinical Medicine David Glasspool School of Informatics, University of Edinburgh

John Fox

Ayelet Oetinger

Sanjay Modgil

Liz Black

James Smith-Spark

Pete Yule

Matt South

Dejana Braithwaite

Rick Cooper

Jon Bury

Fortunato Castillo

Victoria Monaghan

Kirsty Bradbrook

Rachel McCloy

Fred Kavalier

Graham Winstanley

With thanks to: