Nurses and “irreducible” Uncertainty Prof. Carl Thompson RN, PhD.

Nurses and “irreducible” Uncertainty

Prof. Carl Thompson RN, PhD

Where?

York

The plan

The problem

Some evidence

Solutions?

The problem: irreducible uncertainty

David Eddy (MD) Variations & uncertainty linked

Definitions Diagnosis Treatment Observing outcomes “Putting it all together” (i.e.

judgement and decision making)

The problem: nurses face same uncertainties

Lets agree to disagree

The problem: context

The problem: errors

11% admissions suffer adverse events, 50% due to error

1 million patients suffer iatrogenic harm,

1000 per year die 7 - 8.4 additional bed days per adverse

event Mandatory reporting does not work

(sensitivity 5%)

(NAO 2005, NPSA 2002, Akbari and Sheldon 2006)

Problem: “getting” care needs experience

One learns the basic patterns

Then you can see it

The good news. Information behaviour is…

1. Think number between 10 and 20

2. Add the digits together (e.g. 13 = 1+3 = 4)

3. Subtract from the first number you thought of

4. Subtract 5

5. Convert to a letter (e.g. 1=A, 2=B etc…)

6. Listen to me…

Entirely predictable

Denmark

Elephant

(*maybe Emu… for Australians)

uncertainty reduction via synthesis?

The problem: everyone hate numbers

One solution: intuition

“the seasoned nurse’s well honed sixth sense enables her to make lifesaving decisions”

Benner & Tanner 1997

In common?In common?

Critical Event Risk Assessment

50% of cardiac arrests had deteriation documented (Hodgetts 2002)

Nursing knowledge “basics”: heart rate, resps, O2

98% of calls to emergency teams/outreach nurse initiated (Cioffi 2000)

25% of all calls delayed by 1-3 hours (Crispin and Daffurn 1998)

Misinterpretation and mismanging valuable clinical information (McQuillan et al. 1998)

methods

50 scenarios in wards/units/ITUs

250 nurses (Oz, UK, Canada, Holland) years registered 11.6

(8.8) years in specialty 9 (6.7) age 34 years (SD 8.1) 64% > critical care

experience Graduates: UK 6%;

Canada 77%; Netherlands 40%; Aus100%

methods

Signal detection analysis1

  risk No risk

Yes TP+ FP-

no FN- TN+

1Stanislaw & Todorov 1999 Calculation of signal detection theory Measures, Behaviour research measures, instruments and computers 31(1), 137-149

Tendency toward intervening, misses and false alarms (N = 237) Experience in Critical Care in Years (n)

Decision Tendency: Mean β (SD)

Mean Proportion of Misses

Mean Proportion of False Alarms

0 (70) -.05 (.54) 0.27 0.30

1 (84) -.18 (.51) 0.21 0.34

2 (33) -.47 (.52) 0.16 0.38

≥ 3 (50) -.10 (.58) 0.23 0.30

SD = standard deviation.