1 / 23

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

guang
Download Presentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

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

  2. Where? York

  3. The plan • The problem • Some evidence • Solutions?

  4. 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)

  5. The problem: nurses face same uncertainties

  6. Lets agree to disagree

  7. The problem: context

  8. 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)

  9. Problem: “getting” care needs experience

  10. One learns the basic patterns

  11. Then you can see it

  12. The good news. Information behaviour is… • Think number between 10 and 20 • Add the digits together (e.g. 13 = 1+3 = 4) • Subtract from the first number you thought of • Subtract 5 • Convert to a letter (e.g. 1=A, 2=B etc…) • Listen to me…

  13. Entirely predictable Denmark Elephant (*maybe Emu… for Australians)

  14. uncertainty reduction via synthesis?

  15. The problem: everyone hate numbers

  16. “the seasoned nurse’s well honed sixth sense enables her to make lifesaving decisions” Benner & Tanner 1997 One solution: intuition

  17. In common?

  18. 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)

  19. 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%

  20. methods Signal detection analysis1 1Stanislaw & Todorov 1999 Calculation of signal detection theory Measures, Behaviour research measures, instruments and computers 31(1), 137-149

More Related