Literature DB >> 9300001

What alters physicians' decisions to admit to the coronary care unit?

L Green1, D R Mehr.   

Abstract

BACKGROUND: A trial of a decision-support tool to modify utilization of the coronary care unit (CCU) failed because utilization improved after explanation of the tool but before its actual employment in the trial. We investigated this unexpected phenomenon in light of an emerging theory of decision-making under uncertainty.
METHODS: A prospective trial of the decision-support intervention was performed on the Family Practice service at a 100-bed rural hospital. Cards with probability charts from the acute ischemic Heart Disease Predictive Instrument (HDPI) were distributed to residents on the service and withdrawn on alternate weeks. Residents were encouraged to consult the probability charts when making CCU placement decisions. The study decision was between placement in the CCU and in a monitored nursing bed. Analyses included all patients admitted during the intervention trial year for suspected acute cardiac ischemia (n = 89), plus patients admitted in two pretrial periods (n = 108 and 50) and one posttrial period (n = 45).
RESULTS: In the intervention trial, HDPI use did not affect CCU utilization (odds ratio 1.046, P > .5). However, following the description of the instrument at a departmental clinical conference, CCU use markedly declined at least 6 months before the intervention trial (odds ratio 0.165, P < .001). Simply in learning about the instrument. residents achieved sensitivity and specificity equal to the instrument's optimum, whether or not they actually used it.
CONCLUSIONS: Physicians introduced to a decision-support tool achieved optimal CCU utilization without actually performing probability estimations. This may have resulted from improved focus on relevant clinical factors identified by the tool. Teaching simple decision-making strategies might effectively reduce unnecessary CCU utilization.

Entities:  

Mesh:

Year:  1997        PMID: 9300001

Source DB:  PubMed          Journal:  J Fam Pract        ISSN: 0094-3509            Impact factor:   0.493


  18 in total

1.  Teaching resource and information management using an innovative case-based conference.

Authors:  S J Kravet; S M Wright; J A Carrese
Journal:  J Gen Intern Med       Date:  2001-06       Impact factor: 5.128

2.  The Michigan Clinical Research Collaboratory: following the NIH Roadmap to the community.

Authors:  Thomas L Schwenk; Lee A Green
Journal:  Ann Fam Med       Date:  2006 Sep-Oct       Impact factor: 5.166

3.  To act or not to act: responses to electronic health record prompts by family medicine clinicians.

Authors:  Philip Zazove; Michael McKee; Lauren Schleicher; Lee Green; Paul Kileny; Mary Rapai; Elie Mulhem
Journal:  J Am Med Inform Assoc       Date:  2017-03-01       Impact factor: 4.497

4.  Heuristics: foundations for a novel approach to medical decision making.

Authors:  Nicolai Bodemer; Yaniv Hanoch; Konstantinos V Katsikopoulos
Journal:  Intern Emerg Med       Date:  2014-10-28       Impact factor: 3.397

5.  On the suitability of fast and frugal heuristics for designing values clarification methods in patient decision aids: a critical analysis.

Authors:  Arwen H Pieterse; Marieke de Vries
Journal:  Health Expect       Date:  2011-09-08       Impact factor: 3.377

6.  An Electronic-Based Curriculum to Train Acute Care Providers in Rural Haiti and India.

Authors:  Ayesha Khan; Stefanie S Sebok-Syer; Hanna Linstadt; Megan Storm; Nadeem Modan; Mukteshwari K Bosco; Gayathri Prashanth; S V Mahadevan
Journal:  J Grad Med Educ       Date:  2019-08

7.  Cognitive schemes and strategies in diagnostic and therapeutic decision making: a primer for trainees.

Authors:  Imad Salah Ahmed Hassan
Journal:  Perspect Med Educ       Date:  2013-11

Review 8.  Good judgments do not require complex cognition.

Authors:  Julian N Marewski; Wolfgang Gaissmaier; Gerd Gigerenzer
Journal:  Cogn Process       Date:  2009-09-27

Review 9.  Heuristic decision making in medicine.

Authors:  Julian N Marewski; Gerd Gigerenzer
Journal:  Dialogues Clin Neurosci       Date:  2012-03       Impact factor: 5.986

10.  Natural frequencies improve Bayesian reasoning in simple and complex inference tasks.

Authors:  Ulrich Hoffrage; Stefan Krauss; Laura Martignon; Gerd Gigerenzer
Journal:  Front Psychol       Date:  2015-10-14
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