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Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

Postal Subscription Code 80-967

2018 Impact Factor: 1.847

Front Med    2012, Vol. 6 Issue (1) : 89-93    https://doi.org/10.1007/s11684-012-0183-9
RESEARCH ARTICLE
Clinical decision-making by the emergency department resident physicians for critically ill patients
Tengda Xu, Jun Xu, Xuezhong Yu, Sui Ma, Zhong Wang()
Department of Emergency Medicine, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China.
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Abstract

The application of main methodologies for clinical decision-making by residents in emergency medical practice was assessed, and issues in this area were investigated. The treatments provided to 2 611 critical patients by the Peking Union Medical College Hospital of were analyzed by independent investigators who evaluated the main clinical decision-making processes applied by the hospital residents. The application of decision-making strategies by PG1 and PG3 groups, which means the residents in first year and the third year, were compared. The patients were treated according to pattern recognition (43.0%), hypothetico-deductive reasoning (23.4%), event-driven models (19.3%), and rule-using algorithms (5.9%). A significant difference was found between PG1 and PG3 groups (χ2=498.01, P<0.001). Pattern recognition and hypothetic-deductive methods were the most common techniques applied by emergency physicians in evaluating critically ill patients. The decision-making processes applied by junior and senior residents were significantly different, although neither group adequately applied rule-using algorithms. Inclusion of clinical decision-making in medical curricula is needed to improve decision-making in critical care.

Keywords clinical decision-making      emergency medicine      critically ill patient      resident      methodology     
Corresponding Author(s): Wang Zhong,Email:wangzhong523@vip.163.com   
Issue Date: 05 March 2012
 Cite this article:   
Tengda Xu,Jun Xu,Xuezhong Yu, et al. Clinical decision-making by the emergency department resident physicians for critically ill patients[J]. Front Med, 2012, 6(1): 89-93.
 URL:  
https://academic.hep.com.cn/fmd/EN/10.1007/s11684-012-0183-9
https://academic.hep.com.cn/fmd/EN/Y2012/V6/I1/89
Emergency problemsnEmergency problemsn
Dyspnea552Sudden death69
Chest pain445Epilepsy63
Coma239Hyperpyrexia58
Palpitation193Syncope56
Gastrointestinal bleed187Anaphylaxis47
Weakness120Dizziness, vertigo33
Acute intoxication89Hemoptysis33
Altered mental status87Acute pelvis pain30
Acute abdominal pain85Vaginal bleeding29
Multiple trauma78Jaundice25
Headache76Diarrhea, constipation17
Tab.1  Acute conditions and number of cases ( = 2 611)
Clinical decision-makingPattern recognitionRule-using algorithmHypothetico deductiveEvent drivenOthers
PG1group*192 (22.1%)61 (7.0%)417 (48.0%)163 (18.7%)37 (4.3%)
PG3 group**930 (53.4%)93 (5.3%)194 (11.1%)341 (19.6%)183 (10.5%)
χ2232.632.91438.990.2729.45
P&lt; 0.0010.08&lt; 0.0010.60&lt; 0.001
Tab.2  Comparison of clinical decision-making processes between the two groups
Errors in clinical decision-makingImplicationsPercentage (n)
1Anchoring biasAccepted previously applied labels without questioning diagnosis and treatment23.0% (49)
2Faulty hypothesis generationMaintained a narrow view of possible diagnosis and hypotheses15.9% (34)
3Over-rigid, overconfidenceUnwilling to accept a good or likely presumptive diagnosis before making critical time-dependent therapeutic decisions14.0% (30)
4Sutton’s slipOnly considered the obvious diagnosis, failed to see the whole picture8.4% (18)
5Fault hypotheses refinementFailure to revise list of diagnostic hypotheses to explain results of data gathered8.4% (18)
6Biased memoryRelied only on knowledge from prior experience7.5% (16)
7Revision under stressRecently learned behavior replaced by older familiar one6.5% (14)
8LapsesFailures in memory that resulted in omissions and inefficiencies6.5% (14)
9Playing the oddsFault estimate of disease prevalence.5.6% (12)
10Misapplied rulesUsed wrong algorithm or pathway or used correct heuristic incorrectly4.2% (9)
Tab.3  The 10 most common types of clinical decision-making errors
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