The Diagnostic Decision-Making Process: Factors Influencing Diagnosis and Changes in Diagnosis

1973 ◽  
Vol 130 (9) ◽  
pp. 972-975 ◽  
Author(s):  
DAVID J. FITZGIBBONS ◽  
DEAN T. HOKANSON
2012 ◽  
Vol 4 (3) ◽  
pp. 223
Author(s):  
Kathleen Callaghan

INTRODUCTION: Identifying influences on diagnostic decisions is important because diagnostic errors often have far-reaching consequences for an individual’s future within the workforce and their eligibility for Accident Compensation Corporation–funded treatment. Most investigations of factors biasing decision making have used quantitative techniques rather than qualitative methods. AIM: To identify factors influencing GPs’ diagnostic decision-making and to develop a valid questionnaire to determine the desirability and importance of each factor’s influence. METHODS: Focus groups and the Delphi method were combined with Rasch analysis to identify factors influencing GPs’ diagnostic decision-making and then examine the strength and stability of ratings of the factors’ desirability and importance. RESULTS: Thirty-nine factors were identified. Factors demonstrating high stability but no consensus included the importance of evidence-based medicine, the potential ramifications of a diagnosis, and the desirability of medicolegal issues. Factors for which there was disagreement in the first Delphi round but consensus in the second round included the importance of patient advocacy/support groups and the desirability of examination findings. Rasch analysis indicated that the questionnaire was close to the model (88.6% and 86.2% of variance in the ratings of importance and desirability explained). DISCUSSION: Participants readily identified factors influencing GPs’ diagnostic decision-making. Their ratings did not appear to support a prescriptive model of medicine, yet two cornerstones of prescriptive medicine, clinical information and probability of disease, were rated as highly desirable and important. KEYWORDS: Decision-making; diagnosis; bias; Rasch analysis; general practitioners


2019 ◽  
Vol 69 (689) ◽  
pp. e809-e818 ◽  
Author(s):  
Sophie Chima ◽  
Jeanette C Reece ◽  
Kristi Milley ◽  
Shakira Milton ◽  
Jennifer G McIntosh ◽  
...  

BackgroundThe diagnosis of cancer in primary care is complex and challenging. Electronic clinical decision support tools (eCDSTs) have been proposed as an approach to improve GP decision making, but no systematic review has examined their role in cancer diagnosis.AimTo investigate whether eCDSTs improve diagnostic decision making for cancer in primary care and to determine which elements influence successful implementation.Design and settingA systematic review of relevant studies conducted worldwide and published in English between 1 January 1998 and 31 December 2018.MethodPreferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials were searched, and a consultation of reference lists and citation tracking was carried out. Exclusion criteria included the absence of eCDSTs used in asymptomatic populations, and studies that did not involve support delivered to the GP. The most relevant Joanna Briggs Institute Critical Appraisal Checklists were applied according to study design of the included paper.ResultsOf the nine studies included, three showed improvements in decision making for cancer diagnosis, three demonstrated positive effects on secondary clinical or health service outcomes such as prescribing, quality of referrals, or cost-effectiveness, and one study found a reduction in time to cancer diagnosis. Barriers to implementation included trust, the compatibility of eCDST recommendations with the GP’s role as a gatekeeper, and impact on workflow.ConclusioneCDSTs have the capacity to improve decision making for a cancer diagnosis, but the optimal mode of delivery remains unclear. Although such tools could assist GPs in the future, further well-designed trials of all eCDSTs are needed to determine their cost-effectiveness and the most appropriate implementation methods.


Author(s):  
Julia Hodgson ◽  
Kevin Moore ◽  
Trisha Acri ◽  
Glenn Jordan Treisman

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