Identification of factors associated with diagnostic error in primary care
1 Andalusian School of Public Health, Cuesta del Observatorio 4, Campus Universitario de Cartuja, 18080 Granada, Spain
2 Institute de recherche en santé publique. Université de Montréal, Montréal, Canada
3 CIBERESP. CIBER de Epidemiología y Salud Pública, Madrid, Spain
4 Universidad de Granada, Facultad de Ciencias Económicas y Empresariales, Campus Universitario de la Cartuja, 18011 Granada, Spain
5 Centro de salud Almanjayar. Servicio Andaluz de Salud, C/Pintor Joaquín Capulino Jaúregui SN., 18013 Granada, Spain
6 Centro de salud Cartuja. Servicio Andaluz de Salud, C/Pintor Joaquín Capulino Jaúregui SN., 18013 Granada, Spain
7 Centro de salud Gran Capitán. Servicio Andaluz de Salud, C/Gran Capitán, 10, 18002 Granada, España
8 Distrito de Atención Primaria de Granada -Metropolitano. Servicio Andaluz de Salud, Calle Doctor Azpitarte, 4, 18012 Granada, Spain
9 Département d’administration de la Santé, École de santé publique, 7101, Avenue du Parc., H3N 1X9 Montréal, Québec, Canada
BMC Family Practice 2014, 15:92 doi:10.1186/1471-2296-15-92Published: 12 May 2014
Missed, delayed or incorrect diagnoses are considered to be diagnostic errors. The aim of this paper is to describe the methodology of a study to analyse cognitive aspects of the process by which primary care (PC) physicians diagnose dyspnoea. It examines the possible links between the use of heuristics, suboptimal cognitive acts and diagnostic errors, using Reason’s taxonomy of human error (slips, lapses, mistakes and violations). The influence of situational factors (professional experience, perceived overwork and fatigue) is also analysed.
Cohort study of new episodes of dyspnoea in patients receiving care from family physicians and residents at PC centres in Granada (Spain). With an initial expected diagnostic error rate of 20%, and a sampling error of 3%, 384 episodes of dyspnoea are calculated to be required. In addition to filling out the electronic medical record of the patients attended, each physician fills out 2 specially designed questionnaires about the diagnostic process performed in each case of dyspnoea. The first questionnaire includes questions on the physician’s initial diagnostic impression, the 3 most likely diagnoses (in order of likelihood), and the diagnosis reached after the initial medical history and physical examination. It also includes items on the physicians’ perceived overwork and fatigue during patient care. The second questionnaire records the confirmed diagnosis once it is reached. The complete diagnostic process is peer-reviewed to identify and classify the diagnostic errors. The possible use of heuristics of representativeness, availability, and anchoring and adjustment in each diagnostic process is also analysed. Each audit is reviewed with the physician responsible for the diagnostic process. Finally, logistic regression models are used to determine if there are differences in the diagnostic error variables based on the heuristics identified.
This work sets out a new approach to studying the diagnostic decision-making process in PC, taking advantage of new technologies which allow immediate recording of the decision-making process.