Identifying early warning signs for diagnostic errors in primary care: A qualitative study
Balla J., Heneghan C., Goyder C., Thompson M.
Objective: We investigate the mechanisms of diagnostic error in primary care consultations to detect warning signs for possible error. We aim to identify places in the diagnostic reasoning process associated with major risk indicators. Design: A qualitative study using semistructured interviews with open-ended questions. Setting: A 2-month study in primary care conducted in Oxfordshire, UK. Participants: We approached about 25 experienced general practitioners by email or word of mouth, 15 volunteered for the interviews and were available at a convenient time. Intervention: Interview transcripts provided 45 cases of error. Three researchers searched these independently for underlying themes in relation to our conceptual framework. Outcome measures: Locating steps in the diagnostic reasoning process associated with major risk of error and detecting warning signs that can alert clinicians to increased risk of error. Results: Initiation and closure of the cognitive process are most exposed to risk of error. Cognitive biases developed early in the process lead to errors at the end. These warning signs can be used to alert clinicians to the increased risk of diagnostic error. Ignoring red flags or critical cues was related to processes being biased through the initial frame, but equally well, it could be explained by knowledge gaps. Conclusions: Cognitive biases developed at the initial framing of the problem relate to errors at the end of the process. We refer to these biases as warning signs that can alert clinicians to the increased risk of diagnostic error. We conclude that lack of knowledge is likely to be an important factor in diagnostic error. Reducing diagnostic errors in primary care should focus on early and systematic recognition of errors including near misses, and a continuing professional development environment that promotes reflection in action to highlight possible causes of process bias and of knowledge gaps.