Dataset Information

Identifying early warning signs for diagnostic errors in primary care: a qualitative study.

ABSTRACT:

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.

SUBMITTER: Balla J

PROVIDER: S-EPMC3467597 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Publications

Identifying early warning signs for diagnostic errors in primary care: a qualitative study.

Balla John J Heneghan Carl C Goyder Clare C Thompson Matthew M

BMJ open 20120913 5

<h4>Objective</h4>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.<h4>Design</h4>A qualitative study using semistructured interviews with open-ended questions.<h4>Setting</h4>A 2-month study in primary care conducted in Oxfordshire, UK.<h4>Participants</h4>We approached about 25 experienced general practitioners by email o ...[more]

PMID: 22983786

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Project description:Dengue is the most common mosquito-borne viral disease in humans. However, the sensitivities of warning signs (WSs) for identifying severe dengue in adults are low, and the utility of lactate levels for identifying severe dengue in adults has not been verified. Therefore, we aimed to evaluate the diagnostic accuracy of using peripheral venous lactate levels (PVL), as well as WSs established by the World Health Organization, for identifying severe dengue.We prospectively evaluated individuals hospitalized for dengue who were admitted to the Hospital for Tropical Diseases in Thailand between May 2013 and January 2015. Blood samples to evaluate PVL levels were collected at admission and every 24 h until the patient exhibited a body temperature of <37.8 °C for at least 24 h. Data were recorded on a pre-defined case report form, including baseline characteristics, clinical parameters, and laboratory findings.Among 125 patients with confirmed dengue, 105 (84.0%) patients had non-severe dengue, and 20 (16.0%) patients had severe dengue. The presence of clinical fluid accumulation as a WS provided high sensitivity (75.0%, 95% confidence interval [CI]: 50.9-91.3%) and specificity (90.5%, 95% CI: 83.2-95.3%). The PVL level at admission was used to evaluate its diagnostic value, and receiver operating characteristic curve analysis revealed an area under the curve of 0.84 for identifying severe dengue. At the optimal cutoff value (PVL: 2.5 mmol/L), the sensitivity and specificity were 65.0% (95% CI: 40.8-84.6%) and 96.2% (95% CI: 90.5-99.0%), respectively. A combined biomarker comprising clinical fluid accumulation and/or PVL of ≥2.5 mmol/L provided the maximum diagnostic accuracy for identifying severe dengue, with a sensitivity of 90.0% (95% CI: 68.3-98.8%) and a specificity of 87.6% (95% CI: 79.8-93.2%).Clinical fluid accumulation and/or PVL may be used as a diagnostic biomarker of severe dengue among adults. This biomarker may facilitate early recognition and timely treatment of patients with severe dengue, which may reduce dengue-related mortality and hospital burden.

Dataset Information

Identifying early warning signs for diagnostic errors in primary care: a qualitative study.

Objective

Design

Setting

Participants

Intervention

Outcome measures

Results

Conclusions

Publications

Identifying early warning signs for diagnostic errors in primary care: a qualitative study.

Similar Datasets

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