Reducing diagnostic error with computer-based clinical decision support

Errors in clinical diagnosis: a narrative review

Diagnostic errors are often caused by cognitive biases and sometimes by other cognitive errors, which are driven by factors specific to clinicians, patients, diseases, and health care systems. An experienced clinician diagnoses routine cases intuitively, effortlessly, and automatically through non-analytic reasoning and uses deliberate, cognitively effortful analytic reasoning to diagnose atypical or complicated clinical cases. However, diagnostic errors can never be completely avoided. To minimize the frequency of diagnostic errors, it is advisable to rely on multiple sources of information including the clinician's personal experience, expert opinion, principals of statistics, evidence-based data, and well-designed algorithms and guidelines, if available. It is also important to frequently engage in thoughtful, reflective, and metacognitive practices that can serve to strengthen the clinician's diagnostic skills, with a consequent reduction in the risk of diagnostic error. The purpose of this narrative review was to highlight certain factors that influence the genesis of diagnostic errors. Understanding the dynamic, adaptive, and complex interactions among these factors may assist clinicians, managers of health care systems, and public health policy makers in formulating strategies and guidelines aimed at reducing the incidence and prevalence of the phenomenon of clinical diagnostic error, which poses a public health hazard.

Strategies to reduce diagnostic errors: a systematic review

Background

To evaluate the effectiveness of audit and communication strategies to reduce diagnostic errors made by clinicians.

Methods

MEDLINE complete, CINHAL complete, EMBASE, PSNet and Google Advanced. Electronic and manual search of articles on audit systems and communication strategies or interventions, searched for papers published between January 1990 and April 2017. We included studies with interventions implemented by clinicians in a clinical environment with real patients.

Results

A total of 2431 articles were screened of which 26 studies met inclusion criteria. Data extraction was conducted by two groups, each group comprising two independent reviewers. Articles were classified by communication (6) or audit strategies (20) to reduce diagnostic error in clinical settings. The most common interventions were delivered as technology-based systems n = 16 (62%) and within an acute care setting n = 15 (57%). Nine studies reported randomised controlled trials. Three RCT studies on communication interventions and 3 RCTs on audit strategies found the interventions to be effective in reducing diagnostic errors.

Conclusion

Despite numerous studies on interventions targeting diagnostic errors, our analyses revealed limited evidence on interventions being practically used in clinical settings and a bias of studies originating from the US (n = 19, 73% of included studies). There is some evidence that trigger algorithms, including computer based and alert systems, may reduce delayed diagnosis and improve diagnostic accuracy. In trauma settings, strategies such as additional patient review (e.g. trauma teams) reduced missed diagnosis and in radiology departments review strategies such as team meetings and error documentation may reduce diagnostic error rates over time.

Trial registration

The systematic review was registered in the PROSPERO database under registration number CRD42017067056.

Electronic supplementary material

The online version of this article (10.1186/s12911-019-0901-1) contains supplementary material, which is available to authorized users.