Clinical criteria to screen for inpatient diagnostic errors: a scoping review

Shenvi, Edna C.; El‐Kareh, Robert

doi:10.1515/dx-2014-0047

Cited by 21 publications

(17 citation statements)

References 45 publications

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“…Because very few methods focus on inpatient diagnostic errors, future efforts using similar triggers could be useful to identify and understand contributory factors associated with diagnostic adverse events in inpatient settings. 6–8 While this trigger cannot be used for estimating frequency, a combination of various types of electronic triggers could be refined and tested and if found useful can be used to calculate frequency of inpatient diagnostic errors, a number that remains elusive and yet to be defined in US hospitals. 23 …”

Section: Discussionmentioning

confidence: 99%

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An electronic trigger based on care escalation to identify preventable adverse events in hospitalised patients

et al. 2017

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BackgroundMethods to identify preventable adverse events typically have low yield and efficiency. We refined the methods of Institute of Healthcare Improvement’s Global Trigger Tool (GTT) application and leveraged electronic health record (EHR) data to improve detection of preventable adverse events, including diagnostic errors.MethodsWe queried the EHR data repository of a large health system to identify an ‘index hospitalization’ associated with care escalation (defined as transfer to the intensive care unit (ICU) or initiation of rapid response team (RRT) within 15 days of admission) between March 2010 and August 2015. To enrich the record review sample with unexpected events, we used EHR clinical data to modify the GTT algorithm and limited eligible patients to those at lower risk for care escalation based on younger age and presence of minimal comorbid conditions. We modified the GTT review methodology; two physicians independently reviewed eligible ‘e-trigger’ positive records to identify preventable diagnostic and care management events.ResultsOf 88 428 hospitalisations, 887 were associated with care escalation (712 ICU transfers and 175 RRTs), of which 92 were flagged as trigger-positive and reviewed. Preventable adverse events were detected in 41 cases, yielding a trigger positive predictive value of 44.6% (reviewer agreement 79.35%; Cohen’s kappa 0.573). We identified 7 (7.6%) diagnostic errors and 34 (37.0%) care management-related events: 24 (26.1%) adverse drug events, 4 (4.3%) patient falls, 4 (4.3%) procedure-related complications and 2 (2.2%) hospital-associated infections. In most events (73.1%), there was potential for temporary harm.ConclusionWe developed an approach using an EHR data-based trigger and modified review process to efficiently identify hospitalised patients with preventable adverse events, including diagnostic errors. Such e-triggers can help overcome limitations of currently available methods to detect preventable harm in hospitalised patients.

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Section: Discussionmentioning

confidence: 99%

“… 5 For example, similar to many other measurement methods, current applications of GTT usually are unable to find ‘omission’ events related to diagnostic errors. 6–8 …”

Section: Introductionmentioning

confidence: 99%

An electronic trigger based on care escalation to identify preventable adverse events in hospitalised patients

et al. 2017

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“…One of the potential strategies for minimising the frequency and impact of diagnostic errors includes training to improve clinicians' cognitive skills and their awareness of common biases and disease-specific pitfalls, providing a better infrastructure for learning from diagnostic outcomes and blame-free learning from errors that are identified, and processes to minimise the harmful impacts of diagnostic errors and delays [27]. Although the diagnostic discrepancy between the reason for admission and discharge diagnosis is not necessarily equal to diagnostic error, it can be used as an indicator or clinical criteria for screening diagnostic errors in the lack of prospective or autopsy-based studies [17].…”

Section: Discussionmentioning

confidence: 99%

Errors in diagnosis of infective endocarditis

2018

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Infective endocarditis (IE) is now the third or fourth most common life-threatening infectious disease. The high morbidity and mortality rates in the absence of appropriate care necessitate a thorough understanding of the obstacles towards the early diagnosis and management of IE. The aim of this study was to evaluate the frequency of discrepancy in diagnosis (i.e. discrepancy between the reason for admission and discharge diagnosis) and associated factors in patients with IE. It was a retrospective review of hospital records of all adult patients admitted in a 1000-bed academic general hospital in Mashhad, Iran with the discharge diagnosis of IE. Discrepancy in diagnosis on admission was observed in 64 (54.2%) of 118 episodes of IE. For patients with discrepant diagnosis, the odds of poor outcome were more than two times higher than the odds of those with the non-discrepant diagnosis. Multivariate analysis identified the only history of prosthetic valve replacement as an independent factor in predicting non-discrepant diagnosis. We suggest that in facing a patient with the complex clinical scenario, proposing a comprehensive clinical syndrome that includes predisposing factors instead of a symptom or finding-based diagnosis can help making the differential diagnosis more accurate.

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“…[7][8][9] The impact of how diagnoses change with time and across transitions of care is difficult to establish, particularly in large inpatient populations. [10][11][12][13] This is despite a renewed focus on diagnostic safety and efforts to minimize diagnostic error. 3 An important reason for this is the lack of time varying information in administrative datasets produced by hospitals.…”

Section: Introductionmentioning

confidence: 99%