Unscheduled returns to the emergency department: an outcome of medical errors?

Núñez, Salvador

doi:10.1136/qshc.2005.016618

Cited by 131 publications

(140 citation statements)

References 24 publications

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“…Although not an internationally accepted rule, lower than 1% is considered as an acceptable figure (13). Readmision within 24 hours is one of the standard quality indicators to be monitored in Turkey.…”

Section: Quality Measurement In Emergency Departmentmentioning

confidence: 99%

Emergency Department Care Survey

Bektemür¹,

Osmanbeyoglu²,

Cander³

2015

EAJEM

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Section: Quality Measurement In Emergency Departmentmentioning

confidence: 99%

Emergency Department Care Survey

Bektemür¹,

Osmanbeyoglu²,

Cander³

2015

EAJEM

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Section: Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…By applying these screens to ambulatory EHRs they increased the prevalence of cases of error from 2.1% at baseline to 5.4%-20.9% in groups using screening triggers such as an unexpected return visit or hospitalization. In the Emergency Department (ED) context, return visits within 7 days had a rate of 5.7% adverse events, with 1.6% having adverse events from diagnostic errors [10], and about 20% of unscheduled returns had diagnostic errors [15].One powerful and underutilized capability of electronic records is the capacity to rearrange information to cognitively support the process of assessing content in medical records. By optimizing display of longitudinal data, the EHR can be used facilitate comparison of "upstream" diagnostic assessments with "downstream" diagnostic outcomes [16,17].…”

mentioning

confidence: 99%

“…For the patient subset with any other EHR notes within the preceding 14 days of a sentinel ED visit, here defined as the ED visit within the specified period that triggered the case being pulled into our database, we imported all notes from 14 days before and 30 days afterwards into a Microsoft Access (Microsoft Corporation, Redmond, WA) database. The ED population was chosen due to our involvement in ongoing quality improvement efforts within that department, and due to a perception that diagnostic errors are an important problem in this clinical area [10,15].The database had a customized visual display to allow simultaneous comparison of the sentinel ED visit note to any other EHR notes within the specified range (▶Figure 1). This tool was designed to enable the reviewing clinician to efficiently examine diagnostic assessments and outcomes from preceding visits, the sentinel ED visit, and any subsequent notes.…”

mentioning

confidence: 99%

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Use of an Expedited Review Tool to Screen for Prior Diagnostic Error in Emergency Department Patients

2015

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KeywordsMonitoring and surveillance, error management and prevention, emergency and disaster care, data processing, human-computer inter action, diagnostic error SummaryObjective: Missed diagnoses are an important area of care quality resulting in significant morbidity and mortality. Determination of rates and causes has been limited by difficulties in screening, including the effort of manual chart review. We developed and tested a semi-automated review tool to expedite screening for diagnostic errors in an electronic health record (EHR). Methods: We retrospectively reviewed patients seen in the emergency department (ED) of a teaching hospital over 31 days, using an automated screen to identify those with a prior in-system visit during the 14 days preceding their ED visit. We collected prior and subsequent notes from the institution's EHR for these cases, then populated a specially designed relational database enabling rapid comparison of prior visit records to the sentinel ED visit. Each case was assessed for potential missed or delayed diagnosis, and rated by likelihood as "definite, probable, possible, unlikely or none." Results: A total of 5 066 patient encounters were screened by a clinician using the tool, of which 1 498 (30%) had a clinical encounter within the preceding 14 days. Of these, 37 encounters (2.6% of those reviewed) were "definite" or "probable" missed diagnoses. The rapid review tool took a mean of 1.9 minutes per case for primary review, compared with 11.2 minutes per case for reviews without the automated tool. Conclusions: Diagnostic errors were present in a significant number of cases presenting to the ED after recent healthcare visits. An innovative review tool enabled a substantially increased efficiency in screening for diagnostic errors. BackgroundMissed or delayed diagnoses are an important area of medical error that result in significant morbidity and mortality [1,2], and identifying and decreasing the rate of diagnostic error represents a major unmet quality improvement need. Claims for misdiagnosis are the leading cause of malpractice cases [3][4][5][6][7], but determining their true incidence remains difficult for multiple reasons. These include lack of agreement on definitions for diagnostic errors, or even whether these should be described more neutrally, as in "diagnostic discrepancies"; the subjective nature of determining whether a diagnosis could and should have been made earlier, with significant concerns regarding hindsight and outcome bias [8]; poor feedback systems, where diagnoses made in one encounter frequently are not connected to prior or future patient outcomes; the insensitivity of traditional approaches such as random case review, autopsy review, and malpractice claims in finding diagnostic error; and the typically time-intensive process of reviewing patient charts to identify diagnosis errors or delays [9]. This last barrier limits the extensive review of records in research, with one study of diagnostic errors reporting a mean review time of 1.4 hours per re...

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Identifying Diagnostic Errors in Primary Care Using an Electronic Screening Algorithm

et al. 2007

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Background: Diagnostic errors are the leading basis for malpractice claims in primary care, yet these errors are underidentified and understudied. Computerized methods used to screen for other types of errors (eg, medication related) have not been applied to diagnostic errors. Our objectives were to assess the feasibility of computerized screening to identify diagnostic errors in primary care and to categorize diagnostic breakdowns using a recently published taxonomy. Methods: We used an algorithm to screen the electronic medical records of patients at a single hospital that is part of a closed health care system. A Structured Query Language-based program detected the presence of 1 of 2 mutually exclusive electronic screening criteria: screen 1, a primary care visit (index visit) followed by a hospitalization in the next 10 days; or screen 2, an index visit followed by 1 or more primary care, urgent care, or emergency department visits within 10 days. Two independent, blinded reviewers determined the presence or absence of diagnostic error through medical record review of visits with positive and negative screening results. Results: Among screen 1 and 2 positive visits, 16.1% and 9.4%, respectively, were associated with a diagnostic error. The error rate was 4% in control cases that met neither screening criterion. The most common primary errors in the diagnostic process were failure or delay in eliciting information and misinterpretation or suboptimal weighing of critical pieces of data from the history and physical examination. The most common secondary errors were suboptimal weighing or prioritizing of diagnostic probabilities and failure to recognize urgency of illness or its complications. Conclusions: Electronic screening has potential to identify records that may contain diagnostic errors in primary care, and its performance is comparable to screening tools for other types of errors. Future studies that validate these findings in other settings could provide improvement initiatives in this area.

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Unscheduled returns to the emergency department: an outcome of medical errors?

Cited by 131 publications

References 24 publications

Emergency Department Care Survey

Emergency Department Care Survey

Use of an Expedited Review Tool to Screen for Prior Diagnostic Error in Emergency Department Patients

Identifying Diagnostic Errors in Primary Care Using an Electronic Screening Algorithm

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