Annals of emergency medicine
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Comment Multicenter Study Clinical Trial
Identifying children at very low risk of clinically important blunt abdominal injuries.
We derive a prediction rule to identify children at very low risk for intra-abdominal injuries undergoing acute intervention and for whom computed tomography (CT) could be obviated. ⋯ A prediction rule consisting of 7 patient history and physical examination findings, and without laboratory or ultrasonographic information, identifies children with blunt torso trauma who are at very low risk for intra-abdominal injury undergoing acute intervention. These findings require external validation before implementation.
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There is widespread concern about patients with frequent emergency department (ED) use. We identify sociodemographic and clinical factors most strongly associated with frequent ED use within the Veterans Health Administration (VHA) nationally. ⋯ Frequent ED use occurs even in a coordinated health care system that provides ready access to outpatient care. Frequent ED users are characterized by traits that represent high levels of psychosocial and medical needs. The correlates we identified for frequent ED use were consistent across multiple distinct levels of ED use.
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Multicenter Study Comparative Study Clinical Trial
Poor sensitivity of a modified Alvarado score in adults with suspected appendicitis.
A clinical decision rule that identifies patients at low risk for appendicitis may reduce the reliance on computed tomography (CT) for diagnosis. We seek to prospectively evaluate the accuracy of a low modified Alvarado score in emergency department (ED) patients with suspected appendicitis and compare the score to clinical judgment. We hypothesize that a low modified Alvarado score will have a sufficiently high sensitivity to rule out acute appendicitis. ⋯ With a sensitivity of 72%, a low modified Alvarado score is less sensitive than clinical judgment in excluding acute appendicitis.
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As use of radiology studies increases, there is a concurrent increase in incidental findings (eg, lung nodules) for which the radiologist issues recommendations for additional imaging for follow-up. Busy emergency physicians may be challenged to carefully communicate recommendations for additional imaging not relevant to the patient's primary evaluation. The emergence of electronic health records and natural language processing algorithms may help address this quality gap. We seek to describe recommendations for additional imaging from our institution and develop and validate an automated natural language processing algorithm to reliably identify recommendations for additional imaging. ⋯ Recommendations for additional imaging are common, and failure to document relevant recommendations for additional imaging in ED discharge instructions occurs frequently. The natural language processing algorithm's performance improved with each iteration and offers a promising error-prevention tool.