Introduction: This study reviews malpractice, also called medical professional liability (MPL), claims involving adult patients cared for in emergency departments (ED) and urgent care settings.

Methods: We conducted a retrospective review of closed MPL claims of adults over 18 years, from the Medical Professional Liability Association’s Data Sharing Project database from 2001–2015, identifying 6,779 closed claims. Data included the total amount, origin, top medical specialties named, chief medical factors, top medical conditions, severity of injury, resolution, average indemnity, and defense costs of closed claims.

Results: Of 6,779 closed claims, 65.9% were dropped, withdrawn, or dismissed. Another 22.8% of claims settled for an average indemnity of $297,709. Of the 515 (7.6%) cases that went to trial, juries returned verdicts for the defendant in 92.6% of cases (477/515). The remaining 7.4% of cases (38/515) were jury verdicts for the plaintiff, with an average indemnity of $816,909. The most common resulting medical condition cited in paid claims was cardiac or cardiorespiratory arrest (10.4%). Error in diagnosis was the most common chief medical error cited in closed claims. Death was the most common level of severity listed in closed (38.5%) and paid (42.8%) claims. Claims reporting major permanent injury had the highest paid-to-closed ratio, and those reporting grave injury had the highest average indemnity of $686,239.

Conclusion: This retrospective review updates the body of knowledge surrounding medical professional liability and represents the most recent analysis of claims in emergency medicine. As the majority of emergency providers will be named in a MPL claim during their career, it is essential to have a better understanding of the most common factors resulting in MPL claims.

Introduction: We sought to validate a handheld, near-infrared spectroscopy (NIRS) device for detecting intracranial hematomas in children with head injury.

Methods: Eligible patients were those <18 years old who were admitted to the emergency department at three academic children’s hospitals with head trauma and who received a clinically indicated head computed tomography (HCT). Measurements were obtained by a blinded operator in bilateral frontal, temporal, parietal, and occipital regions. Qualifying hematomas were a priori determined to be within the brain scanner’s detection limits of >3.5 milliliters in volume and <2.5 centimeters from the surface of the brain. The device’s measurements were positive if the difference in optical density between hemispheres was >0.2 on three successive scans. We calculated diagnostic performance measures with corresponding exact two-sided 95% Clopper-Pearson confidence intervals (CI). Hypothesis test evaluated whether predictive performance exceeded chance agreement (predictive Youden’s index > 0).

Results: A total of 464 patients were enrolled and 344 met inclusion for primary data analysis: 10.5% (36/344) had evidence of a hematoma on HCT, and 4.7% (16/344) had qualifying hematomas. The handheld brain scanner demonstrated a sensitivity of 58.3% (21/36) and specificity of 67.9% (209/308) for hematomas of any size. For qualifying hematomas the scanner was designed to detect, sensitivity was 81% (13/16) and specificity was 67.4% (221/328). Predictive performance exceeded chance agreement with a predictive Youden’s index of 0.11 (95% CI, 0.10 – 0.15; P < 0.001) for all hematomas, and 0.09 (95% CI, 0.08 – 0.12; P < 0.001) for qualifying hematomas.

Conclusion: The handheld brain scanner can non-invasively detect a subset of intracranial hematomas in children and may serve an adjunctive role to head-injury neuroimaging decision rules that predict the risk of clinically significant intracranial pathology after head trauma.

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