Laughlin, Michael J.

AbstractBackgroundGiven that abdominal aorta is a retroperitoneal structure, increased body mass index (BMI) may have an adverse effect upon the quality of aortic ultrasonographic imaging.PurposeTo assess the hypothesis that increased BMI is associated with worsening point‐of‐care abdominal aortic ultrasonographic image quality.MethodsThis is a retrospective single‐center study of point‐of‐care abdominal aortic ultrasound examinations performed in an academic emergency department (ED) with fellowship‐trained emergency ultrasonography faculty performing quality assurance review.ResultsMean ± SD BMI was 27.4 ± 6.2, among the 221 included records. The overall quality rating decreased as BMI increased (correlation coefficient − 0.24; P < .001) and this persisted after adjustment for age and sex (P < .001). Although BMI was higher on average in the records that were of insufficient quality for clinical decisions when compared with those of sufficient quality (mean BMI 28.7 vs 27.0), this did not reach statistical significance in a univariable setting (P = .11) or after adjusting for age and sex (P = .14).ConclusionThis study data shows a decrease in point‐of‐care abdominal aorta ultrasound imaging quality as BMI increases, though this difference did not result in a statistically significant impairment in achieving the minimum quality for clinical decisions. This finding may help ameliorate some clinician concerns about ultrasonography for patients with high BMI.

AbstractBackgroundMany clinicians believe that a patient's body mass index (BMI) affects the likelihood of obtaining high quality ultrasound images.ObjectivesTo assess the hypothesis that increased BMI is associated with worsening focused assessment with sonography in trauma (FAST) image quality.MethodsWe conducted a retrospective single‐center study of FAST examinations performed in a large academic emergency department (ED) with fellowship‐trained emergency ultrasonography faculty performing quality assurance review.ResultsMean (SD) BMI was 28.0 (6.6) among the 302 included studies. The overall quality rating tended to decrease as BMI increased but did not achieve statistical significance in a univariable setting (P = .06) or after adjustment for age and sex (P = .06). Operators perception of image adequacy was largely unaffected by BMI, with the exception of the pericardial view.ConclusionThis study did not identify a statistically significant difference in FAST quality with increased BMI. This result may help assuage clinician concerns about ultrasonography for patients in the ED.

Common approaches to emergency department (ED) staffing are to optimize shifts based on historical patient volume or arrival patterns. The former is problematic because historical patient volumes are based on the volumes during existing shifts. Therefore, optimizing shifts based on these volumes can replicate the inefficiencies in these shifts. The latter approach ignores queueing effects. To address the shortcomings of these commonly used approaches, we use classification and regression trees to identify thresholds for patient-to-staff ratios, which split the patient subpopulations into two groups that have different empirical cumulative distribution functions (ecdfs) for patients’ lengths of stay in the ED; one has an extended length and the other has a shorter length. We apply these thresholds and ecdfs to historical patient volumes to calculate an ideal patient volume. After accounting for arrival patterns of ED patients, ideal patient volumes represent the load on the entire ED if patient-to-staff ratios are always kept under the identified thresholds. We then use a mixed-integer programming model to minimize understaffing with respect to the ideal patient volumes. The ED at Mayo Clinic Saint Marys Hospital in Rochester, Minnesota, a trauma center for both adults and pediatrics, implemented the new shift templates in the fourth quarter of 2015. The templates resulted in statistically significant improvements in several patient-centered metrics. In particular, the median length of stay, door-to-provider time, and door-to-bed time decreased by 11, 2.7, and 3 minutes, respectively, despite a six percent increase in patient volume.