Effects of precompression on elasticity imaging of the breast: development of a clinically useful semiquantitative method of precompression assessment.
Adult; Female; Humans; Middle Aged; Young Adult; Ultrasonography; Sensitivity and Specificity; Breast Neoplasms/*diagnostic imaging; Reproducibility of Results; Elasticity Imaging Techniques/*methods; *Algorithms; Artifacts; Image Enhancement/methods; Palpation/*methods; Image Interpretation; Mammary/*methods; Computer-Assisted/*methods
OBJECTIVES: Elastography of the breast is a new technique for characterization of breast lesions. The reproducibility of elastographic techniques has been questioned. Precompression is known to effect elastographic results. This study determined the effect of precompression on clinical images and proposes a method to semiquantify the amount of precompression applied. METHODS: Ten patients with different breast tissue types were evaluated with shear wave and strain elastography with varying amounts of precompression. The changes in the shear wave speed and images were documented. A semiquantitative method for determining the amount of precompression applied is presented. The reproducibility of the technique was determine by repeated measurements by 3 sonographers. RESULTS: Precompression substantially changes the elastographic results of patient images on both strain and shear wave elastography. Fat can have the same elasticity as cancer with clinically possible amounts of precompression. The proposed method for determining the amount of precompression applied has variability of less than 10%, which is within the error of the technique and would not affect clinical results. Four zones of precompression are identified, which are useful for explaining the effects of precompression on both strain and shear wave imaging. CONCLUSIONS: Precompression is a substantial factor in obtaining accurate results with elastography. A proposed simple, easily applied technique can be used to semiquantify the amount of precompression applied. Precompression should be minimized in obtaining breast clinical images.
Barr Richard G; Zhang Zheng
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
2012
2012-06
Article information provided for research and reference use only. All rights are retained by the journal listed under publisher and/or the creator(s).
<a href="http://doi.org/10.7863/jum.2012.31.6.895" target="_blank" rel="noreferrer noopener">10.7863/jum.2012.31.6.895</a>
Automated identification of antibiotic overdoses and adverse drug events via analysis of prescribing alerts and medication administration records.
*Algorithms; *Medical Order Entry Systems; Adolescence; Adolescent; adverse drug event; Adverse Drug Event – Prevention and Control; Age Distribution; Algorithms; Anti-Bacterial Agents/*administration & dosage/adverse effects; Antibiotics – Administration and Dosage; Antibiotics – Adverse Effects; Child; clinical; Clinical; Computer Assisted; Computer-Assisted; CPOE; decision support systems; Decision Support Systems; Demography; Drug Overdose/diagnosis/*prevention & control; Drug Therapy; Drug-Related Side Effects and Adverse Reactions/*prevention & control; electronic health record; Electronic Health Records; electronic medical record; Electronic Order Entry; Female; Funding Source; Hospitals; Humans; Infant; Male; medical order entry system; Medication Errors – Prevention and Control; Medication Errors – Statistics and Numerical Data; Medication Errors/*prevention & control/statistics & numerical data; Newborn; Overdose – Diagnosis; Overdose – Prevention and Control; patient safety; Pediatric; Preschool; risk management; Young Adult
Objectives: Electronic trigger detection tools hold promise to reduce Adverse drug event (ADEs) through efficiencies of scale and real-time reporting. We hypothesized that such a tool could automatically detect medication dosing errors as well as manage and evaluate dosing rule modifications. Materials and Methods: We created an order and alert analysis system that identified antibiotic medication orders and evaluated user response to dosing alerts. Orders associated with overridden alerts were examined for evidence of administration and the delivered dose was compared to pharmacy-derived dosing rules to confirm true overdoses. True overdose cases were reviewed for association with known ADEs. Results: Of 55 546 orders reviewed, 539 were true overdose orders, which lead to 1965 known overdose administrations. Documentation of loose stools and diarrhea was significantly increased following drug administration in the overdose group. Dosing rule thresholds were altered to reflect clinically accurate dosing. These rule changes decreased overall alert burden and improved the salience of alerts. Discussion: Electronic algorithm-based detection systems can identify antibiotic overdoses that are clinically relevant and are associated with known ADEs. The system also serves as a platform for evaluating the effects of modifying electronic dosing rules. These modifications lead to decreased alert burden and improvements in response to decision support alerts. Conclusion: The success of this test case suggests that gains are possible in reducing medication errors and improving patient safety with automated algorithm-based detection systems. Follow-up studies will determine if the positive effects of the system persist and if these changes lead to improved safety outcomes.
Kirkendall Eric S; Kouril Michal; Dexheimer Judith W; Courter Joshua D; Hagedorn Philip; Szczesniak Rhonda; Li Dan; Damania Rahul; Minich Thomas; Spooner S Andrew
Journal of the American Medical Informatics Association : JAMIA
2017
2017-03
Article information provided for research and reference use only. All rights are retained by the journal listed under publisher and/or the creator(s).
<a href="http://doi.org/10.1093/jamia/ocw086" target="_blank" rel="noreferrer noopener">10.1093/jamia/ocw086</a>
Simple Triage Algorithm and Rapid Treatment and Sort, Assess, Lifesaving, Interventions, Treatment, and Transportation mass casualty triage methods for sensitivity, specificity, and predictive values.
*Algorithms; *Emergency Service; *Mass Casualty Incidents; *Triage; 80 and over; 80 and Over; Adolescence; Adolescent; Adult; Aged; Algorithms; Emergency Service; Female; Hospital; Humans; Male; Mass Casualty Incidents; Middle Age; Middle Aged; Pilot Projects; Pilot Studies; Predictive Value of Tests; Retrospective Design; Retrospective Studies; Scales; Triage; Wounds and Injuries – Diagnosis; Wounds and Injuries – Mortality; Wounds and Injuries – Therapy; Wounds and Injuries/*diagnosis/mortality/therapy; Young Adult
OBJECTIVE: Two common mass casualty triage algorithms are Simple Triage Algorithm and Rapid Treatment (START) and Sort, Assess, Lifesaving, Interventions, Treatment, and Transportation (SALT). We sought to determine the START and SALT efficacy in predicting clinical outcome by appropriate triage. METHODS: We performed a retrospective chart review of trauma registry of patients from our emergency department (ED). We applied the triage algorithms to 100 patient charts. The end points categories were defined by patient outcomes and the need for intervention: minor/green, discharged without intervention other than minor ED procedure; delayed/yellow, patients get an intervention more than 12 hours after arrival to the ED; immediate/red, patients get an intervention less than 12 hours after arrival; dead/expectant/black, patients die within 48 hours after arrival. RESULTS: The mean age was 47 years (range, 17-92 years), and 72% were male. The mechanism of injury was 41% motor vehicle collision, 32% fall, and 16% penetrating trauma. Hospital outcome was 60% minor/green, 5% delayed/yellow, 29% immediate/red, and 6% dead/black. The SALT method resulted in 5 patients overtriaged (95% confidence interval [CI], 1.6-11.2), 30 undertriaged (95% CI, 21.2-40), and 65 met triage level (95% CI, 54.8-74.3). The START method resulted in 12 overtriage (95% CI, 6.4-20), 33 undertriaged (95% CI, 23.9-43.1), and 55 at triage level (95% CI, 44.7-65). Within triage levels, sensitivity ranged from 0% to 92%, specificity from 55% to 100%, positive predictive values from 10% to 100%, and negative predictive value from 65% to 97%. CONCLUSION: Overall, neither SALT nor START was sensitive or specific for predicting clinical outcome.
Bhalla Mary Colleen; Frey Jennifer; Rider Cody; Nord Michael; Hegerhorst Mitch
The American journal of emergency medicine
2015
2015-11
Article information provided for research and reference use only. All rights are retained by the journal listed under publisher and/or the creator(s).
<a href="http://doi.org/10.1016/j.ajem.2015.08.021" target="_blank" rel="noreferrer noopener">10.1016/j.ajem.2015.08.021</a>