Dataset Information

Long-term changes in computed tomography and ultrasound utilization in a pediatric emergency department.

ABSTRACT:

Objective

Many studies have proposed reducing unnecessary use of computed tomography (CT), and ongoing studies in pediatric populations are aiming to decrease radiation dosages whenever possible. We aimed to evaluate the long-term changes in the utilization patterns of CT and ultrasound (US) in pediatric emergency departments (PEDs).

Methods

This retrospective study reviewed the electronic medical data of patients who underwent CT and/or US in the PED of a tertiary referral hospital from 2000 to 2014. We compared the changes in utilization patterns of brain and abdominal CT scans in pediatric patients and analyzed changes in abdominal US utilization in the PED.

Results

During the study period, 196,371 patients visited the PED. A total of 12,996 brain and abdominal CT scans and 12,424 abdominal US were performed in the PED. Comparison of CT use in pediatric patients before and after 2007 showed statistically decreasing trends after 2007, expressed as the coefficient values of the differences in groups. The numbers of brain and abdominal CT scans showed a significant decreasing trend in children, except for abdominal CT in adolescents. The abdominal US/CT ratio in the PED showed a statistically significant increase (2.68; 95% confidence interval, 1.87 to 3.49) except for the adolescent group (5.82; 95% confidence interval, -2.06 to 13.69).

Conclusion

Overall, CT use in pediatric patients has decreased since 2007. Pediatric US use has also shown a decreasing trend; however, the abdominal US/CT ratio in pediatric patients showed an increasing trend, except for adolescents.

SUBMITTER: Chang I

PROVIDER: S-EPMC5891745 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Publications

Long-term changes in computed tomography and ultrasound utilization in a pediatric emergency department.

Chang Ikwan I Jung Jae Yun JY Kwak Young Ho YH Kim Do Kyun DK Lee Jin Hee JH Jung Jin Hee JH Kwon Hyuksool H Paek So Hyun SH Park Joong Wan JW

Clinical and experimental emergency medicine 20180131 1

<h4>Objective</h4>Many studies have proposed reducing unnecessary use of computed tomography (CT), and ongoing studies in pediatric populations are aiming to decrease radiation dosages whenever possible. We aimed to evaluate the long-term changes in the utilization patterns of CT and ultrasound (US) in pediatric emergency departments (PEDs).<h4>Methods</h4>This retrospective study reviewed the electronic medical data of patients who underwent CT and/or US in the PED of a tertiary referral hospit ...[more]

PMID: 29381908

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Project description:BackgroundDuring the coronavirus disease 2019 (COVID-19) pandemic period, the use of emergency services with pediatric non-COVID patients has decreased considerably. We aimed to examine whether there was a change in the demographic data, triage profile, causes, management, and cost of pediatric emergency department (PED) visits of non-COVID patients during the pandemic period.MethodsThis study was a retrospective, single-center, observational comparative study that was conducted at the PED. Patient records were examined during "the pandemic spring" and the same period of the previous year. Patient demographics, waiting time, and outcome of the PED visit were analyzed in the entire population of children admitted to the PED during the study period, whereas more precise data such as the reason for PED use, duration of symptoms, urgency levels according to the Emergency Severity Index (ESI), final diagnosis, management, and cost of patient care were analyzed in a sample of admitted patients. We used the chi-square test, Fisher's exact test, and Mann-Whitney U test for statistical analyses.ResultsA total of 62,593 PED visits occurred. During the pandemic period, PED visits showed a decrease of 55.8% compared to the previous year. Patients included in the sampling study group were selected using a systematic random sampling method. The median waiting time during the pandemic period was significantly shorter than the previous year (median 14 min [IQR: 5-32] vs. median 5 min [IQR: 2-16]; p<0.001). The median duration of symptoms was 1 day (1-2) in both groups. Emergency Severity Index (ESI) levels I, II, and III showed a significant increase (27.7% vs. 37.3%) in triage scoring compared to levels IV and V (72.3% vs. 62.7%) during the pandemic period (p<0.001). The median cost per patient during the pandemic period was statistically higher compared to the previous year ($19.57 [19.57-40.50] vs. $25.34 [31.50-52.01]; p<0.001). Overall costs during the pandemic period had a 1.6-fold decline.ConclusionWe highlighted the changes in an ordinary PED profile during an extraordinary period. A shift in ESI levels in a more emergent direction was observed. While the number of nonurgent patients, especially those with infections, decreased, the rates of surgical cases, acute neurological and heart diseases, home accidents, and poisoning increased relative to the pre-pandemic period.

Project description:BACKGROUND:Reliably abstracting outcomes from free-text electronic health records remains a challenge. While automated classification of free text has been a popular medical informatics topic, performance validation using real-world clinical data has been limited. The two main approaches are linguistic (natural language processing [NLP]) and statistical (machine learning). The authors have developed a hybrid system for abstracting computed tomography (CT) reports for specified outcomes. OBJECTIVES:The objective was to measure performance of a hybrid NLP and machine learning system for automated outcome classification of emergency department (ED) CT imaging reports. The hypothesis was that such a system is comparable to medical personnel doing the data abstraction. METHODS:A secondary analysis was performed on a prior diagnostic imaging study on 3,710 blunt facial trauma victims. Staff radiologists dictated CT reports as free text, which were then deidentified. A trained data abstractor manually coded the reference standard outcome of acute orbital fracture, with a random subset double-coded for reliability. The data set was randomly split evenly into training and testing sets. Training patient reports were used as input to the Medical Language Extraction and Encoding (MedLEE) NLP tool to create structured output containing standardized medical terms and modifiers for certainty and temporal status. Findings were filtered for low certainty and past/future modifiers and then combined with the manual reference standard to generate decision tree classifiers using data mining tools Waikato Environment for Knowledge Analysis (WEKA) 3.7.5 and Salford Predictive Miner 6.6. Performance of decision tree classifiers was evaluated on the testing set with or without NLP processing. RESULTS:The performance of machine learning alone was comparable to prior NLP studies (sensitivity = 0.92, specificity = 0.93, precision = 0.95, recall = 0.93, f-score = 0.94), and the combined use of NLP and machine learning showed further improvement (sensitivity = 0.93, specificity = 0.97, precision = 0.97, recall = 0.96, f-score = 0.97). This performance is similar to, or better than, that of medical personnel in previous studies. CONCLUSIONS:A hybrid NLP and machine learning automated classification system shows promise in coding free-text electronic clinical data.

Project description:Study objectiveReduced-dose computed tomography (CT) scans have been recommended for diagnosis of kidney stone but are rarely used in the emergency department (ED) setting. Test characteristics are incompletely characterized, particularly in obese patients. Our primary outcome is to determine the sensitivity and specificity of a reduced-dose CT protocol for symptomatic ureteral stones, particularly those large enough to require intervention, using a protocol stratified by patient size.MethodsThis was a prospective, blinded observational study of 201 patients at an academic medical center. Consenting subjects underwent both regular- and reduced-dose CT, stratified into a high and low body mass index (BMI) protocol based on effective abdominal diameter. Reduced-dose CT scans were interpreted by radiologists blinded to regular-dose interpretations. Follow-up for outcome and intervention was performed at 90 days.ResultsCT scans with both regular and reduced doses were conducted for 201 patients, with 63% receiving the high BMI reduced-dose protocol. Ureteral stone was identified in 102 patients (50.7%) of those receiving regular-dose CT, with a ureteral stone greater than 5 mm identified in 26 subjects (12.9%). Sensitivity of the reduced-dose CT for any ureteral stone was 90.2% (95% confidence interval [CI] 82.3% to 95.0%), with a specificity of 99.0% (95% CI 93.7% to 100.0%). For stones greater than 5 mm, sensitivity was 100% (95% CI 85.0% to 100.0%). Reduced-dose CT identified 96% of patients who required intervention for ureteral stone within 90 days. Mean reduction in size-specific dose estimate was 18.6 milligray (mGy), from 21.7 mGy (SD 9.7) to 3.4 mGy (SD 0.9).ConclusionCT with substantial dose reduction was 90.2% (95% CI 82.3% to 95.0%) sensitive and 98.9% (95% CI 85.0% to 100.0%) specific for ureteral stones in ED patients with a wide range of BMIs. Reduced-dose CT was 96.0% (95% CI 80.5% to 99.3%) sensitive for ureteral stones requiring intervention within 90 days.

Dataset Information

Long-term changes in computed tomography and ultrasound utilization in a pediatric emergency department.

Objective

Methods

Results

Conclusion

Publications

Long-term changes in computed tomography and ultrasound utilization in a pediatric emergency department.

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