Dataset Information

Validation of chief complaints, medical history, medications, and physician diagnoses structured with an integrated emergency department information system in Japan: the Next Stage ER system.

ABSTRACT: Aim:Emergency department information systems (EDIS) facilitate free-text data use for clinical research; however, no study has validated whether the Next Stage ER system (NSER), an EDIS used in Japan, accurately translates electronic medical records (EMRs) into structured data. Methods:This is a retrospective cohort study using data from the emergency department (ED) of a tertiary care hospital from 2018 to 2019. We used EMRs of 500 random samples from 27,000 ED visits during the study period. Through the NSER system, chief complaints were translated into 231 chief complaint categories based on the Japan Triage and Acuity Scale. Medical history and physician's diagnoses were encoded using the International Classification of Diseases, 10th Revision; medications were encoded as Anatomical Therapeutic Chemical Classification System codes. Two reviewers independently reviewed 20 items (e.g., presence of fever) for each study component (e.g., chief complaints). We calculated association measures of the structured data by the NSER system, using the chart review results as the gold standard. Results:Sensitivities were very high (>90%) in 17 chief complaints. Positive predictive values were high for 14 chief complaints (?80%). Negative predictive values were ?96% for all chief complaints. For medical history and medications, most of the association measures were very high (>90%). For physicians' ED diagnoses, sensitivities were very high (>93%) in 16 diagnoses; specificities and negative predictive values were very high (>97%). Conclusions:Chief complaints, medical history, medications, and physician's ED diagnoses in EMRs were well-translated into existing categories or coding by the NSER system.

SUBMITTER: Goto T

PROVIDER: S-EPMC7453131 | biostudies-literature | 2020 Jan-Dec

REPOSITORIES: biostudies-literature

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Validation of chief complaints, medical history, medications, and physician diagnoses structured with an integrated emergency department information system in Japan: the Next Stage ER system.

Goto Tadahiro T Hara Konan K Hashimoto Katsuhiko K Soeno Shoko S Shirakawa Toru T Sonoo Tomohiro T Nakamura Kensuke K

Acute medicine & surgery 20200101 1

<h4>Aim</h4>Emergency department information systems (EDIS) facilitate free-text data use for clinical research; however, no study has validated whether the Next Stage ER system (NSER), an EDIS used in Japan, accurately translates electronic medical records (EMRs) into structured data.<h4>Methods</h4>This is a retrospective cohort study using data from the emergency department (ED) of a tertiary care hospital from 2018 to 2019. We used EMRs of 500 random samples from 27,000 ED visits during the ...[more]

PMID: 32884825

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Project description:Objective:We learn contextual embeddings for emergency department (ED) chief complaints using Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art language model, to derive a compact and computationally useful representation for free-text chief complaints. Materials and methods:Retrospective data on 2.1 million adult and pediatric ED visits was obtained from a large healthcare system covering the period of March 2013 to July 2019. A total of 355 497 (16.4%) visits from 65 737 (8.9%) patients were removed for absence of either a structured or unstructured chief complaint. To ensure adequate training set size, chief complaint labels that comprised less than 0.01%, or 1 in 10 000, of all visits were excluded. The cutoff threshold was incremented on a log scale to create seven datasets of decreasing sparsity. The classification task was to predict the provider-assigned label from the free-text chief complaint using BERT, with Long Short-Term Memory (LSTM) and Embeddings from Language Models (ELMo) as baselines. Performance was measured as the Top-k accuracy from k?=?1:5 on a hold-out test set comprising 5% of the samples. The embedding for each free-text chief complaint was extracted as the final 768-dimensional layer of the BERT model and visualized using t-distributed stochastic neighbor embedding (t-SNE). Results:The models achieved increasing performance with datasets of decreasing sparsity, with BERT outperforming both LSTM and ELMo. The BERT model yielded Top-1 accuracies of 0.65 and 0.69, Top-3 accuracies of 0.87 and 0.90, and Top-5 accuracies of 0.92 and 0.94 on datasets comprised of 434 and 188 labels, respectively. Visualization using t-SNE mapped the learned embeddings in a clinically meaningful way, with related concepts embedded close to each other and broader types of chief complaints clustered together. Discussion:Despite the inherent noise in the chief complaint label space, the model was able to learn a rich representation of chief complaints and generate reasonable predictions of their labels. The learned embeddings accurately predict provider-assigned chief complaint labels and map semantically similar chief complaints to nearby points in vector space. Conclusion:Such a model may be used to automatically map free-text chief complaints to structured fields and to assist the development of a standardized, data-driven ontology of chief complaints for healthcare institutions.

Project description:IntroductionKnowledge about the relationship between symptoms, diagnoses, and mortality in emergency department (ED) patients is essential for the emergency physician to optimize treatment, monitoring, and flow. In this study, we investigated the association between symptoms and discharge diagnoses; symptoms and mortality; and we then analyzed whether the association between symptoms and mortality was influenced by other risk factors.MethodsThis was a population-based, multicenter cohort study of all non-trauma ED patients ≥18 years who presented at a hospital in the Region of Southern Denmark between January 1, 2016-March 20, 2018. We used multivariable logistic regression to examine the association between symptoms and mortality adjusted for other risk factors.ResultsWe included 223,612 ED visits with a median patient age of 63 and even distribution of females and males. The frequency of the chief complaints at presentation were as follows: non-specific symptoms (19%); abdominal pain (16%); dyspnea (12%); fever (8%); chest pain (8%); and neurologic complaints (7%). Discharge diagnoses were symptom-based (24%), observational (hospital visit for observation or examination, 17%), circulatory (12%), or respiratory (12%). The overall 30-day mortality was 3.5%, with 1.7% dead within 0-7 days and 1.8% within 8-30 days. The presenting symptom was associated with mortality at 0-7 days but not with mortality at 8-30 days. Patients whose charts were missing documentation of symptoms (adjusted odds ratio [aOR] 3.5) and dyspneic patients (aOR 2.4) had the highest mortality at 0-7 days across patients with different primary symptoms. Patients ≥80 years and patients with a higher degree of comorbidity had increased mortality from 0-7 days to 8-30 days (aOR from 24.0 to 42.7 and 1.9 to 2.8, respectively).ConclusionShort-term mortality was more strongly associated with patient-related factors than with the primary presenting symptom at arrival to the hospital.

Project description:ObjectivesVeteran persons living with dementia (PLWDs) have high acute care utilization. We aim to understand why PLWDs seek care in the emergency department (ED) and how their utilization differs from older Veterans with no dementia diagnosis. We demonstrate the use of a novel national chief complaint data set in the Veteran Affairs Health Care System.MethodsThis was a retrospective observational study of ED users 65 years or older as of FY2017. The primary outcome is presence of one or more ED visits in FYs 2017-2018 using a logistic regression model controlling for dementia and other variables. Secondary outcomes include counts of ED visits by disposition, Emergency Severity Index, chief complaints defined by a natural language processing program, and ED encounter diagnoses defined by primary International Statistical Classification of Diseases, Tenth Revision (ICD-10-CM) code.ResultsOur cohort of Veterans comprised 3,115,263 patients. Of those, 255,372 (8.2%) had a diagnosis of dementia. Logistic regression modeling demonstrated that dementia is a significant predictor of ED use (p < 0.0001), with PLWDs more likely to have an ED visit (odds ratio 1.96, 95% confidence interval 1.94-1.98). PLWDs were admitted at higher rates when accounting for age and acuity. Chief complaints that were more common among PLWDs included falls (6.7% dementia vs. 3.3% without dementia), weakness (3.6% vs. 2.2%), and abnormal mental state (2.2% vs. 0.4%). ICD-10-CM codes were largely similar between the two groups.ConclusionsOur results reinforce that the ED is a common access point for Veterans with dementia. These patients require special consideration as they are more likely to visit the ED and be admitted. Our use of a novel national chief complaint data set suggests that they more commonly present with certain geriatric syndromes and nonspecific complaints. Further work is needed to determine whether these would warrant targeted interventions to improve quality of acute care.

Project description:Introduction: Black and Hispanic patients are frequently assigned lower acuity triage scores than White patients. This can lead to longer wait times, less aggressive care, and worse outcomes. In this study we aimed to determine whether these effects are more pronounced for patients with subjective complaints. Methods: We performed a retrospective analysis for all adult visits between 2016-2019 at an urban academic emergency department (ED) with acuity-based pods. We determined rates of initial high-acuity triage both across all patients and among the subset located in the high-acuity pod at time of disposition (either through initial assignment or subsequent up-triage). Analysis was performed for common chief complaints categorized as subjective (chest pain, dyspnea, any pain); observed (altered mental status); numeric (fever, hypotension); or protocolized (stroke, ST-elevation myocardial infarction). We constructed logistic regression models to control for age, race, gender, method of arrival, and final disposition. Results: We analyzed 297,355 adult ED visits. Black and Hispanic patients were less likely to be triaged to high-acuity beds (adjusted odds ratio [aOR] 0.76, 95% confidence interval [CI] 0.73-0.79 for Black, and aOR 0.87, 95% CI 0.84-0.90 for Hispanic patients). This effect was more pronounced for those with subjective chief complaints, including chest pain (aOR 0.76, 95% CI 0.73-0.79 for Black and 0.88, 95% CI 0.78-0.99 for Hispanic patients), dyspnea (aOR 0.79, 95% CI 0.68-0.92 and 0.8, 95% CI 0.72-0.99), and any pain (aOR 0.83, 95% CI 0.75-0.92 and 0.89, 95% CI 0.82-0.97, respectively). Among patients in the high-acuity pod at time of disposition, Black and Hispanic patients were disproportionately triaged to lower acuity pods on arrival (aOR 1.47, 95% CI 1.33-1.63 for Black and aOR 1.27, 95% CI 1.15-1.40 for Hispanic adults), with significant differences observed only for subjective chief complaints. No differences were observed for observed, objective, or protocolized complaints in either analysis. Conclusion: Black and Hispanic adults, including those who ultimately required high-acuity resources, were disproportionately triaged to lower acuity pods. This effect was more pronounced for patients with subjective chief complaints. Additional work is needed to identify and overcome potential bias in the assessment of patients with subjective chief complaints in ED triage.

Project description:With the continuing coronavirus disease 2019 (COVID-19) pandemic coupled with phased reopening, it is critical to identify risk factors associated with susceptibility and severity of disease in a diverse population to help shape government policies, guide clinical decision making, and prioritize future COVID-19 research. In this retrospective case-control study, we used de-identified electronic health records (EHR) from the University of California Los Angeles (UCLA) Health System between March 9th, 2020 and June 14th, 2020 to identify risk factors for COVID-19 susceptibility (severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) PCR test positive), inpatient admission, and severe outcomes (treatment in an intensive care unit or intubation). Of the 26,602 individuals tested by PCR for SARS-CoV-2, 992 were COVID-19 positive (3.7% of Tested), 220 were admitted in the hospital (22% of COVID-19 positive), and 77 had a severe outcome (35% of Inpatient). Consistent with previous studies, males and individuals older than 65 years old had increased risk of inpatient admission. Notably, individuals self-identifying as Hispanic or Latino constituted an increasing percentage of COVID-19 patients as disease severity escalated, comprising 24% of those testing positive, but 40% of those with a severe outcome, a disparity that remained after correcting for medical comorbidities. Cardiovascular disease, hypertension, and renal disease were premorbid risk factors present before SARS-CoV-2 PCR testing associated with COVID-19 susceptibility. Less well-established risk factors for COVID-19 susceptibility included pre-existing dementia (odds ratio (OR) 5.2 [3.2-8.3], p=2.6 x 10-10), mental health conditions (depression OR 2.1 [1.6-2.8], p=1.1 x 10-6) and vitamin D deficiency (OR 1.8 [1.4-2.2], p=5.7 x 10-6). Renal diseases including end-stage renal disease and anemia due to chronic renal disease were the predominant premorbid risk factors for COVID-19 inpatient admission. Other less established risk factors for COVID-19 inpatient admission included previous renal transplant (OR 9.7 [2.8-39], p=3.2x10-4) and disorders of the immune system (OR 6.0 [2.3, 16], p=2.7x10-4). Prior use of oral steroid medications was associated with decreased COVID-19 positive testing risk (OR 0.61 [0.45, 0.81], p=4.3x10-4), but increased inpatient admission risk (OR 4.5 [2.3, 8.9], p=1.8x10-5). We did not observe that prior use of angiotensin converting enzyme inhibitors or angiotensin receptor blockers increased the risk of testing positive for SARS-CoV-2, being admitted to the hospital, or having a severe outcome. This study involving direct EHR extraction identified known and less well-established demographics, and prior diagnoses and medications as risk factors for COVID-19 susceptibility and inpatient admission. Knowledge of these risk factors including marked ethnic disparities observed in disease severity should guide government policies, identify at-risk populations, inform clinical decision making, and prioritize future COVID-19 research.

Project description:IntroductionPatients with mental health diagnoses (MHD) are among the most frequent emergency department (ED) users, suggesting the importance of identifying additional factors associated with their ED use frequency. In this study we assessed various patient sociodemographic and clinical characteristics, and service use associated with low ED users (1-3 visits/year), compared to high (4-7) and very high (8+) ED users with MHD.MethodsOur study was conducted in four large Quebec (Canada) ED networks. A total of 299 patients with MHD were randomly recruited from these ED in 2021-2022. Structured interviews complemented data from network health records, providing extensive data on participant profiles and their quality of care. We used multivariable multinomial logistic regression to compare low ED use to high and very high ED use.ResultsOver a 12-month period, 39% of patients were low ED users, 37% high, and 24% very high ED users. Compared with low ED users, those at greater probability for high or very high ED use exhibited more violent/disturbed behaviors or social problems, chronic physical illnesses, and barriers to unmet needs. Patients previously hospitalized 1-2 times had lower risk of high or very high ED use than those not previously hospitalized. Compared with low ED users, high and very high ED users showed higher prevalence of personality disorders and suicidal behaviors, respectively. Women had greater probability of high ED use than men. Patients living in rental housing had greater probability of being very high ED users than those living in private housing. Using at least 5+ primary care services and being recurrent ED users two years prior to the last year of ED use had increased probability of very high ED use.ConclusionFrequency of ED use was associated with complex issues and higher perceived barriers to unmet needs among patients. Very high ED users had more severe recurrent conditions, such as isolation and suicidal behaviors, despite using more primary care services. Results suggested substantial reduction of barriers to care and improvement on both access and continuity of care for these vulnerable patients, integrating crisis resolution and supported housing services. Limited hospitalizations may sometimes be indicated, protecting against ED use.

Dataset Information

Validation of chief complaints, medical history, medications, and physician diagnoses structured with an integrated emergency department information system in Japan: the Next Stage ER system.

Publications

Validation of chief complaints, medical history, medications, and physician diagnoses structured with an integrated emergency department information system in Japan: the Next Stage ER system.

Similar Datasets

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