Abstract P317: Sex and Age Differences in a typical Chief Complains for Heart Failure in Emergency Department Visits

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Michelle L Meyer ◽  
Montika Bush ◽  
Jason J Bischof ◽  
Anna E Waller ◽  
Timothy F Platts-Mills
Keyword(s):  
Heart Failure ◽  
Emergency Department ◽  
Chest Pain ◽  
Age Differences ◽  
Chief Complaint ◽  
Age Group ◽  
Chief Complaints ◽  
Ed Visits ◽  
Respiratory Complaints ◽  
Sex And Age Differences

Background: Around 1 million United States emergency department (ED) visits per year are due to exacerbation of heart failure (HF) symptoms, with ~80% of those patients admitted to the hospital. However, sex and age differences in HF symptom presentation in the ED have not been thoroughly investigated. Objectives: To describe sex and age differences in chief complaints of ED patients with a HF diagnosis. Methods: We included patients ≥18 years old with an ED diagnosis of HF in NC DETECT, a statewide syndromic surveillance system. We defined a HF diagnosis using ICD-9-CM and ICD-10-CM codes from ED visits between 2010 and 2016. We classified the ED chief complaints into categories by symptom groups (e.g. respiratory complaint includes hypoxia, respiratory distress, breathing difficulties). Chief complaint categories are not mutually exclusive. We calculated frequencies of chief complaint categories for ED visits by sex and age (18-44 (n=55,216), 45-64 (n=260,397), ≥65 (n=578,313) years old) and evaluated for a 10% standardized difference between groups. Results: There were 422,720 patients with 893,950 total unique visits (1.6 average visits/person). Of these visits, 55.0% were by women and 59.5% patients were admitted. Overall, the top chief complaint categories were dyspnea (19.1%), chest pain (13.5%), and respiratory complaints (13.4%), and were similar by sex and by ED disposition (admitted or discharged) and sex. When stratified by sex and age group, in those 18-44 years old, women had more reports of nausea/vomiting (6.7%) compared with men (4.1%) and headache (4.2%) compared with men (2.0%). In those 45-64 and ≥65 years old, chief complaint categories were similar between women and men. When stratified by age group alone, reports of chest pain decreased with age (21.4% in 18-44, 17.7% in 45-64, and 10.8% in ≥65 year olds), whereas reports of balance issues (1.2% in 18-44, 2.4% in 45-64, and 6.0% in ≥65 year olds), weakness (1.7% in 18-44, 2.7% in 45-64, and 5.5% in ≥65 year olds), and confusion (0.8% in 18-44, 2.1% in 45-64, and 4.5% in ≥65 year olds) increased with age. Compared to those ≥65 years old, those 18-44 years old had fewer respiratory complaints (10.0% vs. 13.9%), but more reports of headache (3.2% vs. 0.8%) and nausea/vomiting (5.5% vs. 3.2%). Conclusion: In a state-wide population of ED patients with HF diagnoses, sex differences in chief complaint categories that are less obvious symptoms of HF were observed for those 18-44 years old, with women reporting more nausea/vomiting and headache compared to men. Chief complaint categories that are less obvious symptoms of HF were more common among patients 18-44 (nausea/vomiting, headache) and ≥65 (balance issues, confusion, weakness) years old. Characterizing the variation of symptoms of HF patients in the ED may help inform the identification of ED patients with HF and the outpatient management of HF-related symptoms.

scholarly journals Generating contextual embeddings for emergency department chief complaints

JAMIA Open ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 160-166
Author(s):  
David Chang ◽  
Woo Suk Hong ◽  
Richard Andrew Taylor
Keyword(s):  
Emergency Department ◽  
Short Term Memory ◽  
Language Model ◽  
Chief Complaint ◽  
Language Models ◽  
Free Text ◽  
Set Size ◽  
Chief Complaints ◽  
Ed Visits ◽  
Cutoff Threshold

Abstract 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.

scholarly journals Monitoring Out-of-State Patients during a 2017 Hurricane Response using ESSENCE

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Caleb Wiedeman ◽  
Julie Shaffner ◽  
Kelly Squires ◽  
Jeffrey Leegon ◽  
Rendi Murphree ◽  
...  
Keyword(s):  
Emergency Department ◽  
Syndromic Surveillance ◽  
Situational Awareness ◽  
Chief Complaint ◽  
Free Text ◽  
Chief Complaints ◽  
Major Hurricane ◽  
Ed Visits ◽  
Zip Code ◽  
Hurricane Irma

ObjectiveTo demonstrate the use of ESSENCE in the BioSense Platform to monitor out-of-State patients seeking emergency healthcare in Tennessee during Hurricanes Harvey and Irma.IntroductionSyndromic surveillance is the monitoring of symptom combinations (i.e., syndromes) or other indicators within a population to inform public health actions. The Tennessee Department of Health (TDH) collects emergency department (ED) data from more than 70 hospitals across Tennessee to support statewide syndromic surveillance activities. Hospitals in Tennessee typically provide data within 48 hours of a patient encounter. While syndromic surveillance often supplements disease- or condition-specific surveillance, it can also provide general situational awareness about emergency department patients during an event or response.During Hurricanes Harvey (continental US landfall on August 25, 2017) and Irma (continental US landfall on September 10, 2017), TDH supported all hazards situational awareness using the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) in the BioSense Platform supported by the National Syndromic Surveillance Program (NSSP). The volume of out-of-state patients in Tennessee was monitored to assess the impact on the healthcare system and any geographic- or hospital-specific clustering of out-of-state patients within Tennessee. Results were included in daily State Health Operations Center (SHOC) situation reports and shared with agency response partners such as the Tennessee Emergency Management Agency (TEMA).MethodsData were monitored from August 18, 2017 through September 24, 2017. A simple query was established in ESSENCE using the Patient Location (Full Details) dataset. Data were limited to hospital ED visits reported by Tennessee (Site = “Tennessee”). To monitor ED visits among residents of Texas before, during, and after Major Hurricane Harvey, data were queried for a patient zip code within Texas (State = “Texas”). ED visits among Florida residents were monitored similarly (State = “Florida”) before, during, and after Major Hurricane Irma. Additionally, a free text chief complaint search was implemented for the terms “Harvey”, “Irma, “hurricane”, “evacuee”, “evacuate”, “Florida”, and “Texas”. Chief complaint search results were then filtered to remove encounters with patient zip codes within Tennessee.ResultsFrom August 18, 2017 through September 24, 2017, Tennessee hospital EDs reported 277 patient encounters among Texas residents and 1,041 patient encounters among Florida residents. The number of encounters among patients from Texas remained stable throughout the monitoring period. In contrast, the number of encounters among patients from Florida exceeded the expected value on September 7, peaked September 10 at 116 patient encounters, and returned to expected levels on September 16 (Figure 1). The increase in patients from Florida was evenly distributed across most of Tennessee, with some clustering around a popular tourism area in East Tennessee. No concerning trends in reported syndromes or chief complaints were identified among Texas or Florida patients.The free text chief complaint query first exceeded the expected value on September 9, peaked on September 11 with 5 patient encounters, and returned to expected levels on September 14. From August 18 through September 24, 21 of 30 visits captured by the query were among Florida residents. One Tennessee hospital appeared to be intentionally using the term “Irma” in their chief complaint field to indicate patients from Florida impacted by the hurricane.ConclusionsThe ESSENCE instance in the BioSense platform provided TDH the opportunity to easily locate and monitor out-of-state patients seen in Tennessee hospital EDs. While TDH was unable to validate whether all patients identified as residents of Florida were displaced because of Major Hurricane Irma, the timing of the rise and fall of patient encounters was highly suggestive. Likewise, seeing no substantial increase ED patients with residence in Texas reassured TDH that the effects of Hurricane Harvey were not impacting hospital emergency departments in Tennessee.TDH used information and charts from ESSENCE to support situational awareness in our SHOC and at TEMA. Use of patient zip code to identify out-of-state residents was more sensitive than chief complaint searches by keyword during this event. ESSENCE allowed TDH to see where out-of-state patients appeared to be concentrating in Tennessee and monitor the need for targeting messaging and resources to heavily affected areas. Additionally, close surveillance of chief complaints among out-of-state patients provided assurance that no unusual patterns in illness or injury were occurring.ESSENCE is the only TDH information source capable of rapidly collecting health information on out-of-state patients. ESSENCE allowed TDH to quickly identify a change within the patient population seen at Tennessee emergency departments and monitor the situation until the patient population returned to baseline levels.

scholarly journals Effects of Dust Storms and Climatological Factors on Mortality and Morbidity of Cardiovascular Diseases Admitted to ED

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Behcet Al ◽  
Mustafa Bogan ◽  
Suat Zengin ◽  
Mustafa Sabak ◽  
Seval Kul ◽  
...  
Keyword(s):  
Heart Failure ◽  
Emergency Department ◽  
Chest Pain ◽  
Cardiovascular Diseases ◽  
Dust Storm ◽  
Dust Storms ◽  
Maximum Temperature ◽  
Inpatient Hospitalization ◽  
Mortality And Morbidity ◽  
Coronary Syndrome

Objective. This study was designed to investigate the effects of Desert Dust Storms and Climatological Factors on Mortality and Morbidity of Cardiovascular Diseases admitted to emergency department in Gaziantep. Method. Hospital records, obtained between September 01, 2009 and January 31, 2014, from four state hospitals in Gaziantep, Turkey, were compared to meteorological and climatological data. Statistical analysis was performed by Statistical Package for the Social Science (SPSS) for windows version 24.0. Results. 168,467 patients were included in this study. 83% of the patients had chest pain and 17% of patients had cardiac failure (CF). An increase in inpatient hospitalization due to CF was observed and corresponded to the duration of dust storms measured by number of days. However, there was no significant increase in emergency department (ED) presentations. There was no significant association of cardiac related mortality and coinciding presence of a dust storm or higher recorded temperature. The association of increases in temperature levels and the presence of dust storms with “acute coronary syndrome- (ACS-) related emergency service presentations, inpatient hospitalization, and mortality” were statistically significant. The relationship between the increase in PM10 levels due to causes unrelated to dust storms and the outpatient application, admission, and mortality due to heart failure was not significant. The increase in particle matter 10 (PM) levels due to causes outside the dust storm caused a significant increase in outpatient application, hospitalization, and mortality originated from ACS. Conclusion. Increased number of dust storms resulted in a higher prevalence of mortality due to ACS while mortality due to heart failure remained unchanged. Admission, hospitalization, and mortality due to chest pain both dependent and independent of ACS were increased by the presence of dust storms, PM10 elevation, and maximum temperature.

scholarly journals Derivation of a clinical decision rule for chest radiography in emergency department patients with chest pain and possible acute coronary syndrome

CJEM ◽  
2010 ◽  
Vol 12 (02) ◽  
pp. 128-134 ◽  
Author(s):  
Erik P. Hess ◽  
Jeffrey J. Perry ◽  
Pam Ladouceur ◽  
George A. Wells ◽  
Ian G. Stiell
Keyword(s):  
Heart Failure ◽  
Emergency Department ◽  
Congestive Heart Failure ◽  
Chest Pain ◽  
Chest Radiography ◽  
Clinical Decision ◽  
Chest Radiographs ◽  
Clinical Decision Rule ◽  
Coronary Syndrome ◽  
History Of

ABSTRACTObjective:We derived a clinical decision rule to determine which emergency department (ED) patients with chest pain and possible acute coronary syndrome (ACS) require chest radiography.Methods:We prospectively enrolled patients over 24 years of age with a primary complaint of chest pain and possible ACS over a 6-month period. Emergency physicians completed standardized clinical assessments and ordered chest radiographs as appropriate. Two blinded investigators independently classified chest radiographs as “normal,” “abnormal not requiring intervention” and “abnormal requiring intervention,” based on review of the radiology report and the medical record. The primary outcome was abnormality of chest radiographs requiring acute intervention. Analyses included interrater reliability assessment (with κ statistics), univariate analyses and recursive partitioning.Results:We enrolled 529 patients during the study period between Jul. 1, 2007, and Dec. 31, 2007. Patients had a mean age of 59.9 years, 60.3% were male, 4.0% had a history of congestive heart failure and 21.9% had a history of acute myocardial infarction. Only 2.1% (95% confidence interval [CI] 1.1%–3.8%) of patients had radiographic abnormality of the chest requiring acute intervention. The κ statistic for chest radiograph classification was 0.81 (95% CI 0.66–0.95). We derived the following rule: patients can forgo chest radiography if they have no history of congestive heart failure, no history of smoking and no abnormalities on lung auscultation. The rule was 100% sensitive (95% CI 32.0%–10.4%) and 36.1% specific (95% CI 32.0%–40.4%).Conclusion:This rule has potential to reduce health care costs and enhance ED patient flow. It requires validation in an independent patient population before introduction into clinical practice.

scholarly journals Cartography of Emergency Department Visits for Asthma – Targeting High-Morbidity Populations

2004 ◽  
Vol 11 (6) ◽  
pp. 427-433 ◽  
Author(s):  
Pierre Lajoie ◽  
Andrée Laberge ◽  
Germain Lebel ◽  
Louis-Philippe Boulet ◽  
Marie Demers ◽  
...  
Keyword(s):  
Emergency Department ◽  
Emergency Department Visits ◽  
Administrative Database ◽  
Chronic Obstructive ◽  
High Morbidity ◽  
Age Group ◽  
Obstructive Pulmonary Disease ◽  
Asthmatic Patients ◽  
South Central ◽  
Ed Visits

BACKGROUND:Asthma education should be offered with priority to populations with the highest asthma-related morbidity. In the present study, the aim was to identify populations with high-morbidity for asthma from the Quebec Health Insurance Board Registry, a large administrative database, to help the Quebec Asthma and Chronic Obstructive Pulmonary Disease Network target its interventions.METHODS:All emergency department (ED) visits for asthma were analyzed over a one-year period, considering individual and medical variables. Age- and sex-adjusted rates, as well as standardized rate ratios related to the overall Quebec rate, among persons zero to four years of age and five to 44 years of age were determined for 15 regions and 163 areas served by Centres Locaux de Services Communautaires (CLSC). The areas with rates 50% to 300% higher (P<0.01) than the provincial rate were defined as high-morbidity areas. Maps of all CLSC areas were generated for the above parameters.RESULTS:There were 102,551 ED visits recorded for asthma, of which more than 40% were revisits. Twenty-one CLSCs and 32 CLSCs were high-morbidity areas for the zero to four years age group and five to 44 years age group, respectively. For the most part, the high-morbidity areas were located in the south-central region of Quebec. Only 47% of asthmatic patients seen in ED had also seen a physician in ambulatory care.CONCLUSION:The data suggest that a significant portion of the population seeking care at the ED is undiagnosed and undertreated. A map of high-morbidity areas that could help target interventions to improve asthma care and outcomes is proposed.

scholarly journals Validation of a Decision Rule and Derivation of a Modified Rule to Obtain Chest Radiograph in Patients with Nontraumatic Chest Pain in the Emergency Department

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Case Newsom ◽  
Rebecca Jeanmonod ◽  
Karl Weller ◽  
Nabil Boutros ◽  
Mark Reiter ◽  
...  
Keyword(s):  
Heart Failure ◽  
Emergency Department ◽  
Congestive Heart Failure ◽  
Chest Pain ◽  
Alcohol Abuse ◽  
Decision Rule ◽  
Predictive Value ◽  
Breath Sounds ◽  
History Of ◽  
Sensitivity Specificity

Objectives. We sought to validate and refine a decision rule for chest X-ray (CXR) utilization in nontraumatic chest pain (CP) patients presenting to the emergency department (ED). Methods. Retrospective review of ED patients presenting with CP who had CXR performed during three nonconsecutive months was performed. The presence of 18 variables derived from history and exam was ascertained. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the original rule were calculated. Refinement using additional variables was performed. Results. 967 patient charts were reviewed. 89.9% of CXR were normal, 5.2% had insignificant findings, and 5.1% had significant findings. Application of the criteria had a sensitivity/specificity of 74%/59% and a PPV/ NPV of 9%/98%. Rule modification to obtain CXR for age ≥ 65 years, history of congestive heart failure and alcohol abuse, and exam findings of decreased breath sounds, fever, and tachypnea maintained sensitivity while improving specificity to 69%. Conclusions. Most CP patients have normal CXRs. Narrowing a decision rule to obtain CXR in patients with age ≥ 65 years, history of congestive heart failure and alcohol abuse, and exam findings of decreased breath sounds, fever, and tachypnea maintain sensitivity while improving specificity and NPV.

scholarly journals Free-Text Mining to Improve Syndrome Definition Matching Across Emergency Departments

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Kristin Arkin
Keyword(s):  
Text Mining ◽  
Influenza Season ◽  
Chief Complaint ◽  
Free Text ◽  
Diagnosis Code ◽  
Diagnosis Codes ◽  
Chief Complaints ◽  
Group A ◽  
Ed Visits ◽  
Group B

ObjectiveWe sought to use free text mining tools to improve emergency department (ED) chief complaint and discharge diagnosis data syndrome definition matching across facilities with differing robustness of data in the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) application in Idaho’s syndromic surveillance system.IntroductionStandard syndrome definitions for ED visits in ESSENCE rely on chief complaints. Visits with more words in the chief complaint field are more likely to match syndrome definitions. While using ESSENCE, we observed geographic differences in chief complaint length, apparently related to differences in electronic health record (EHR) systems, which resulted in disparate syndrome matching across Idaho regions. We hypothesized that chief complaint and diagnosis code co-occurrence among ED visits to facilities with long chief complaints could help identify terms that would improve syndrome match among facilities with short chief complaints.MethodsThe ESSENCE-defined influenza-like illness (ILI) chief complaint syndrome was used as the base syndrome for this analysis. Syndrome-matched visits were defined as visits that match the syndrome definition.We assessed chief complaints and diagnosis code co-occurrence of syndrome-matched visits using the RCRAN TidyText package and developed a bigram network from normalized, concatenated chief complaint and diagnosis code (CCDD) fields and normalized diagnosis code (DD) fields per previously described methodologies.1 Common connections were defined by a natural break in frequency of pair occurrence for CCDD pairs (30 occurrences) and DD pairs (5 occurrences).The ESSENCE syndrome was revised by adding relevant bigram network clusters and logic operators. We compared time series of the percent of ED visits matched to the ESSENCE syndrome with those matched to the revised syndrome. We stratified the time series by facilities grouped by short (average < 4 words, “Group A”) and long (average ≥ 4 words, “Group B”) chief complaint fields (Figure 1). Influenza season start was defined as two consecutive weeks above baseline, or the 95% upper confidence limit of percent syndrome-matched visits outside of the CDC ILI surveillance season. Season trends and influenza-related deaths in Idaho residents were compared.ResultsDuring August 1, 2016 through July 31, 2017, 1,587 (1.17%) of 135,789 ED visits matched the ESSENCE syndrome. Bigram networks of CCDD fields produced clusters already included by the ESSENCE syndrome. The bigram network of DD fields (Figure 2) produced six clusters. The revised syndrome definition included the ESSENCE syndrome, 3 single DD terms, and 3 two DD terms combined. The start of influenza season was identified as the same week for both ILI syndrome definitions (ESSENCE baseline 0.70%; revised baseline 2.21%). The ESSENCE syndrome indicated the season peaked during Morbidity and Mortality Weekly Report (MMWR) week 2017-05 with the season ending MMWR week 2017-14. The revised syndrome indicated 2017-20 as the season end. Multiple peaks seen with the revised syndrome during MMWR weeks 2017-02, 2017-05, and 2017-10 mirrored peaks in influenza-related deaths during MMWR weeks 2017-03, 2017-06, and 2017-11.ILI season onset was five weeks earlier with the revised syndrome compared with the ESSENCE syndrome in Group A facilities, but remained the same in Group B. The annual percentage of ED visits related to ILI was more uniform between facility groups under the revised syndrome than the ESSENCE syndrome. Unlike the trend seen with the ESSENCE syndrome, the revised syndrome shows low-level ILI activity in both groups year-round.ConclusionsIn Idaho, dramatic differences in ED visit chief complaint word counts were seen between facilities; bigram networks were found to be an important tool to identify diagnosis codes and logical operators that built more inclusive syndrome definitions when added to an existing chief complaint syndrome. Bigram networks may aid understanding the relationship between chief complaints and diagnosis codes in syndrome-matched visits.Use of trade names and commercial sources is for identification only and does not imply endorsement by the Centers for Disease Control and Prevention, the Public Health Service, or the U.S. Department of Health and Human Services.References1. Silge, J., Robinson, D. (2017). “Text Mining with R”. O’Reilly.

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