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.

scholarly journals Using Real-Time Syndromic Surveillance to Analyze the Impact of a Cold Weather Event in New Mexico

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
Victoria F. Dirmyer
Keyword(s):  
Real Time ◽  
Syndromic Surveillance ◽  
Chief Complaint ◽  
Cold Weather ◽  
Weather Event ◽  
Diagnosis Codes ◽  
Chief Complaints ◽  
Icd 10 ◽  
Ed Visits ◽  
The Impact

Objective. This report describes the development of a novel syndromic cold weather syndrome for use in monitoring the impact of cold weather events on emergency department attendance. Methods. Syndromic messages from seven hospitals were analyzed for ED visits that occurred over a 12-day period. A cold weather syndrome was defined using terms in the self-reported chief complaint field as well as specific ICD-10-CM codes related to cold weather. A κ statistic was calculated to assess the overall agreement between the chief complaint field and diagnosis fields to further refine the cold weather syndrome definition. Results. Of the 3,873 ED visits that were reported, 487 were related to the cold weather event. Sixty-three percent were identified by a combination of diagnosis codes and chief complaints. Overall agreement between chief complaint and diagnosis codes was moderate (κ=0.50; 95% confidence interval = 0.48–0.52). Conclusion. Due to the near real-time reporting of syndromic surveillance data, analysis results can be acted upon. Results from this analysis will be used in the state’s emergency operations plan (EOP) for cold weather and winter storms. The EOP will provide guidance for mobilization of supplies/personnel, preparation of roadways and pedestrian walkways, and the coordination efforts of multiple state agencies.

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 Early effect of validation efforts of Massachusetts syndromic surveillance data

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Mark Bova ◽  
Roas Ergas
Keyword(s):  
Emergency Department ◽  
Data Quality ◽  
Syndromic Surveillance ◽  
Chief Complaint ◽  
Surveillance Program ◽  
Production Environment ◽  
Diagnosis Code ◽  
Diagnosis Codes ◽  
Chief Complaints ◽  
Validation Strategy

ObjectiveTo develop a detailed data validation strategy for facilitiessending emergency department data to the Massachusetts SyndromicSurveillance program and to evaluate the validation strategy bycomparing data quality metrics before and after implementation ofthe strategy.IntroductionAs a participant in the National Syndromic Surveillance Program(NSSP), the Massachusetts Department of Public Health (MDPH)has worked closely with our statewide Health Information Exchange(HIE) and National Syndromic Surveillance Program (NSSP)technical staff to collect and transmit emergency department (ED)data from eligible hospitals (EHs) to the NSSP. Our goal is to ensurecomplete and accurate data using a multi-step process beginning withpre-production data and continuing after EHs are sending live datato production.MethodsWe used an iterative process to establish a framework formonitoring data quality during onboarding of EHs into our syndromicsurveillance system and kept notes of the process.To evaluate the framework, we compared data received duringthe month of January 2016 to the most recent full month of data(June 2016) to describe the following primary data quality metricsand their change over time: total and daily average of message andvisit volume; percent of visits with a chief complaint or diagnosiscode received in the NSSP dataset; and percentage of visits with achief complaint/diagnosis code received within a specified time ofadmission to the ED.ResultsThe strategies for validation we found effective includedexamination of pre-production test HL7 messages and the executionof R scripts for validation of live data in the staging and productionenvironments. Both the staging and production validations areperformed at the individual message level as well as the aggregatedvisit level, and included measures of completeness for requiredfields (Chief Complaint, Diagnosis Codes, Discharge Dispositions),timeliness, examples of text fields (Chief Complaint and TriageNotes), and demographic information. We required EHs to passvalidation in the staging environment before granting access to senddata to the production environment.From January to June 2016, the number of EHs sending data tothe production environment increased from 44 to 48, and the numberof messages and visits captured in the production environmentincreased substantially (see Table 1). The percentage of visits witha chief complaint remained consistently high (>99%); howeverthe percentage of visits with a chief complaint within three hoursof admission decreased during the study period. Both the overallpercentage of visits with a diagnosis code and the percentage of visitswith a diagnosis code within 24 hours of admission increased.ConclusionsFrom January to June 2016, Massachusetts syndromic surveillancedata improved in the percentage of visits with diagnosis codes and thetime from admission to first diagnosis code. This was achieved whilethe volume of data coming into the system increased. The timelinessof chief complaints decreased slightly during the study period, whichmay be due to the inclusion of several new facilities that are unable tosend real-time data. Even with the improvements in the timeliness ofthe diagnosis code field, and the subsequent decrease in the timelinessof the chief complaint field, chief complaints remained a more timelyoption for syndromic surveillance. Pre-production and ongoing dataquality assurance activities are crucial to ensure meaningful dataare acquired for secondary analyses. We found that reviewing testHL7 messages and staging data, daily monitoring of productiondata for key factors such as message volume and percent of visitswith a diagnosis code, and monthly full validation in the productionenvironment were and will continue to be essential to ensure ongoingdata integrity.Table 1: ED Data in the Production Environment

Evaluation of effect of efficacy of Koshtha Shuddhi in the Management of Gridrasi (Sciatica)

The Healer ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 48-51
Author(s):  
Sandeepanie Maragalawaththa ◽  
E.R.H.S.S. Ediriweera
Keyword(s):  
Medical Condition ◽  
The Body ◽  
Root Cause ◽  
Lower Back ◽  
Effect Of Therapy ◽  
Chief Complaints ◽  
Group A ◽  
Group B ◽  
Gastro Intestinal Tract ◽  
Inflammatory Effect

Introduction: Sciatica is a medical condition of pain going down the leg through back, outside, or front of the leg from the lower back. It can be co-related with Grdrasi caused by both the aggravated Vata and Kapha two elements out of three basic elements of the body. Diagnostic method of disease is different and management also based on root cause of the disease. Sepalika  (Nyctanthes arbor-tristis.Linn.)(Oleacea) leaves are having anti inflammatory effect and analgesic effect. Aim and Objectives: To Evaluate the efficacy of Koshtha (GIT) (Gastro Intestinal tract) Shuddhi (Purification) in the management of Gridrasi w.s.r. to Sciatica. Material and methods: For this study, 20 patients were resisted and divided into two groups. Registered patients of group A and Group B were given Koshtha Shuddhi with Sepalika leaves decoction along with Sashapadi oil Abhyanga and Sand Potali fomentation and Sepalika leaves decoction along with Sashapadi oil Abhyanga and Sand Potali fomentation respectively for 2 weeks before meal. Patients of group A were given 120ml of Vasagudushi decoction with 5ml Eranada oil twice a day for purpose of Koshtha Shuddhi for 3 days. The effect of therapy was evaluated on the basis of changes of chief complaints and SLR test was taken for assessment parameter. Discussion: The statistically significant relief was showed on the chief complaints of Gridrasi (Sciatica) in the both the groups except Ruk (Pain) in group B. SLR of all the patient of present study were in between 30o- 70o in R/side LL (Lower Limb). SLR was changed of both the groups up to 70o-90o and 100% showed relief except 4 patients in the group B. Conclusion: It can be concluded that the Koshtha Shuddhi is showed comparatively better effect than management of Gridrasi (Sciatica) without carried out Koshtha Shuddhi.

scholarly journals Characteristics and Risk Factors of Recurrent Epistaxis in Geriatric Patients

2021 ◽  
Vol 64 (8) ◽  
pp. 548-553
Author(s):  
So Jeong Kim ◽  
So Jeong Lee ◽  
Yu Jin Go ◽  
Sohl Park ◽  
Jung Ho Bae
Keyword(s):  
Risk Factors ◽  
Initial Treatment ◽  
The Elderly ◽  
Treatment Method ◽  
Recurrent Epistaxis ◽  
Group A ◽  
Ed Visits ◽  
Group B ◽  
Care Costs ◽  
Precise Area

Background and Objectives Recurrent epistaxis requiring emergency department (ED) visits results in increased morbidity in the elderly and associated with high health care costs. This study is to analyze the frequency and characteristics of epistaxis patients in the elderly and to find out the risk factors and effective treatment for recurrent epistaxis. Subjects and Method We studied retrospectively the clinical cases of 977 emergency patients and 155 patients, aged over 65, for the treatment of epistaxis during the last 10 years from January 2008 to January 2018. The group A, comprised of 95 patients (68.29%), was treated with an initial treatment. The group B, which comprised of 60 patients (38.71%), visited for re-bleeding following an initial treatment. Results Patients made 2 to 10 ED visits due to re-bleeding and 32 of the 60 patients (53.5%) visited twice. The electrocauterization was the most common (61.7%) for treatment method during rebleeding, followed by posterior packing (18.3%). The factors that increases the risk of recurrent epistaxis are anticoagulants, posterior epistaxis, anterior packing, inefficient ED packing. There was no correlation between comorbidities and rebleeding. Conclusion Accurate medical history taking of anticoagulants may enable personnel to provide more effective management of these patients. The most important factors in the failure of primary care were not being able to find the precise area of bleeding and ineffective packing during the initial treatment. Therefore, it is important that we must carefully check the areas using the endoscope to decrease the failure of initial treatment of epistaxis.

scholarly journals Clinical and demographic profile of paediatric patients presenting with acute diarrhea

2020 ◽  
Vol 7 (5) ◽  
pp. 1043
Author(s):  
Apurva C. Shah ◽  
Devendra Sareen ◽  
Dileep Kumar Goyal
Keyword(s):  
Tertiary Care ◽  
Public Health Problem ◽  
Rural People ◽  
Demographic Profile ◽  
Chief Complaints ◽  
Male Preponderance ◽  
Group A ◽  
And Gender ◽  
Group B ◽  
Study Participants

Background: Diarrhea is a public health problem globally, being the 2nd leading cause of death in children under 5 years. Dehydration as well as malnutrition are also serious consequences of diarrhea. This study was carried out with an aim to focus on the clinical and demographic profile of diarrheal patients of pediatric age.Methods: Infants and children aged 6 months to 5 years were analysed for age and gender distribution, chief complaints, feeding practices, nutritional status and assessment of dehydration; from January 2018 to June 2019 in the Department of Pediatrics of a Tertiary Care Teaching Hospital.Results: Total 150 patients were analysed. Almost 50.67% group A and 41.34% group B patients belonged to toddlerhood. Male preponderance was also noted. Along with diarrhea, vomiting was noted in 22 group A and 21 group B and fever in 19 group A and 29 group B patients. Approximately 41-45% patients had no malnutrition and 55-60% had no dehydration in both the study groups.Conclusions: There is lack of awareness regarding dog bite and its management among the rural people fever and vomiting were most frequently associated with diarrhea. A little less than half of the study participants had some-dehydration. Nearly half of the patients belonged to toddler age group. Majority of the patients were exclusively breast-fed for six months.

scholarly journals Validation of a Syndromic Case Definition for Detecting Emergency Department Visits Potentially Related to Marijuana

2017 ◽  
Vol 132 (4) ◽  
pp. 471-479 ◽  
Author(s):  
Kathryn DeYoung ◽  
Yushiuan Chen ◽  
Robert Beum ◽  
Michele Askenazi ◽  
Cali Zimmerman ◽  
...  
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
Health Impact ◽  
Case Definition ◽  
Emergency Department Visits ◽  
Free Text ◽  
Search Term ◽  
Diagnosis Codes ◽  
Ed Visits ◽  
The Impact

Objectives: Reliable methods are needed to monitor the public health impact of changing laws and perceptions about marijuana. Structured and free-text emergency department (ED) visit data offer an opportunity to monitor the impact of these changes in near-real time. Our objectives were to (1) generate and validate a syndromic case definition for ED visits potentially related to marijuana and (2) describe a method for doing so that was less resource intensive than traditional methods. Methods: We developed a syndromic case definition for ED visits potentially related to marijuana, applied it to BioSense 2.0 data from 15 hospitals in the Denver, Colorado, metropolitan area for the period September through October 2015, and manually reviewed each case to determine true positives and false positives. We used the number of visits identified by and the positive predictive value (PPV) for each search term and field to refine the definition for the second round of validation on data from February through March 2016. Results: Of 126 646 ED visits during the first period, terms in 524 ED visit records matched ≥1 search term in the initial case definition (PPV, 92.7%). Of 140 932 ED visits during the second period, terms in 698 ED visit records matched ≥1 search term in the revised case definition (PPV, 95.7%). After another revision, the final case definition contained 6 keywords for marijuana or derivatives and 5 diagnosis codes for cannabis use, abuse, dependence, poisoning, and lung disease. Conclusions: Our syndromic case definition and validation method for ED visits potentially related to marijuana could be used by other public health jurisdictions to monitor local trends and for other emerging concerns.

scholarly journals Enhanced home palliative care could reduce emergency department visits due to non-organic dyspnea among cancer patients: a retrospective cohort study

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Hua-Shui Hsu ◽  
Tai-Hsien Wu ◽  
Chin-Yu Lin ◽  
Ching-Chun Lin ◽  
Tsung-Po Chen ◽  
...  
Keyword(s):  
Emergency Department ◽  
Palliative Care ◽  
Cancer Patients ◽  
Emergency Department Visits ◽  
Standard Operating Procedures ◽  
Gi Symptoms ◽  
Standard Operating ◽  
Group A ◽  
Ed Visits ◽  
Group B

Abstract Background Dyspnea is a common trigger of emergency department visits among terminally ill and cancer patients. Frequent emergency department (ED) visits at the end of life are an indicator of poor-quality care. We examined emergency department visit rates due to dyspnea symptoms among palliative patients under enhanced home palliative care. Methods Our home palliative care team is responsible for patient management by palliative care specialists, residents, home care nurses, social workers, and chaplains. We enhanced home palliative care visits from 5 days a week to 7 days a week, corresponding to one to two extra visits per week based on patient needs, to develop team-based medical services and formulate standard operating procedures for dyspnea care. Results Our team cared for a total of 762 patients who exhibited 512 ED visits, 178 of which were due to dyspnea (mean ± SD age, 70.4 ± 13.0 years; 49.4% male). Dyspnea (27.8%) was the most common reason recorded for ED visits, followed by pain (19.0%), GI symptoms (15.7%), and fever (15.3%). The analysis of Group A versus Group B revealed that the proportion of nonfamily workers (42.9% vs. 19.4%) and family members (57.1% vs. 80.6%) acting as caregivers differed significantly (P < 0.05). Compared to the ED visits of the Group A, the risk was decreased by 30.7% in the Group B (P < 0.05). Conclusions This study proves that enhanced home palliative care with two additional days per week and formulated standard operating procedures for dyspnea could significantly reduce the rate of ED visits due to non-organic dyspnea during the last 6 months of life.

scholarly journals Developing and Validating a Fireworks-Related Syndrome Definition in Kansas

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Zachary M Stein
Keyword(s):  
Syndromic Surveillance ◽  
Public Information ◽  
False Positives ◽  
Chief Complaint ◽  
Surveillance Program ◽  
Anatomical Location ◽  
Free Text ◽  
Data Set ◽  
Ed Visits ◽  
Key Terms

ObjectiveTo develop a syndrome definition and analyze syndromic surveillance data usefulness in surveillance of firework-related emergency department visits in Kansas. Introduction Across the U.S.A., multiple people seek treatment for fireworks-related injuries around the July 4th holiday. Syndromic surveillance in Kansas allows for near real-time analysis of the injuries occurring during the firework selling season. During the 2017 July 4thholiday, the Kansas Syndromic Surveillance Program (KSSP) production data feed received data from 88 EDs at excellent quality and timeliness. Previous and current firework safety messaging in Kansas is dependent on voluntary reporting from hospitals across the state. With widespread coverage of EDs by KSSP, data can be more complete and timely to better drive analysis and public information Methods:KSSP data was queried through the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) v.1.20 provided by the National Syndromic Surveillance Program. Data between June 12, 2017 and August 13, 2017 were queried. The first query (Query A, Table 1.) searched the Discharge Diagnosis History field for the “W39” ICD-10 Diagnosis code, “Discharge of firework.” These records were searched for common firework terms contained in the Chief Complaint History field. These firework-related free text terms (Query B, Table 1.) were then combined with other potential firework-related terms to create a preliminary free text query (Query C, Table 1.). This preliminary query was run on the Chief Complaint History field. Data were then searched for false positive cases and appropriate negation terms were included to accommodate this. The new query with negation terms (Query D, Table 1.) was run on the Chief Complaint History field, combined with the results from the Discharge Diagnosis History field, and then combined records were de-duplicated based on a unique visit identifier. The final data set was then classified by the anatomical location of the injury and the gender and age group of the patient. Results:The initial query (Query A, Table 1.) for the diagnosis code “W39” returned 101 unique ED visits. Of these 101 unique ED visits, the following terms were identified in the Chief Complaint History field: shell, artillery, bomb, sparkler, grenade, fire cracker, firework, and firework show. These key terms were translated into Query B, Table 1. Other key terms deemed likely to capture specific firework-related exposures were then included into Query C, Table 1. , including roman, candle, lighter, M80, and punk. Query C was then used to query the Chief Complaint History field, returning 144 unique ED visits. Cases captured by Query C were then reviewed by hand for false positives and the negation terms, lighter fluid, fish, nut, and pistachio, were incorporated the Query D, Table 1. The previous process for Query C was then repeated on Query D, leaving a remaining 136 unique cases. Query A’s 101 unique ED visits was then combined with the 136 unique ED visits captured by Query D and de-duplicated. The de-duplicated data set contained 170 unique ED visits which were then reviewed by hand for false positives. The final removal of false positives from the combined and de-duplicated data set left a remaining 154 unique ED visits for firework-related injuries during this time period.For these data, the most common victims of firework injuries were males, accounting for 65.5% of all firework related ED visits and children ages 0 to 19 accounting for 44.2% of these visits. At every age breakout, male injuries exceeded female injuries. The most common anatomical location of the injury was one or both hands with 38.3% of all injuries mentioned hands as their primary injury. Injuries to the eyes, face, and head accounted for the second most injuries (28.6% of all patients). Conclusions: The selling of fireworks will be a yearly occurrence of a specific exposure that can potentially lead to injuries. Utilizing syndromic surveillance to review the holiday firework injuries is a very rapid method to assess the impact of these injuries and may allow for future direction of public information during the holiday. Having a syndrome definition that builds on knowledge from previous years will allow for quicker case identification as well.State public information regarding firework safety can be significantly bolstered by accurate and rapid data assessment. Developing a firework injury syndrome definition that is accurate and returns information rapidly has allowed for increased buy-in to the Kansas Syndromic Surveillance Program from public information offices, fire marshal’s offices, and other program fields.

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