scholarly journals A step closer to nationwide electronic health record–based chronic disease surveillance: characterizing asthma prevalence and emergency department utilization from 100 million patient records through a novel multisite collaboration

2019 ◽  
Vol 27 (1) ◽  
pp. 127-135
Author(s):  
Yasir Tarabichi ◽  
Jake Goyden ◽  
Rujia Liu ◽  
Steven Lewis ◽  
Joseph Sudano ◽  
...  
Keyword(s):  
United States ◽  
Emergency Department ◽  
Chronic Disease ◽  
Electronic Health Record ◽  
Disease Surveillance ◽  
The United States ◽  
Emergency Department Visits ◽  
Asthma Prevalence ◽  
Health Record ◽  
Health Records

Abstract Objective The study sought to assess the feasibility of nationwide chronic disease surveillance using data aggregated through a multisite collaboration of customers of the same electronic health record (EHR) platform across the United States. Materials and Methods An independent confederation of customers of the same EHR platform proposed and guided the development of a program that leverages native EHR features to allow customers to securely contribute de-identified data regarding the prevalence of asthma and rate of asthma-associated emergency department visits to a vendor-managed repository. Data were stratified by state, age, sex, race, and ethnicity. Results were qualitatively compared with national survey-based estimates. Results The program accumulated information from 100 million health records from over 130 healthcare systems in the United States over its first 14 months. All states were represented, with a median coverage of 22.88% of an estimated state’s population (interquartile range, 12.05%-42.24%). The mean monthly prevalence of asthma was 5.27 ± 0.11%. The rate of asthma-associated emergency department visits was 1.39 ± 0.08%. Both measures mirrored national survey-based estimates. Discussion By organizing the program around native features of a shared EHR platform, we were able to rapidly accumulate population level measures from a sizeable cohort of health records, with representation from every state. The resulting data allowed estimates of asthma prevalence that were comparable to data from traditional epidemiologic surveys at both geographic and demographic levels. Conclusions Our initiative demonstrates the potential of intravendor customer collaboration and highlights an organizational approach that complements other data aggregation efforts seeking to achieve nationwide EHR-based chronic disease surveillance.

Automated chronic disease surveillance and visualization using electronic health record data

2011 ◽  
Vol 4 (0) ◽  
Author(s):  
Michael Klompas ◽  
Chaim Kirby ◽  
Jason McVetta ◽  
Paul Oppedisano ◽  
John Brownstein ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Electronic Health Record ◽  
Disease Surveillance ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Record Data ◽  
Electronic Health

scholarly journals Emergency Department Visits From 2014 to 2018 for Head Injuries in Youth Non-Tackle Football Compared With Other Sports

2021 ◽  
Vol 9 (1) ◽  
pp. 232596712097540
Author(s):  
Jessica M. Zendler ◽  
Ron Jadischke ◽  
Jared Frantz ◽  
Steve Hall ◽  
Grant C. Goulet
Keyword(s):  
United States ◽  
Emergency Department ◽  
Head Injury ◽  
Head Injuries ◽  
The United States ◽  
Emergency Department Visits ◽  
Head Region ◽  
Cerebral Contusion ◽  
Common Diagnosis ◽  
Tackle Football

Background: Non-tackle football (ie, flag, touch, 7v7) is purported to be a lower-risk alternative to tackle football, particularly in terms of head injuries. However, data on head injuries in non-tackle football are sparse, particularly among youth participants. Purpose: To describe the epidemiology of  emergency department visits for head injuries due to non-tackle football among youth players in the United States and compare the data with basketball, soccer, and tackle football. Study Design: Descriptive epidemiology study. Methods: Injury data from 2014 to 2018 were obtained from the National Electronic Injury Surveillance System database. Injury reports coded for patients aged 6 to 18 years and associated with basketball, football, or soccer were extracted. Data were filtered to include only injuries to the head region, specifically, the head, ear, eyeball, mouth, or face. Football injuries were manually assigned to “non-tackle” or “tackle” based on the injury narratives. Sports & Fitness Industry Association data were used to estimate annual sport participation and calculate annual injury rates per 100,000 participant-years. Results: A total of 26,770 incident reports from 2014 to 2018 were analyzed. For head region injuries in non-tackle football, the head was the most commonly injured body part, followed by the face; the most common diagnosis was a laceration, followed by concussion and internal injury (defined as an unspecified head injury or internal head injury [eg, subdural hematoma or cerebral contusion]). The most common contacting object was another player. The projected national rate of head region injuries was lowest for non-tackle football across the 4 sports. In particular, the projected rate of injuries to the head for non-tackle football (78.0 per 100,000 participant-years) was less than one-fourth the rates for basketball (323.5 per 100,000 participant-years) and soccer (318.2 per 100,000 participant-years) and less than one-tenth the rate for tackle football (1478.6 per 100,000 participant-years). Conclusion: Among youth in the United States aged 6 to 18 years who were treated in the emergency department for injuries related to playing non-tackle football, the most common diagnosis for injuries to the head region was a laceration, followed by a concussion. Head region injuries associated with non-tackle football occurred at a notably lower rate than basketball, soccer, or tackle football.

Hospital Emergency Department Visits Attributed to Pulpal and Periapical Disease in the United States in 2006

2011 ◽  
Vol 37 (1) ◽  
pp. 6-9 ◽  
Author(s):  
Romesh P. Nalliah ◽  
Veeratrishul Allareddy ◽  
Satheesh Elangovan ◽  
Nadeem Karimbux ◽  
Min Kyeong Lee ◽  
...  
Keyword(s):  
United States ◽  
Emergency Department ◽  
The United States ◽  
Emergency Department Visits ◽  
Hospital Emergency Department ◽  
Hospital Emergency ◽  
Periapical Disease

Identification of patients at high risk for preventable emergency department visits and inpatient admissions after starting chemotherapy: Machine learning applied to comprehensive electronic health record data.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1511-1511
Author(s):  
Dylan J. Peterson ◽  
Nicolai P. Ostberg ◽  
Douglas W. Blayney ◽  
James D. Brooks ◽  
Tina Hernandez-Boussard
Keyword(s):  
Machine Learning ◽  
Emergency Department ◽  
Electronic Health Record ◽  
Acute Care ◽  
Cancer Care ◽  
Model Performance ◽  
Emergency Department Visits ◽  
Health Record ◽  
Patients At Risk ◽  
Ed Visits

1511 Background: Acute care use is one of the largest drivers of cancer care costs. OP-35: Admissions and Emergency Department Visits for Patients Receiving Outpatient Chemotherapy is a CMS quality measure that will affect reimbursement based on unplanned inpatient admissions (IP) and emergency department (ED) visits. Targeted measures can reduce preventable acute care use but identifying which patients might benefit remains challenging. Prior predictive models have made use of a limited subset of the data available in the Electronic Health Record (EHR). We hypothesized dense, structured EHR data could be used to train machine learning algorithms to predict risk of preventable ED and IP visits. Methods: Patients treated at Stanford Health Care and affiliated community care sites between 2013 and 2015 who met inclusion criteria for OP-35 were selected from our EHR. Preventable ED or IP visits were identified using OP-35 criteria. Demographic, diagnosis, procedure, medication, laboratory, vital sign, and healthcare utilization data generated prior to chemotherapy treatment were obtained. A random split of 80% of the cohort was used to train a logistic regression with least absolute shrinkage and selection operator regularization (LASSO) model to predict risk for acute care events within the first 180 days of chemotherapy. The remaining 20% were used to measure model performance by the Area Under the Receiver Operator Curve (AUROC). Results: 8,439 patients were included, of whom 35% had one or more preventable event within 180 days of starting chemotherapy. Our LASSO model classified patients at risk for preventable ED or IP visits with an AUROC of 0.783 (95% CI: 0.761-0.806). Model performance was better for identifying risk for IP visits than ED visits. LASSO selected 125 of 760 possible features to use when classifying patients. These included prior acute care visits, cancer stage, race, laboratory values, and a diagnosis of depression. Key features for the model are shown in the table. Conclusions: Machine learning models trained on a large number of routinely collected clinical variables can identify patients at risk for acute care events with promising accuracy. These models have the potential to improve cancer care outcomes, patient experience, and costs by allowing for targeted preventative interventions. Future work will include prospective and external validation in other healthcare systems.[Table: see text]

Epidemiologic Trends in Oculoplastics-Related Emergency Department Visits in the United States, 2006–2015

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Meleha Ahmad ◽  
Jiawei Zhao ◽  
Mustafa Iftikhar ◽  
Joseph K. Canner ◽  
Fatemeh Rajaii ◽  
...  
Keyword(s):  
United States ◽  
Emergency Department ◽  
The United States ◽  
Emergency Department Visits

Emergency Department Visits due to Scabies in the United States: A Retrospective Analysis of a Nationally Representative Emergency Department Sample

2019 ◽  
Author(s):  
Raghav Tripathi ◽  
Konrad D Knusel ◽  
Harib H Ezaldein ◽  
Jeremy S Bordeaux ◽  
Jeffrey F Scott
Keyword(s):  
United States ◽  
Emergency Department ◽  
Retrospective Analysis ◽  
The United States ◽  
Cost Of Care ◽  
Emergency Department Visits ◽  
Limited Information ◽  
Targeted Interventions ◽  
Ed Visits ◽  
Nationally Representative

Abstract Background Limited information exists regarding the burden of emergency department (ED) visits due to scabies in the United States. The goal of this study was to provide population-level estimates regarding scabies visits to American EDs. Methods This study was a retrospective analysis of the nationally representative National Emergency Department Sample from 2013 to 2015. Outcomes included adjusted odds for scabies ED visits, adjusted odds for inpatient admission due to scabies in the ED scabies population, predictors for cost of care, and seasonal/regional variation in cost and prevalence of scabies ED visits. Results Our patient population included 416 017 218 ED visits from 2013 to 2015, of which 356 267 were due to scabies (prevalence = 85.7 per 100 000 ED visits). The average annual expenditure for scabies ED visits was $67 125 780.36. The average cost of care for a scabies ED visit was $750.91 (±17.41). Patients visiting the ED for scabies were most likely to be male children from lower income quartiles and were most likely to present to the ED on weekdays in the fall, controlling for all other factors. Scabies ED patients that were male, older, insured by Medicare, from the highest income quartile, and from the Midwest/West were most likely to be admitted as inpatients. Older, higher income, Medicare patients in large Northeastern metropolitan cities had the greatest cost of care. Conclusion This study provides comprehensive nationally representative estimates of the burden of scabies ED visits on the American healthcare system. These findings are important for developing targeted interventions to decrease the incidence and burden of scabies in American EDs.

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