scholarly journals Using routine emergency department data for syndromic surveillance of acute respiratory illness before and during the COVID-19 pandemic in Germany, week 10-2017 and 10-2021

2021 ◽  
Author(s):  
T Sonia Boender ◽  
Wei Cai ◽  
Madlen Schranz ◽  
Theresa Kocher ◽  
Birte Wagner ◽  
...  
Keyword(s):  
Emergency Department ◽  
Emergency Departments ◽  
Syndromic Surveillance ◽  
Virus Disease ◽  
Respiratory Illness ◽  
Acute Respiratory Illness ◽  
Case Definitions ◽  
Emergency Department Data ◽  
Duration Magnitude ◽  
Icd 10

Introduction: To better assess the epidemiological situation of acute respiratory illness in Germany over time, we used emergency department data for syndromic surveillance before and during the COVID-19 pandemic. Methods: We included routine attendance data from emergency departments who continuously transferred data between week 10-2017 and 10-2021, with ICD-10 codes available for >75% of the attendances. Case definitions for acute respiratory illness (ARI), severe ARI (SARI), influenza-like illness (ILI), respiratory syncytial virus disease (RSV) and Coronavirus disease 2019 (COVID-19) were based on a combination of ICD-10 codes, and/or chief complaints, sometimes combined with information on hospitalisation and age. Results: We included 1,372,958 attendances from eight emergency departments. The number of attendances dropped in March 2020, increased during summer, and declined again during the resurge of COVID-19 cases in autumn and winter of 2020/2021. A pattern of seasonality of acute respiratory infections could be observed. By using different case definitions (i.e. for ARI, SARI, ILI, RSV) both the annual influenza seasons in the years 2017-2020 and the dynamics of the COVID-19 pandemic in 2020-2021 were apparent. The absence of a flu season during the fall and winter of 2020/2021 was visible, in parallel to the resurge of COVID-19 cases. The proportion of SARI among ARI cases peaked in April-May 2020 and November 2020-January 2021. Conclusion: Syndromic surveillance using routine emergency department data has the potential to monitor the trends, timing, duration, magnitude and severity of illness caused by respiratory viruses, including both influenza and SARS-CoV-2.

scholarly journals Validation of ICD-10-CM codes for injuries complicating pregnancy, childbirth and the puerperium: a medical record review

2021 ◽  
Vol 27 (Suppl 1) ◽  
pp. i9-i12
Author(s):  
Anna Hansen ◽  
Dana Quesinberry ◽  
Peter Akpunonu ◽  
Julia Martin ◽  
Svetla Slavova
Keyword(s):  
Emergency Department ◽  
Medical Record ◽  
International Classification Of Diseases ◽  
Medical Record Review ◽  
Full Sample ◽  
Emergency Department Data ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Record Review

IntroductionThe purpose of this study was to estimate the positive predictive value (PPV) of International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes for injury, poisoning, physical or sexual assault complicating pregnancy, childbirth and the puerperium (PCP) to capture injury encounters within both hospital and emergency department claims data.MethodsA medical record review was conducted on a sample (n=157) of inpatient and emergency department claims from one Kentucky healthcare system from 2015 to 2017, with any diagnosis in the ICD-10-CM range O9A.2-O9A.4. Study clinicians reviewed medical records for the sampled cases and used an abstraction form to collect information on documented presence of injury and PCP complications. The study estimated the PPVs and the 95% CIs of O9A.2-O9A.4 codes for (1) capturing injuries and (2) capturing injuries complicating PCP.ResultsThe estimated PPV for the codes O9A.2-O9A.4 to identify injury in the full sample was 79.6% (95% CI 73.3% to 85.9%) and the PPV for capturing injuries complicating PCP was 72.0% (95% CI 65.0% to 79.0%). The estimated PPV for an inpatient principal diagnosis O9A.2-O9A.4 to capture injuries was 90.7% (95% CI 82.0% to 99.4%) and the PPV for capturing injuries complicating PCP was 88.4% (95% CI 78.4% to 98.4%). The estimated PPV for any mention of O9A.2-O9A.4 in emergency department data to capture injuries was 95.2% (95% CI 90.6% to 99.9%) and the PPV for capturing injuries complicating PCP was 81.0% (95% CI 72.4% to 89.5%).DiscussionThe O9A.2-O9A.4 codes captured high percentage true injury cases among pregnant and puerperal women.

scholarly journals Syndromic Surveillance of Emergency Department Visits for Acute Adverse Effects of Marijuana, Tri-County Health Department, Colorado, 2016-2017

2019 ◽  
Vol 134 (2) ◽  
pp. 132-140 ◽  
Author(s):  
Grace E. Marx ◽  
Yushiuan Chen ◽  
Michele Askenazi ◽  
Bernadette A. Albanese
Keyword(s):  
Emergency Department ◽  
Adverse Effects ◽  
Medical Records ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Marijuana Use ◽  
Emergency Department Visits ◽  
Diagnostic Codes ◽  
Icd 10 ◽  
Ed Visits

Objectives: In Colorado, legalization of recreational marijuana in 2014 increased public access to marijuana and might also have led to an increase in emergency department (ED) visits. We examined the validity of using syndromic surveillance data to detect marijuana-associated ED visits by comparing the performance of surveillance queries with physician-reviewed medical records. Methods: We developed queries of combinations of marijuana-specific International Classification of Diseases, Tenth Revision (ICD-10) diagnostic codes or keywords. We applied these queries to ED visit data submitted through the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE) syndromic surveillance system at 3 hospitals during 2016-2017. One physician reviewed the medical records of ED visits identified by ≥1 query and calculated the positive predictive value (PPV) of each query. We defined cases of acute adverse effects of marijuana (AAEM) as determined by the ED provider’s clinical impression during the visit. Results: Of 44 942 total ED visits, ESSENCE queries detected 453 (1%) as potential AAEM cases; a review of 422 (93%) medical records identified 188 (45%) true AAEM cases. Queries using ICD-10 diagnostic codes or keywords in the triage note identified all true AAEM cases; PPV varied by hospital from 36% to 64%. Of the 188 true AAEM cases, 109 (58%) were among men and 178 (95%) reported intentional use of marijuana. Compared with noncases of AAEM, cases were significantly more likely to be among non-Colorado residents than among Colorado residents and were significantly more likely to report edible marijuana use rather than smoked marijuana use ( P < .001). Conclusions: ICD-10 diagnostic codes and triage note keyword queries in ESSENCE, validated by medical record review, can be used to track ED visits for AAEM.

scholarly journals Assessing Definitions of Heroin Overdose in ED & EMS Data Using Hospital Billing Data

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Peter J Rock ◽  
M D Singleton
Keyword(s):  
Emergency Department ◽  
Syndromic Surveillance ◽  
Chief Complaint ◽  
Data Sources ◽  
Data Systems ◽  
Case Definitions ◽  
Billing Data ◽  
Heroin Overdose ◽  
Drug Overdoses ◽  
Hospital Administrative

Objective: The aim of this project was to assess the face validity of surveillance case definitions for heroin overdose in emergency medical services (EMS) and emergency department syndromic surveillance (SyS) data systems by comparing case counts to those found in a statewide emergency department (ED) hospital administrative billing data system.Introduction: In 2016, the Centers for Disease Control and Prevention funded 12 states, under the Enhanced State Opioid Overdose Surveillance (ESOOS) program, to utilize state Emergency Medical Services (EMS) and emergency department syndromic surveillance (SyS) data systems to increase timeliness of state data on drug overdose events. An important component of the ESOOS program is the development and validation of case definitions for drug overdoses for EMS and ED SyS data systems with a focus on small area anomaly detection. In fiscal year one of the grant Kentucky collaborated with CDC to develop case definitions for heroin and opioid overdoses for both SyS and EMS data. These drug overdose case definitions are compared between these two rapid surveillance systems, and further compared to emergency department (ED) hospital administrative claims billing data, to assess their face validity.Methods: The most recent available data were pulled from multiple hospitals in a large healthcare system serving an urban region of Kentucky. Definitions for acute heroin overdose were applied to all three sources. For SyS and ED data, definitions were queried against the same hospitals within this geographic region and aggregated to week-level totals. SyS and ED data are similar with the exception of additional textual information available in SyS (such as chief complaint). Our EMS definition of heroin overdose was loosely based on a draft definition that was produced by the Massachusetts Department of Public Health, and relies more on textual analysis versus ICD10 codes used in SyS and ED data systems. While SyS and ED used the same hospitals as the frame of selection, EMS used incidents that occurred in the approximate catchment area served by those hospitals. Weekly totals from all three data sources were plotted in R studio with LOESS-smoothed trend lines. Unsmoothed times series plots also demonstrate highly correlated trends, but the smoothed trend lines are less cluttered and easier to interpret.Results: Visual interpretation of the LOESS-smoothed trend lines shows very similar trajectories among all three sources [Fig 1]. The resultant graph demonstrates that individually, the time courses described by SyS and EMS data track closely with the one observed in ED data. The absolute counts between the three sources showed some differences, as expected. The EMS system captures a slightly different cohort that may include people that do not go to the ED (observation patients, refused transport, etc.) and SyS/ED have slightly different definitions (as ED does not include a free-text chief complaint. These types of limitations are better explored through data linkage that may or may not include medical record review to establish ground truth.Conclusions: Public health surveillance of drug overdoses has traditionally relied on ED billing data. In most states, however, there is a lag of at least several months before this data becomes available for analysis. In some jurisdictions the delay may be considerably longer. Rapid surveillance data sources may allow for more timely identification of changes in overdose patterns at the local level. In addition, SyS/EMS can be used together to confirm that a spike seen in one rapid system is confirmed within the other, with relative ease.Though the comparison is a rather simple or crude visual analysis of three data systems at a common geographic level, there is still appears to be a common pattern among the three systems. While this does not carry the validity of cross-data matched analysis, it does provide some of the utility of looking at these system collective without match; and therefore may be of use to surveillance users that may be limited by de-identified data.

scholarly journals Length of stay as quality indicator in emergency departments: analysis of determinants in the German Emergency Department Data Registry (AKTIN registry)

2022 ◽  
Author(s):  
Ronny Otto ◽  
Sabine Blaschke ◽  
Wiebke Schirrmeister ◽  
Susanne Drynda ◽  
Felix Walcher ◽  
...  
Keyword(s):  
Emergency Department ◽  
Length Of Stay ◽  
Emergency Departments ◽  
Patient Flow ◽  
Management Strategies ◽  
Organizational Factors ◽  
Related Factors ◽  
Adult Age ◽  
Emergency Department Data ◽  
Data Registry

AbstractSeveral indicators reflect the quality of care within emergency departments (ED). The length of stay (LOS) of emergency patients represents one of the most important performance measures. Determinants of LOS have not yet been evaluated in large cohorts in Germany. This study analyzed the fixed and influenceable determinants of LOS by evaluating data from the German Emergency Department Data Registry (AKTIN registry). We performed a retrospective evaluation of all adult (age ≥ 18 years) ED patients enrolled in the AKTIN registry for the year 2019. Primary outcome was LOS for the whole cohort; secondary outcomes included LOS stratified by (1) patient-related, (2) organizational-related and (3) structure-related factors. Overall, 304,606 patients from 12 EDs were included. Average LOS for all patients was 3 h 28 min (95% CI 3 h 27 min–3 h 29 min). Regardless of other variables, patients admitted to hospital stayed 64 min longer than non-admitted patients. LOS increased with patients’ age, was shorter for walk-in patients compared to medical referral, and longer for non-trauma presenting complaints. Relevant differences were also found for acuity level, day of the week, and emergency care levels. We identified different factors influencing the duration of LOS in the ED. Total LOS was dependent on patient-related factors (age), disease-related factors (presentation complaint and triage level), and organizational factors (weekday and admitted/non-admitted status). These findings are important for the development of management strategies to optimize patient flow through the ED and thus to prevent overcrowding.

scholarly journals Use of ICD-10-CM coded hospitalisation and emergency department data for injury surveillance

2021 ◽  
Vol 27 (Suppl 1) ◽  
pp. i1-i2
Author(s):  
Renee L Johnson ◽  
Holly Hedegaard ◽  
Emilia S Pasalic ◽  
Pedro D Martinez
Keyword(s):  
Emergency Department ◽  
Injury Surveillance ◽  
Emergency Department Data ◽  
Icd 10

scholarly journals A Comparison of Fever Classified Chief Complaints and Diagnoses with Recorded Body Temperatures

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Patricia Araki ◽  
Emily Kajita ◽  
Kelsey OYong ◽  
Monica Z. Luarca ◽  
Bessie Hwang ◽  
...  
Keyword(s):  
Emergency Department ◽  
Los Angeles ◽  
Syndromic Surveillance ◽  
Los Angeles County ◽  
Body Temperatures ◽  
Emergency Department Data ◽  
Chief Complaints

In an effort to evaluate patient stated "fever" chief complaints and diagnoses utilizing emergency department data from the Los Angeles County Syndromic Surveillance project, each were compared with measured patient body temperatures in the fever range.

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