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Kite-Powell Aaron

Description

Florida has implemented various surveillance methods to augment existing sources of surveillance data and enhance decision making with timely evidence based assessments to guide response efforts post-hurricanes. Historically, data collected from deployed federal assets have been an integral part of this effort. However, a number of factors have made this type of surveillance challenging: logistical is- sues of field work in a post-disaster environment, the resource inten- sive manual data collection process from DMAT sites, and delayed analysis and interpretation of these data to inform decision makers. The ESSENCE-FL system is an automated and secure web-based ap- plication accessed by FDOH epidemiologists and staff at participat- ing hospitals.

Objective

The Florida Department of Health (FDOH), Bureau of Epidemi- ology, partnered with the U.S. Department of Health and Human Services (HHS) Office of the Assistant Secretary for Preparedness and Response (ASPR) to improve surveillance methods in post dis- aster or response events. A new process was implemented for con- ducting surveillance to monitor injury and illness for those presenting for care to ASPR assets such as Disaster Medical Assistance Team (DMAT) sites when they are operational in the state. The purpose of the current work was to field test and document the operational ex- perience of the newly implemented ASPR data module in ESSENCE- FL (syndromic surveillance system) to receive near real-time automated data feeds when ASPR federal assets were deployed in Florida during the 2012 Republican National Convention (RNC).

Submitted by dbedford on

Presented March 27, 2018.

During this 90-minute session, Aaron Kite-Powell, M.S., from CDC and Wayne Loschen, M.S., from JHU-APL provided an overview of tips and tricks in ESSENCE and answered questions from the audience regarding ESSENCE functions, capabilities and uses.

Description

ASPR deploys clinical assets, including an EMR system, to the ground per state requests during planned and no-notice events. The analysis of patient data collected by deployed federal personnel is an integral part of ASPR and FDOH’s surveillance efforts. However, this surveillance can be hampered by the logistical issues of field work in a post-disaster environment leading to delayed analysis and interpretation of these data to inform decision makers at the federal, state, and local levels. FDOH operates ESSENCE-FL, a multi-tiered, automated, and secure web-based application for analysis and visualization of clinical data. The system is accessible statewide by FDOH staff as well as by hospitals that participate in the system. To improve surveillance ASPR and FDOH engaged in a pilot project whereby EMR data from ASPR would be sent to FDOH in near realtime during the 2012 hurricane season and the 2012 RNC. This project is in direct support of Healthcare Preparedness Capability 6, Information Sharing, and Public Health Preparedness Capability 13, Public Health Surveillance and Epidemiological Investigation.

Objective:

U.S. Department of Health and Human Services (HHS) Office of the Assistant Secretary for Preparedness and Response (ASPR) partnered with the Florida Department of Health (FDOH), Bureau of Epidemiology, to implement a new process for the unidirectional exchange of electronic medical record (EMR) data when ASPR clinical assets are operational in the state following a disaster or other response event. The purpose of the current work was to automate the exchange of data from the ASPR electronic medical record system EMR-S into the FDOH Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE-FL) system during the 2012 Republican National Convention (RNC).

 

 

 



 

Submitted by Magou on
Description

Understanding your data is a fundamental pillar of disease surveillance success. With the increase in automated, electronic surveillance tools many public health users have begun to rely on those tools to produce reports that contain processed results to perform their daily jobs. These tools can focus on the algorithm or visualizations needed to produce the report, and can easily overlook the quality of the incoming data. The phrase “garbage in, garbage out” is often used to describe the value of reports when the incoming data is not of high quality. There is a need then, for systems and tools that help users determine the quality of incoming data.

Objective

The objective of this project was to develop visualizations and tools for public health users to determine the quality of their surveillance data. Users should be able to determine or be warned when significant changes have occurred to their data streams, such as a hospital converting from a free-text chief complaint to a pick list. Other data quality factors, such as individual variable completeness and consistency in how values are mapped to standard system selections should be available to users. Once built, these new visualizations should also be evaluated to determine their usefulness in a production disease surveillance system.

Submitted by teresa.hamby@d… on
Description

As system users develop queries within ESSENCE, they step through the user-interface to select data sources and parameters needed for their query. Then they select from the available output options (e.g., time series, table builder, data details). These activities execute a SQL query on the database, the majority of which are saved in a log so that system developers can troubleshoot problems. Secondarily, these data can be used as a form of web analytics to describe user query choices, query volume, query execution time, and develop an understanding of ESSENCE query patterns.

Objective:

The objective of this work is to describe the use and performance of the NSSP ESSENCE system by analyzing the structured query language (SQL) logs generated by users of the National Syndromic Surveillance Program'™s (NSSP) Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE).

Submitted by elamb on
Description

With increasing awareness of SyS systems, there has been a concurrent increase in demand for data from these systems – both from researchers and from the media. The opioid epidemic occurring in the United States has forced the SyS community to determine the best way to present these data in a way that makes sense while acknowledging the incompleteness and variability in how the data are collected at the hospital level and queried at the user level. While significant time and effort are spent discussing optimal queries, responsible presentation of the data - including data disclaimers - is rarely discussed within the SyS community.

Objective:

To discuss data disclaimers and caveats that are fundamental to sharing syndromic surveillance (SyS) data

Submitted by elamb on
Description

In this panel, the presenters will discuss their perspective in responding to Hurricanes Harvey and Irma. Hurricane Harvey made landfall on August 25th and over the course of 4 days dropped approximately 27 trillion gallons of water on Texas and Louisiana. The flooding that ensued was unprecedented and forced over 13,000 people into shelters. These individuals needed to have their basic needs -food, shelter, clothing, sanitation- met as well as their physical and mental health needs. The George R Brown Conference Center (GRB) and NRG Stadium Center were set up as mega-shelters to house shelterees. Hurricane Irma made landfall on September 10th in the Florida Keys as a Category 4 Hurricane. The Hurricane caused 72 deaths and forced thousands of people into shelters. These weather events created novel challenges for local response efforts. Decision makers needed timely and actionable data, including surveillance data.

Objective:

In this panel, attendees will learn about how disaster surveillance was conducted in response to Hurricanes Irma and Harvey, as well as the role of CDC at the federal level in supporting local response efforts. By hearing and discussing the challenges faced and solutions identified, attendees will be better able to respond in the event of a low-frequency/high-consequence disaster occurring within their jurisdiction.

Submitted by elamb on
Description

Overdose deaths involving opioids (i.e., opioid pain relievers and illicit opioids such as heroin) accounted for at least 63% (N = 33,091) of overdose deaths in 2015. Overdose deaths related to illicit opioids, heroin and illicitly-manufactured fentanyl, have rapidly increased since 2010. For instance, heroin overdose deaths quadrupled from 3,036 in 2010 to 12,989 in 2015. Unfortunately, timely response to emerging trends is inhibited by time lags for national data on both overdose mortality via vital statistics (8-12 months) and morbidity via hospital discharge data (over 2 years). Emergency department (ED) syndromic data can be leveraged to respond more quickly to emerging drug overdose trends as well as identify drug overdose outbreaks. CDC’s NSSP BioSense Platform collects near real-time ED data on approximately two-thirds of ED visits in the US. NSSP’s data analysis and visualization tool, Electronic Surveillance System for the Notification of Community-based Epidemics (ESSENCE), allows for tailored syndrome queries and can monitor ED visits related to heroin overdose at the local, state, regional, and national levels quicker than hospital discharge data.

Objective:

This paper analyzes emergency department syndromic data in the Centers for Disease Control and Prevention's (CDC) National Syndromic Surveillance Program’s (NSSP) BioSense Platform to understand trends in suspected heroin overdose.

Submitted by elamb on
Description

One of the more recent successes of NSSP has been the introduction of more robust data quality monitoring and reporting. However, despite the increased insight into data quality, there are still concerns about data sharing and comparisons across sites. For NSSP to be most effective, users need to feel confident in sharing data and making comparisons across sites.

Objective:

As the BioSense Platform matures and more sites submit surveillance data, many in the community have voiced concerns about comparing data across sites. Recently, a number of jurisdictions from across the country were asked to provide opioid overdose data to a news agency highlighting the epidemic. Many jurisdictions requested information on how to present syndromic surveillance data from across sites and shared concern about how the data would be interpreted. This round table will address those concerns and explore options for comparing data across sites.

Submitted by elamb on
Description

A seroprevalence survey carried out in four counties in the Tampa Bay area of Florida (Hillsborough, Pinellas, Manatee and Pasco) provided an estimate of cumulative incidence of infection due to the 2009 influenza A (H1N1) as of the end of that year’s pandemic. During the pandemic, high-level decison-makers wanted timely, credible forecasts as to the likely near-term course of the pandemic. The cumulative percentage of people who will be infected by the end of the epidemic can be estimated from the intrinsic reproductive number of the viral strain, its R0 , which can be measured early in the epidemic. If the current cumulative number of infections can be estimated, then one can determine what fraction of the eventual total number of infected people have already been infected.

Objective

To estimate the number of infections due to the novel 2009 influenza A/H1N1 virus corresponding to each ED visit for ILI in a four-county area of Florida. Knowing such ratios, one could (in future similar situations) estimate the cumulative number of infections due to a novel influenza virus in a population.

Submitted by rmathes on