Loschen Wayne

In November of 2011 BioSense 2.0 went live to provide tools for public health departments to process, store, and analyze meaningful use syndromic surveillance data. In February of 2012 ESSENCE was adapted to support meaningful use syndromic surveillance data and was installed on the Amazon GovCloud. Tarrant County Public Health Department agreed to pilot the ESSENCE system and evaluate its performance compared to a local version ESSENCE they currently used. The project determined the technical feasibility of utilizing the Internet cloud to perform detailed public health analysis, necessary changes needed to support meaningful use syndromic surveillance data, and any public health benefits that could be gained from the technology or data.

Objective:

This project represents collaboration among CDC’s BioSense Program, Tarrant County Public Health and the ESSENCE Team at the Johns Hopkins University APL. For over six months the Tarrant County Public Health Department has been sending data through the BioSense 2.0 application to a pilot version of ESSENCE on the Amazon GovCloud. This project has demonstrated the ability for local hospitals to send meaningful use syndromic surveillance data to the Internet cloud and provide public health officials tools to analyze the data both using BioSense 2.0 and ESSENCE. The presentation will describe the tools and techniques used to accomplish this, an evaluation of how the system has performed, and lessons learned for future health departments attempting similar projects.

 

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).

 

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.

Objective:

The objective of this project is to enable the ESSENCE system to read in, utilize, and export out meaningful use syndromic surveillance data using the Health Level 7 (HL7) v2.5 standard. This presentation will detail the technical hurdles with reading a meaningful use syndromic surveillance data feed containing multiple sources, deriving a common meaning from the varying uses of the standard and writing data out to a meaningful use HL7 2.5 format that can be exported to other tools, such as BioSense 2.0 (2). The presentation will also describe the technologies employed for facilitating this, such as Mirth, and will discuss how other systems could utilize these tools to also support processing meaningful use syndromic surveillance data.

Introduction:

In order to utilize the new meaningful use syndromic surveillance data sets that many public health departments are now receiving, modifications to their systems must be made. Typically this involves enabling the storage and processing of the extra fields the new standard contains. Open source software exists, such as Mirth Connect, to help with reading and interpreting the standard. However, issues with reliably reading data from one source to another arise when the standard itself is misunderstood. Systems that process this data must understand that while the data they receive is in the HL7 v2.5 standard format, the meaning of the data fields might be different from provider to provider. Additional work is necessary to sift thro

The compliance date for the ICD9-ICD10 transition is October 1, 2015. The hospitals have started the ICD9-ICD10 transition. However, not all data providers will transition the data at the same time. In order to facilitate some coherence to the data during this transition period, user interface and data processing functionalities have been developed in ESSENCE to allow usage of both classification systems simultaneously. This capability will allow users to perform ICD10- based queries across all the hospitals in their system, irrespective of the exact number of hospitals that have completed the ICD10 transition.

Objective

To help users seamlessly query and analyze data in disease surveillance systems using both ICD9 and ICD10 codes during the transition period. Additionally, the mappings between ICD9 and ICD10 codes must be flexible enough to support locally required changes based upon a user’s needs.

Knowledge Management is defined as “the process of capturing, distributing, and effectively using knowledge.” ISDS members have varying degrees of experience with public health surveillance and syndromic surveillance specifically, and will all benefit from more structured access to documentation on components related to syndromic surveillance, including but not limited to, the onboarding of facilities, data quality monitoring tools, case definitions, and data processing tools. To build a knowledge management capability, the first step is to gather initial requirements and priorities from the CoP.

Objective

The purpose of the roundtable is to seek feedback from attendees on the components needed to improve syndromic surveillance practice through access to the shared knowledge, practices, and tools of the ISDS Community of Practice (CoP).

The use of R is increasing in the public health disease surveillance community. The ISDS pre-conference workshops and newly formed R Group for Surveillance have been well attended and continue to grow in popularity. The use of R in the National Syndromic Surveillance Program (NSSP) has also been of value to many users who wish to analyze and visualize public health data using custom R scripts. This interest in R, combined with a desire from many ESSENCE users to create custom analytics and visualizations, led to a summer internship project to look into the feasibility and ways R could be integrated into ESSENCE.

Objective

The objective of this project is to give users the ability to run custom R scripts from within the ESSENCE system. This capability would allow for custom analytics and visualizations to be baked into the system for daily use. It would also provide a sandbox area for new ideas and features to be tested before being developed more fully into the ESSENCE codebase for a more seamless use in the future. The project must do this while maintaining a secure environment for public health data to reside.