Evaluation of ESSENCE in the Cloud Using Meaningful Use Syndromic Surveillance 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.

Introduction

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.

Methods

This project investigated database and visualization changes necessary to support meaningful use syndromic surveillance data in ESSENCE. It evaluated the Internet cloud environment and determined the benefits and disadvantages to using this technology as a platform for ESSENCE. This included scalability, performance, and cost analysis of the Internet cloud platform. After using the system for a period of time, the Tarrant County users evaluated the Internet cloud version of the system.

Results

Many technical adaptations to the ESSENCE system were made to support the new meaningful use syndromic surveillance elements. Several optimizations, including a new database schema and cube table structures, were developed to improve performance of ESSENCE in the Internet cloud and incorporating the meaningful use requirements. The Internet cloud platform offered many levels of performance that could alter the ESSENCE user experience. Smaller configurations allowed for 100 concurrent users to experience 16 second response times, whereas larger configurations supported experiences of 2 second response times.

Conclusions

Public health departments are dealing with new meaningful use syndromic surveillance data elements and the cost of maintaining local systems. This collaborative team have researched and evaluated tools, technologies, and solutions that can be used throughout the country.     

Using Cloud Technology to Support Monitoring During High Profile Events

Objective

In May 2012, thousands of protesters, descended on Chicago during the NATO Summit to voice their concern about social and economic inequality. Given the increased numbers of international and domestic visitors to the Windy City and the tension surrounding protesting during the summit, increased monitoring for health events within the city and Chicago metropolitan region was advised. This project represents the first use of cloud technology to support monitoring for a high profile event.

Introduction

Hospital emergency departments in Cook and surrounding counties currently send data to the Cook County Department of Public Health (CCDPH) instance of ESSENCE on CCDPH servers. The cloud instance of ESSENCE has been enhanced to receive and export all meaningful use data elements in the meaningful use format. The NATO summit provided the opportunity for a demonstration project to assess the ability of an Amazon GovCloud instance of ESSENCE to ingest and process meaningful use data, and to export meaningful use surveillance data to the Cook County Locker in BioSense 2.0.

Methods

In the three weeks leading up to the NATO Summit, HL7 data extracts were sent to BioSense 2.0 and a data feed was established to the Amazon GovCloud instance of ESSENCE. Queries specific to anticipated health events associated with the summit such as injuries, tear gas exposure, and general exposure, were developed. Several features of the cloud instance of ESSENCE enhanced the ability of CCDPH staff epidemiologists to conduct analyses, including the sharing capabilities of queries and the myESSENCE dashboard feature. The sharing capabilities within the cloud instance of ESSENCE allowed queries to be easily shared with multiple staff epidemiologists and across health jurisdictions. The myESSENCE dashboard feature was used to create dashboards of surveillance results, including time series graphs, maps, and records of interest for relevant queries, that were shared with public health staff monitoring population health during the summit. This information was used to provide situational awareness on a daily basis in the Chicago Metropolitan region.

Results

Data feeds to BioSense 2.0 and the Amazon GovCloud instance of ESSENCE were successful. The NATO Summit did not produce any remarkable public health concerns in suburban Cook County. The use of the cloud instance of ESSENCE enhanced the timeliness of generating situational awareness reports for distribution to public health partners in the Chicago Metropolitan region.

Conclusions

While further evaluation of cloud resources to conduct syndromic surveillance is warranted, use of the cloud instance of ESSENCE during the NATO Summit demonstrated the ability of the cloud to support surveillance for both routine and high profile events.     

Incorporation of School Absenteeism Data into the Maryland Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE)

Objective

The state of Maryland has incorporated 100% of its public school systems into a statewide disease surveillance system. This session will discuss the process, challenges, and best practices for expanding the ESSENCE system to include school absenteeism data as part of disease surveillance. It will also discuss the plans that Maryland has for using this new data source, as well as the potential for further expansion.

Introduction

Syndromic surveillance offers the potential for earlier detection of bioterrorism, outbreaks, and other public health emergencies than traditional disease surveillance. The Maryland Department of Health and Mental Hygiene (DHMH) Office of Preparedness and Response (OP&R) conducts syndromic surveillance using the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE). Since its inception, ESSENCE has been a vital tool for DHMH, providing continuous situational awareness for public health policy decision makers. It has been established in the public health community that syndromic surveillance data, including school absenteeism data, has efficacy in monitoring disease, and specifically, influenza activity. Schools have the potential to play a major role in the spread of disease during an epidemic. Therefore, having school absenteeism data in ESSENCE would provide the opportunity to monitor schools throughout the school year and take appropriate actions to mitigate infections and the spread of disease.

Methods

DHMH partnered with the Maryland State Department of Education (MSDE), local health departments, and local school systems to incorporate school absenteeism data into the syndromic surveillance program. There are 24 local public school systems and 24 local health departments in the state of Maryland. OP&R contacted each local school superintendent and each local health officer to arrange a joint meeting to discuss the expansion of the ESSENCE program to include school absenteeism data. Once the meetings were arranged, OP&R epidemiologists traveled to each local jurisdiction and presented their plan for the ESSENCE expansion. At each meeting were representatives from the local health department, as well as school health, school attendance, and school IT staff. This allowed all questions and concerns to be addressed from both sides. In addition to the targeted meetings and presentations, the Secretary of Health issued an executive order which required all local school systems to sign a memorandum of understanding (MOU) with DHMH. This MOU detailed the data elements to be shared with the ESSENCE program and the process by which this would be shared. While this order made data contribution mandatory, the site visits by the OP&R staff created a working relationship and partnership with the local jurisdictions. Data was collected from all public schools in the state including elementary, middle, and high schools.

Results

As of June 30, 2012, Maryland became the first state in the United States to incorporate 100% of its public school systems (1,424 schools) into ESSENCE. Each school system reports absenteeism data daily via an automated secure FTP (sFTP) transfer to DHMH. Due to its unique properties, Johns Hopkins Applied Physics Laboratory (JHUAPL) designed a new detection algorithm in ESSENCE specifically for this data source. OP&R epidemiologist review and analyze this data for disease surveillance purposes in conjunction with other data sources in ESSENCE (emergency department chief complaints, poison control center data, thermometer sales data, and over-the-counter medication sales data). Integrating school absenteeism data will provide a more complete analysis of potential public health threats. The process by which Maryland incorporated their public school systems’ data could potentially be used as a best practice for other jurisdictions. Not only was DHMH able to obtain data from all public schools in the state, but the process also enhanced collaboration between local health departments and public school systems.     

Comparing Syndromic Surveillance and Poison Center Data for Snake Bites in Missouri

Objective

This study intends to use two different surveillance systems available in Missouri to explore snake bite frequency and geographic distribution.

Introduction

In 2010, there were 4,796 snake bite exposures reported to Poison Centers nationwide (1). Health care providers frequently request help from poison centers regarding snake envenomations due to the unpredictability and complexity of prognosis and treatment. The Missouri Poison Center (MoPC) maintains a surveillance database keeping track of every phone call received. ESSENCE, a syndromic surveillance system used in Missouri, enables surveillance by chief complaint of 84 different emergency departments (ED) in Missouri (accounting for approximately 90% of all ED visits statewide). Since calling a poison center is voluntary for health care providers, poison center data is most likely an underestimation of the true frequency of snake envenomations. Comparing MoPC and ESSENCE data for snake envenomations would enable the MoPC to have a more accurate depiction of snake bite frequency in Missouri and to see where future outreach of poison center awareness should be focused.

Methods

Archived data from Toxicall®, the MoPC surveillance system, was used to query the total number of snake bite cases from 01/01/2007 until 12/31/2011 called into the MoPC center by hospitals that also participate ESSENCE. Next, ESSENCE data was used to estimate the total number of snake envenomations presenting to EDs in Missouri. This was accomplished using the same date range as well as searching for key terms in the chief complaints that would signify a snake bite. The results of each datasearch were compared and contrasted by Missouri region.

Results

The Toxicall® search showed a total of 324 snake bite cases. The initial ESSENCE data query showed a total of 1983 snake bite cases. After certain data exclusions, there was a total of 1763 ESSENCE snake bite visits. This suggests that approximately 18% of all snake bite visits reported in Missouri ESSENCE were called into the MoPC. The results are demonstrated by Missouri region in Figure 1. This figure also shows that the greatest number of ESSENCE visits for snake bites were reported by Southwest region hospitals whereas the Eastern region hospitals placed the greatest number of calls to MoPC regarding snake bites.Open in a separate windowFigure 1:ESSENCE Snake Bites Cases Compared to Toxicall® Snake Bite Cases in Missouri by Region

Conclusions

The total number of snake bite cases from Missouri ESSENCE ED visits is much greater than the number of snake bites cases called into the MoPC by ESSENCE participating hospitals. This underutilization of the poison center demonstrates the increased need for awareness of the MoPC’s free services. In Missouri, the MoPC should target hospitals in the Southwest region for outreach in particular based on these findings. Poison centers are staffed by individuals trained in all types of poisonings and maintain a list of consulting physicians throughout the United States experienced in management and treatment of venomous snake bites (2). Any healthcare facility would benefit from MoPC assistance. Finally, syndromic surveillance allows for quick and easy data compilation, however there are some difficulties when attempting to search for a particular condition. Communication and partnership between two different public health organizations will be beneficial toward future public health studies.     

Update from CDC’s Public Health Surveillance & Informatics Program Office (PHSIPO)

Objective

To provide updates on current activities and future directions for the National Notifiable Diseases Surveillance System (NNDSS), BioSense 2.0, and the Behavioral Risk Factor Surveillance System (BRFSS) and on the role of PHSIPO as the “home” at CDC for addressing cross-cutting issues in surveillance and informatics practice.

Introduction

The practice of public health surveillance is evolving as electronic health records (EHRs) and automated laboratory information systems are increasing adopted, as new approaches for health information exchange are employed, and as new health information standards affect the entire cascade of surveillance information flow. These trends have been accelerated by the Federal program to promote the Meaningful Use of electronic health records, which includes explicit population health objectives. The growing use of Internet “cloud” technology provides new opportunities for improving information sharing and for reducing surveillance costs. Potential benefits include not only faster and more complete surveillance but also new opportunities for providing population health information back to clinicians.For public health surveys, new Internet-based sampling and survey methods hold the promise of complementing existing telephone-based surveys, which have been plagued by declining response rates despite the addition of cell-phone sampling. While new technologies hold promise for improving surveillance practice, there are multiple challenges, including constraints on public health budgets and the workforce. This panel will explore how PHSIPO is addressing these opportunities and challenges.

Methods

Panelists will provide updates on 1) PHSIPO’s role in engaging health departments, the organizations that represent them, and CDC programs in shaping national policies for implementing the Meaningful Use program, 2) how the BioSense 2.0 program is supporting growth in syndromic surveillance capacity, including its partnership with ISDS in developing standards for syndromic surveillance as part of Meaningful Use, 3) improvements that are underway in strengthening the NNDSS, including efforts to improve CDC’s support for health department disease reporting systems and to develop a “shared services” approach that could provide a platform for streamlining the exchange of information between health departments and CDC, 4) pilot development of Internet-based panels of survey volunteers to supplement existing telephone-based sampling in the BRFSS and of approaches to extend BRFSS survey information through consent-based linkage of survey responses to selected measures recorded in respondents’ EHRs.

Results

Potential questions or discussion points that might arise include: What can or should be done to assure that the population health objectives of Meaningful Use are fulfilled? What are the lessons learned to date in leveraging investments in the Meaningful Use of EHRs to improve disease reporting and syndromic surveillance systems? What are the next steps in developing BioSense 2.0 to assure that it leads to strengthened surveillance capacity at both state/local and regional/national levels? How can insights from the BioSense redesign be applied to improve case reporting and other surveillance capacities? What is CDC doing to address states’ concerns about the growing number of CDC surveillance systems? How will national discussions about the future of public health affect the future surveillance practice? What can be done to assure the ongoing representativeness of population health surveys? Is it feasible to link BRFSS responses to information obtained from EHRs? How can data from surveillance become part of the real-time evidence base for clinical decision making?

Conclusions

The intended outcome of the panel is to foster a conversation between the panelists and the audience, to inform the audience about recent developments in PHSIPO, to obtain insights from the audience about innovations and ideas arising from their experience, and to generate new ideas for approaches to meeting the needs of public health for surveillance information.     

Syndromic Surveillance from a Local Perspective – A Review of the Literature

Objective

Review of the origins and evolution of the field of syndromic surveillance. Compare the goals and objectives of public health surveillance and syndromic surveillance in particular. Assess the science and practice of syndromic surveillance in the context of public health and national security priorities. Evaluate syndromic surveillance in practice, using case studies from the perspective of a local public health department.

Introduction

Public health disease surveillance is defined as the ongoing systematic collection, analysis and interpretation of health data for use in the planning, implementation and evaluation of public health, with the overarching goal of providing information to government and the public to improve public health actions and guidance [1,2]. Since the 1950s, the goals and objectives of disease surveillance have remained consistent [1]. However, the systems and processes have changed dramatically due to advances in information and communication technology, and the availability of electronic health data [2,3]. At the intersection of public health, national security and health information technology emerged the practice of syndromic surveillance [3].

Methods

To better understand the current state of the field, a review of the literature on syndromic surveillance was conducted: topics and keywords searched through PubMed and Google Scholar included biosurveillance, bioterrorism detection, computerized surveillance, electronic disease surveillance, situational awareness and syndromic surveillance, covering the areas of practice, research, preparedness and policy. This literature was compared with literature on traditional epidemiologic and public health surveillance. Definitions, objectives, methods and evaluation findings presented in the literature were assessed with a focus on their relevance from a local perspective, particularly as related to syndromic surveillance systems and methods used by the New York City Department of Health and Mental Hygiene in the areas of development, implementation, evaluation, public health practice and epidemiological research.

Results

A decade ago, the objective of syndromic surveillance was focused on outbreak and bioterrorism early-event detection (EED). While there have been clear recommendations for evaluation of syndromic surveillance systems and methods, the original detection paradigm for syndromic surveillance has not been adequately evaluated in practice, nor tested by real world events (ie, the systems have largely not ‘detected’ events of public health concern). In the absence of rigorous evaluation, the rationale and objectives for syndromic surveillance have broadened from outbreak and bioterrorism EED, to include all causes and hazards, and to encompass all data and analyses needed to achieve “situational awareness”, not simply detection. To evaluate current practices and provide meaningful guidance for local syndromic surveillance efforts, it is important to understand the emergence of the field in the broader context of public health disease surveillance. And it is important to recognize how the original stated objectives of EED have shifted in relation to actual evaluation, recommendation, standardization and implementation of syndromic systems at the local level.

Conclusions

Since 2001, the field of syndromic surveillance has rapidly expanded, following the dual requirements of national security and public health practice. The original objective of early outbreak or bioterrorism event detection remains a core objective of syndromic surveillance, and systems need to be rigorously evaluated through comparison of consistent methods and metrics, and public health outcomes. The broadened mandate for all-cause situation awareness needs to be focused into measureable public health surveillance outcomes and objectives that are consistent with established public health surveillance objectives and relevant to the local practice of public health [2].     

Integration of syndromic surveillance data into public health practice at state and local levels in North Carolina

Objectives

We sought to describe the integration of syndromic surveillance data into daily surveillance practice at local health departments (LHDs) and make recommendations for the effective integration of syndromic and reportable disease data for public health use.

Methods

Structured interviews were conducted with local health directors and communicable disease nursing staff from a stratified random sample of LHDs from May through September 2009. Interviews captured information on direct access to the North Carolina syndromic surveillance system and on the use of syndromic surveillance information for outbreak management, program management, and the creation of reports. We analyzed syndromic surveillance system data to assess the number of signals resulting in a public health response.

Results

Syndromic surveillance data were used for outbreak investigation (19% of respondents) and program management and report writing (43% of respondents); a minority reported use of both syndromic and reportable disease data for these purposes (15% and 23%, respectively). Receiving data from frequent system users was associated with using data for these purposes (p=0.016 and p=0.033, respectively, for syndromic and reportable disease data). A small proportion of signals (<25%) resulted in a public health response.

Conclusions

Use of syndromic surveillance data by North Carolina local public health authorities resulted in meaningful public health action, including both case investigation and program management. While useful, the syndromic surveillance data system was oriented toward sensitivity rather than efficiency. Successful incorporation of new surveillance data is likely to require systems that are oriented toward efficiency.Effective use of surveillance data is essential to good public health practice. In recent years, public health agencies have experienced a significant increase in the amount of data available for surveillance (e.g., data used for syndromic surveillance), and this increase is likely to continue. For example, the federal Health Information Technology for Economic and Clinical Health Act (HITECH Act) supports forwarding medical record data to public health agencies. Published work demonstrates that better data are needed for communicable disease surveillance; communicable disease reporting is not complete,¹ and many cases are reported later than is necessary for public health action.² While the medical record data that may be provided to public health have the potential to improve completeness and timeliness, these datasets are likely to have many records that are not usable for public health purposes.³ Furthermore, limited staff are available to review these data.^4,5 Effective use of these new data for public health surveillance will require efficient identification of and access to the usable data elements present in new datasets.The implementation of syndromic surveillance is an example of the incorporation of new data sources. Syndromic surveillance systems were established to facilitate early detection of events requiring a rapid response, such as outbreaks caused by bioterrorism agents. Events that may require public health intervention are identified using aberration detection algorithms and individual record review. Most states have a system of this type,⁶ and their value for public health event detection and characterization has been demonstrated.^6–10 Lessons learned from attempts to integrate syndromic data for public health surveillance and response can inform future management of new data.While syndromic surveillance data can be valuable to public health practice, the design of these systems frequently limits their use to jurisdictions with greater capacity. Alerts created by system algorithms are often of low positive predictive value,^11,12 and these systems can require a high level of staff time for detecting events that require public health action.⁸ Therefore, syndromic surveillance data are most commonly used by state and large city public health departments that have enough staff time for reviewing alerts and individual case records.^6,13,14 Although these data can be useful to health departments of all sizes, little is known about how best to make these data usable in situations with limited surveillance staff. The use of syndromic surveillance data in smaller population settings, such as most local health departments (LHDs), has not been described.North Carolina can provide an example of the integration of syndromic surveillance data into public health surveillance practice. Current electronic surveillance for communicable disease in the state includes a population-based syndromic surveillance system, the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT), and a population-based reportable communicable disease surveillance system, the North Carolina Electronic Disease Surveillance System (NC EDSS). Both syndromic and reportable disease data have been used for public health surveillance since 2006. NC DETECT use is the responsibility of syndromic surveillance staff, which includes two state-level epidemiologists and 11 hospital-based epidemiologists. All other public health agency staff may use NC DETECT. NC EDSS use is required for and restricted to staff responsible for communicable disease reporting at state and local levels.The objectives of this study were to quantitatively assess the use of syndromic surveillance data at state and local public health agencies in North Carolina, to describe how syndromic surveillance is incorporated into public health practice in the state, and to make recommendations for the effective integration of syndromic and reportable disease data for public health use.     

Enhanced Disease Surveillance during the 2012 Republican National Convention,Tampa, FL

Objective

To describe disease and illness surveillance utilized during the 2012 Republican National Convention (RNC) held August 26–30, 2012 in Tampa, FL.

Introduction

While the Tampa Bay Area has previously hosted other high profile events that required heightened disease surveillance (e.g., two Super Bowls), the 2012 RNC marked the first national special security event (NSSE) held in Florida. The Hillsborough County Health Department (HCHD), in conjunction with the Pinellas County Health Department (PinCHD) coordinated disease surveillance activities during this time frame. This presentation will focus of the disease surveillance efforts of the Hillsborough County Health Department during the 2012 RNC.In addition to the surveillance systems that are used routinely, the HCHD Epidemiology Program implemented additional systems designed to rapidly detect individual cases and outbreaks of public health importance. The short duration of RNC, coupled with the large number of visitors to our area, provided additional surveillance challenges.Tropical Storm Isaac, which threatened Tampa in the days leading up to RNC, and an overwhelming law enforcement presence likely dissuaded many protestors from coming to Tampa. As a result, a tiny fraction of the number of protestors that were expected actually showed up.

Methods

Our normal daily analysis of the emergency department (ED) data using the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) was expanded to look in detail at ED volumes and chief complaints of those patients who live outside of a 5-county Tampa Bay area. This analysis used patient zip code to determine place of residence. Additionally, ESSENCE queries were utilized to look for heat, tear gas, and RNC related exposures. The ESSENCE system also receives Poison Control data every 15 minutes. Expanded analyses of the Poison Control data were conducted as well. Two Disaster Medical Assistance Teams (DMATs) were deployed in Tampa during the RNC. Data was collected electronically and transmitted through ESSENCE as well.The HCHD also asked infection preventionists, health care providers, hotels, labs, and Mosquito Control to lower their reporting threshold to us during the RNC period. We provided updates to all our partners with respect to diseases and outbreaks of public health importance occurring in our county.

Results

No epidemiologic events linked to the RNC were detected through the HCHD’s enhanced surveillance that was conducted. Decreased patient volumes were seen during the RNC at our EDs closest to the convention site. No significant increases in ED visits from outside of our 5-county area were noted during the RNC. Urgent care centers reported seeing patients associated with the RNC for a variety of reasons including respiratory and gastrointestinal illness. DMAT surveillance showed mainly routine visits but four secret service agents did seek care for respiratory illness during the convention.

Conclusions

Substantial time and resources were devoted to disease surveillance in the 6 months leading up to the RNC and during the event. While no epidemiologic events were detected, the public health surveillance infrastructure has clearly been strengthened in our county. We are receiving our ED syndromic data, from many of our hospitals, every two hours as opposed to every day. We have established relationships with our urgent case centers and hope to begin receiving urgent care center data on a daily basis in the near future. Receiving DMAT data through ESSENCE could prove very useful in the future, especially in Florida where hurricanes are always a threat. Lastly the improved relationships with our health care providers should be beneficial as we move forward.     

Utility of Syndromic Surveillance Using Novel Clinical Data Sources

Objective

To document the current evidence base for the use of electronic health record (EHR) data for syndromic surveillance using emergency department, urgent care clinic, hospital inpatient, and ambulatory clinical care data.

Introduction

Historically, syndromic surveillance has primarily involved the use of near real-time data sent from hospital emergency department (EDs) and urgent care (UC) clinics to public health agencies. The use of data from inpatient and ambulatory settings is now gaining interest and support throughout the United States, largely as a result of the Stage 2 and 3 Meaningful Use regulations [1]. Questions regarding the feasibility and utility of applying a syndromic approach to these data sources are hampering the development of systems to collect, analyze, and share this potentially valuable information. Solidifying the evidence base and communicating the results to the public health surveillance community may help to initiate and build support for using these data to advance surveillance functions.

Methods

We conducted a literature search in the published and grey literature that scanned for relevant articles in the Google Scholar, Pub Med, and EBSCO Information Services databases. Search terms included: “inpatient/ambulatory electronic health record”; “ambulatory/inpatient/hospital/outpatient/chronic disease syndromic surveillance”; and “EHR syndromic surveillance”. Information gleaned from each article included data use, data elements extracted, and data quality indicators. In addition, several stakeholders who provided input on the September 2012 ISDS Recommendations [2] also provided articles that were incorporated into the literature review.ISDS also invited speakers from existing inpatient and ambulatory syndromic surveillance systems to give webinar presentations on how they are using data from these novel sources.

Results

The number of public health agencies (PHAs) routinely receiving ambulatory and inpatient syndromic surveillance data is substantially smaller than the number receiving ED and UC data. Some health departments, private medical organizations (including HMOs), and researchers are conducting syndromic surveillance and related research with health data captured in these clinical settings [2].In inpatient settings, many of the necessary infrastructure and analytic tools are already in place. Syndromic surveillance with inpatient data has been used for a range of innovative uses, from monitoring trends in myocardial infarction in association with risk factors for cardiovascular disease [3] to tracking changes in incident-related hospitalizations following the 2011 Joplin, Missouri tornado [3].In contrast, ambulatory systems face a need for new infrastructure, as well as pose a data volume challenge. The existing systems vary in how they address data volume and what types of encounters they capture. Ambulatory data has been used for a variety of uses, from monitoring gastrointestinal infectious disease [3], to monitoring behavioral health trends in a population, while protecting personal identities [4].

Conclusions

The existing syndromic surveillance systems and substantial research in the area indicate an interest in the public health community in using hospital inpatient and ambulatory clinical care data in new and innovative ways. However, before inpatient and ambulatory syndromic surveillance systems can be effectively utilized on a large scale, the gaps in knowledge and the barriers to system development must be addressed. Though the potential use cases are well documented, the generalizability to other settings requires additional research, workforce development, and investment.     

Use of BioSense for Rapid Assessment of the Safety of Medical Countermeasures

Objective

To conduct an initial examination of the potential use of BioSense data to monitor and rapidly assess the safety of medical countermeasures (MCM) used for prevention or treatment of adverse health effects of biological, chemical, and radiation exposures during a public health emergency.

Introduction

BioSense is a national human health surveillance system for disease detection, monitoring, and situation awareness through near real-time access to existing electronic healthcare encounter information, including information from hospital emergency departments (EDs). MCM include antibiotics, antivirals, antidotes, antitoxins, vaccinations, nuclide-binding agents, and other medications. Although some MCM have been extensively evaluated and have FDA approval, many do not (1). Current FDA and CDC systems that monitor drug and vaccine safety have limited ability to monitor MCM safety, and in particular to conduct rapid assessments during an emergency (1).

Methods

To provide a preliminary assessment of the use of BioSense for this purpose, we reviewed selected publications evaluating the use of electronic health records (EHRs) to monitor safety of drugs and vaccinations (medications), focusing particularly on systematic reviews, reviewed BioSense data elements, and consulted with a number of subject matter experts.

Results

More than 40 studies have examined use of EHR data to monitor adverse effects (AEs) of medications using administrative, laboratory, and pharmacy records from inpatient- and out-patient settings, including EDs (2–4). To identify AEs, investigators have used diagnostic codes; administration of antidotes, laboratory measures of drug levels and of biologic response, text searches of unstructured clinical notes, and combinations of those data elements. BioSense ED data include chief complaint text, triage notes, text diagnosis, as well as diagnostic and medical procedure codes.Investigations used a variety of study designs in various populations and settings; examined a wide range of medications, vaccinations, and AEs; and developed a diverse set of analytic algorithms to search EHR data to detect and signal AEs (2–4). Most research has been done on FDA-approved medications. Most studies used EHR data to identify individuals using specific medications and then searched for potential AEs identified from previous research. None of the studies investigated use of EHR data to monitor safety when records of an individual’s medication use could not be linked to that individual’s records of AEs. BioSense data could be used for AE detection, but linking AEs to MCM use would require follow-back investigation. Since there is limited research on AEs of some MCM, there would be limited information to guide identification of potential AEs.Performance characteristics of the AE monitoring systems have been mixed with reported sensitivities ranging from 40–90%; specificities from 1% to 90%, and positive predictive values from < 1% to 64%, depending on the medication, AE and other characteristics of the study (2, 4). However, the small numbers of studies with common characteristics has limited the ability of reviewers to determine which types of systems have better performance for different medications and AEs.Some experts suggest that data in BioSense, might contribute to safety surveillance of MCM. They also caution that poor predictive values and high rates of false positives reported in the literature raise concerns about burden to those conducting investigations in response to AE alerts, particularly in the context of a public health emergency.

Conclusions

These findings suggest that BioSense data could potentially contribute to rapid identification of safety issues for MCM and that some methods from published research could be applicable to the use of BioSense for this purpose. However, such use would require careful development and evaluation.     

Adapting Syndromic Surveillance Systems to Increase Value to Local Health Departments

Objective

Our objective was to describe changes in use following syndromic surveillance system modifications and assess the effectiveness of these modifications.

Introduction

Syndromic surveillance systems offer richer understanding of population health. However, because of their complexity, they are less used at small public health agencies, such as many local health departments (LHDs). The evolution of these systems has included modifying user interfaces for more efficient and effective use at the local level. The North Carolina Preparedness and Emergency Response Research Center previously evaluated use of syndromic surveillance information at LHDs in North Carolina. Since this time, both the NC DETECT system and distribution of syndromic surveillance information by the state public health agency have changed. This work describes use following these changes.

Methods

Data from NC DETECT were used to assess the number of users and usage time. Staff from 14 NC LHDs in 2009 and from 39 LHDs in 2012 were surveyed (May–August of 2009 and June of 2012) to gather information on the mode of access to syndromic surveillance information and how this information was used. Data were analyzed to assess the link between the mode of access and use of syndromic surveillance data.

Results

System changes made between 2009 and 2012 included the creation of “dashboards” (Figure 1) which present users with LHD-specific charts and graphs upon login and increases in the distribution of syndromic surveillance information by the state public health agency. The number of LHD-based NC DETECT system users increased from 99 in 2009 to 175 in 2012. Sixty-two of 72 respondents completed the 2012 survey (86%). Syndromic surveillance information was used in 28/40 LHDs (70%) for key public health tasks. Among 20 NC EDSS leads reporting an outbreak in the past year, 25% reported using data from NC DETECT for outbreak response, compared to 23% in 2009 (Figure 2). Among 30 responding NC EDSS leads, 57% reported using data from NC DETECT to respond to seasonal events such as heat-related illness or influenza, compared to 46% in 2009. NC DETECT data were reported to have been used for program management by 30% (compared to 25% in 2009), and to have been used in reports by 33% (compared to 23% in 2009).Open in a separate windowFigure 1:NC DETECT dashboardsOpen in a separate windowFigure 2:Uses of syndromic surveillance information, communicable disease staff 2009 (13 LHDs) and 2012 (31 LHDs)

Conclusions

Changes in how syndromic surveillance information was distributed supported modest increases in use in LHDs. Because use of syndromic surveillance data at smaller LHDs is rare, these modest increases are important indicators of effective modification of the NC syndromic surveillance system.     

Syndromic Surveillance for Outbreak Detection and Investigation

Objective

For the purpose of developing a national system of outbreak surveillance, we compared local outbreak signals in three sources of syndromic data – telephone triage of acute gastroenteritis (Swedish Health Care Direct 1177), web queries about symptoms of gastrointestinal illness (Stockholm County’s website for healthcare information), and OTC pharmacy sales of anti-diarrhea medication.

Introduction

A large part of the applied research on syndromic surveillance targets seasonal epidemics, e.g. influenza, winter vomiting disease, rotavirus and RSV, in particular when dealing with preclinical indicators, e.g. web traffic (Hulth et al, 2009). The research on local outbreak surveillance is more limited. Two studies of teletriage data (NHS Direct) have shown positive and negative results respectively (Cooper et al, 2006; Smith et al, 2008). Studies of OTC pharmacy sales have reported similar equivocal performance (Edge et al, 2004; Kirian and Weintraub, 2010). As far as we know, no systematic comparison of data sources with respect to multiple point-source outbreaks has so far been published (cf. Buckeridge, 2007). In the current study, we evaluated the potential of three data sources for syndromic surveillance by analyzing the correspondence between signal properties and point-source outbreak characteristics.

Methods

The extracted data streams were compared with respect to nine waterborne and foodborne outbreaks in Sweden in 2007–2011. The analysis consisted of three parts: (1) the validation of outbreak signals by comparing signal counts during outbreak and baseline periods, (2) the estimation of detection limits by modeling signal rates (signal-to-case ratios), and (3) the evaluation of early warning potential by means of signal detection analysis.

Results

The four largest outbreaks generated strong and clear outbreak signals in the 1177 triage data. The two largest outbreaks produced signals in OTC sales of anti-diarrhea. No signals could be identified in the web query data. The outbreak detection limit based on triage data was about 100–1000 cases. For two outbreaks, triage data on diarrhea provided outbreak signals early on, weeks and months respectively, potentially serving the purpose of early warning.

Conclusions

The sensitivity and specificity were highest for telephone triage data on patient symptoms. It provided the most promising source of syndromic data for surveillance of point-source outbreaks. Currently, a project has been initialized to develop and implement a national system in Sweden for daily syndromic surveillance based on 1177 Health Care Direct, supporting regional and local outbreak detection and investigation.     

Evaluating Usefulness of Maine’s Syndromic Surveillance System for Hospitals, 2012

Objective

To assess the usefulness and acceptability of Maine’s syndromic surveillance system among hospitals who currently participate.

Introduction

Maine has been conducting syndromic surveillance since 2007 using the Early Aberration Reporting System (EARS). An evaluation of the syndromic surveillance system was conducted to determine if system objectives are being met, assess the system’s usefulness, and identify areas for improvement. According to CDC’s Guidelines for Evaluating Public Health Surveillance Systems, a surveillance system is useful if it contributes to the timely prevention and control of adverse health events. Acceptability includes the willingness of participants to report surveillance data; participation or reporting rate; and completeness of data.

Methods

A survey was created in 2012 to measure usefulness and acceptability among hospital partners who submit emergency department data to Maine CDC for syndromic surveillance. Currently, 24 of Maine’s 37 emergency departments collect syndromic surveillance data and 20 of those receive a weekly syndromic surveillance report from Maine CDC. The survey was included with the report on August 14, 2012, and hospitals were given two weeks for completion. The survey included questions about how useful hospitals find syndromic surveillance and how data is shared back with the hospitals; which syndromes are most and least useful; and chief complaint data collection at individual hospitals.

Results

The survey was completed by 13 out of 22 emergency departments (59% participation rate), and six out of 13 respondents (46%) completed the entire survey. The factors reported as having an influence on a hospital’s decision to submit data for syndromic surveillance were: public health importance of events (6 respondents) and assurance of privacy/confidentiality (5 respondents). The majority of respondents (5 respondents) reported that there are no factors that limit their ability to send emergency department data. Among hospitals that did report factors that limit their ability to send data, lack of information technology support in the hospital (2 respondents) and manually entering data/lack of electronic health records (1 respondent) were the most frequently reported. Six out of seven hospitals who answered (86°%) reported the current method of sharing syndromic surveillance data on a weekly basis, including a statewide data summary, as useful. Respondents also recommended that data be shared back with participants using 30-day line graphs for each syndrome (4 respondents). The three syndromes respondents found most useful were influenzalike illness (7 respondents), gastrointestinal (5 respondents), and respiratory (5 respondents). The three syndromes respondents found least useful were the broad heat syndrome (4 respondents), the narrow heat syndrome (4 respondents), and the other syndrome that captures all visits not classified into any syndrome (4 respondents). Chief complaint data, which is used to classify emergency department visits into syndromes, is most often recorded by a drop-menu (4 respondents).

Conclusions

With a low survey completion rate, it is difficult to generalize responses to all hospitals who participate in syndromic surveillance. Hospitals that did not respond to or complete the survey will be followed up with to determine their reasons for not doing so, as this may be useful information. In general, those who responded have more factors that influence them to contribute to syndromic surveillance than factors that hinder them. Most hospitals find the current method of sharing data back with the hospitals useful. Also, it is advantageous to know which syndromes the hospitals find most useful, as they are the entities that collect and report the data. Opinions differ among system users, which is why it is important to evaluate a system throughout all points of interaction.     

Evaluating Utility of Cold-Injury Syndromic Surveillance Data in New York City

Objective

1) Develop cold exposure-related injury syndromic case definitions 2) use historical data to compare trends among cases identified in syndromic surveillance and cases identified in NY Statewide Planning and Research Cooperative System (SPARCS) hospital discharge data to evaluate representativeness and 3) develop regression models to examine relationships with cold weather conditions, and compare relationships across case definitions and data sources.

Introduction

Cold weather exposure-related injuries range from hypothermia to less severe conditions such as frost bite, trench foot, and chilblains, which are all preventable causes of mortality and morbidity. In recent years, NYC has successfully used syndromic surveillance of heat-related ED visits to inform emergency response during heat waves. Similar timely surveillance of cold-exposure related injuries could also inform public health protection measures during severe winter weather or cold season power outages. We conducted a retrospective analysis to compare hypothermia and cold-injury patient case characteristics, as well as temporal and meteorological correlates, between syndromic surveillance data and hospital discharge data.

Methods

Using chief complaint key words, we developed syndromic case definitions for 1) hypothermia only and 2) all injury caused by environmental cold exposure. Case definitions were applied to an archive of 2008–2010 cold season (October to April) syndromic surveillance data reported from a subset of NYC emergency departments (ED SS), representing 95% of all ED visits in NYC. Relevant ICD-9 codes (991, E901.0, E901.8, E901.9, E988.3) were applied to ED discharge data (ED Dx) to detect hypothermia and cold injury cases. Age, gender, and alcohol involvement were compared using tests of proportion to determine whether characteristics of cases identified through ED SS were representative of cases identified in ED Dx data. Poisson regression models were fit to estimate the relation of daily ED SS and Dx counts with daily temperature, snow depth, and other weather conditions. Models were adjusted for month, holiday, day of week, and year to account for potential temporal confounding.

Results

Fewer hypothermia and cold injury cases were detected with ED SS than with ED Dx but the two populations did not differ significantly with respect to age and sex. From 2008–2010, there were 292 hypothermia cases with an average annual rate of 1.2 per 100,000 people, and 445 cold injury cases (1.8 per 100,000) identified in ED SS data. Over the same time period, there were 566 hypothermia cases (2.3 per 100,000) and 933 cold injury cases (3.7 per 100,000) identified in ED Dx data. Daily counts of hypothermia and cold injury were correlated across data sources. In preliminary analyses using both case definitions, minimum daily temperature was associated with increases in daily ED SS and ED Dx counts. Mean daily snow depth was associated with ED SS and ED Dx cold injury cases, although not with hypothermia counts. Risk increased at lower temperatures for both case definitions.

Conclusions

There were no meaningful differences between ED SS and ED Dx weather models. Minimum temperature is associated with both case definitions. Snow depth is associated with cold injury. Daily minimum temperature and mean snow depth are potentially useful in determining timing of surveillance. Syndromic surveillance data are a timely means for monitoring hypothermia and other cold-related injuries, and could provide health departments with useful information during severe winter weather to guide prevention.     

Short message service sentinel surveillance of influenza-like illness in Madagascar, 2008-2012

Problem

The revision of the International Health Regulations (IHR) and the threat of influenza pandemics and other disease outbreaks with a major impact on developing countries have prompted bolstered surveillance capacity, particularly in low-resource settings.

Approach

Surveillance tools with well-timed, validated data are necessary to strengthen disease surveillance. In 2007 Madagascar implemented a sentinel surveillance system for influenza-like illness (ILI) based on data collected from sentinel general practitioners.

Setting

Before 2007, Madagascar’s disease surveillance was based on the passive collection and reporting of data aggregated weekly or monthly. The system did not allow for the early identification of outbreaks or unexpected increases in disease incidence.

Relevant changes

An innovative case reporting system based on the use of cell phones was launched in March 2007. Encrypted short message service, which costs less than 2 United States dollars per month per health centre, is now being used by sentinel general practitioners for the daily reporting of cases of fever and ILI seen in their practices. To validate the daily data, practitioners also report epidemiological and clinical data (e.g. new febrile patient’s sex, age, visit date, symptoms) weekly to the epidemiologists on the research team using special patient forms.

Lessons learnt

Madagascar’s sentinel ILI surveillance system represents the country’s first nationwide “real-time” surveillance system. It has proved the feasibility of improving disease surveillance capacity through innovative systems despite resource constraints. This type of syndromic surveillance can detect unexpected increases in the incidence of ILI and other syndromic illnesses.     

A Web-based Electronic Health Record System for National Surveillance

Objective

This showcase aims to demonstrate the viability of Practice Fusion’s web-based electronic health record system for national surveillance. Practice Fusion also wishes to provide aggregate data to public health departments for surveillance for free. This showcase also hopes to engage those potential partners around uses of the company’s research database.

Introduction

Practice Fusion is a web-based electronic health record system with over 150,000 medical professional users treating over 50 million patients. The company focuses on small, ambulatory practices and is predominately comprised of practices in the field of primary care. The user base makes it an ideal system for public health surveillance. The Research Division has undertaken pilot projects to demonstrate the viability of using the data for surveillance for acute diseases, like influenza-like illness, chronic diseases, like diabetes, and risk factors, like hypertension.

Methods

Surveillance systems based on electronic health records have clear advantages over case based reporting, but the majority of those systems are limited to the small geographical area affiliated with the hospital or health plan associated with the project. Practice Fusion has coverage in all 50 states and runs on a single, multi-tenant database making comparisons across those states and the localities within them immediately feasible. The company wishes to engage the organizations represented at ISDS in order to advance public health surveillance using the research database. It is very difficult to obtain electronic health record data currently, but with the appropriate data use agreement Practice Fusion believes that it is a moral imperative to use its aggregate data for surveillance. The Research Division has developed methods for the surveillance of influenza-like illness with its system and comparisons to the CDC have proven its viability.

Conclusions

By comparing trends and levels of influenza-like illness generated from Practice Fusion’s research database to Google Flu Trends and the gold standard estimates produced by the CDC, web-based electronic health record systems have proved to be a viable foundation for syndromic surveillance. The implementation of the system also shows that case definitions for surveillance need not be overly simplistic if they do not require cases to be submitted from physicians, but rather can be programmed to be identified through automated algorithms.     

Use of Syndromic Surveillance Information for Expanded Assessment of Wildfire Disaster

Objective

This presentation describes how syndromic surveillance information was combined with fire emission information and spatio-temporal fire occurrence data to evaluate, model and forecast climate change impacts on future fire scenarios.

Introduction

Syndromic surveillance information can be a useful for the early recognition of outbreaks, acute public health events and in response to natural disasters. Inhalation of particulate matter from wildland fire smoke has been linked to various acute respiratory and cardiovascular health effects. Historically, wildfire disasters occur across Southern California on a recurring basis. During 2003 and 2007, wildfires ravaged San Diego County and resulted in historic levels of population evacuation, significant impact on air quality and loss of lives and infrastructure. In 2011, the National Institutes of Health-National Institute of Environmental Health Sciences awarded Michigan Tech Research Institute a grant to address the impact of fire emissions on human health, within the context of a changing climate. San Diego County Public Health Services assisted on this project through assessment of population health impacts and provisioning of syndromic surveillance data for advanced modeling.

Methods

Various historical data sets were used during this study. These included: emergency department syndromic surveillance from 17 hospitals, as well as air quality and particulate matter, meteorological, wildland burn fuel, and atmospheric dispersion data. The study area was San Diego County. These data were linked temporally and spatially to create statistical models based on selected modeling approaches including generalized additive modeling. Future fire frequency was modeled for the entire region to determine the impacts of climate change on future fire and health outcomes. Modeling based upon previous fire occurrence was used to develop models for future fire indexes, risk of ignition, potential burning, and fire weather.

Results

Several models were developed to produce expected respiratory health impacts under future climate conditions for the San Diego County region. Model results showed that at peak fire particulate concentrations, the odds of a person seeking emergency care increased by approximately 50% compared to non-fire conditions. Also developed was a model to forecast future fire occurrence based on regional climate model predictions. This forecast covering the next the next three decades reveals that San Diego County will experience approximately two extreme fire seasons each decade by 2040.

Conclusions

Syndromic surveillance data are useful during disasters for situational awareness. These data may also provide value for post-disaster analytic work and predictive modeling for future disasters. This study demonstrates utility of syndromic data for collaborative work resulting in better understanding of environmental interactions on human health. We do know that wildfire occurs with some degree of historic regularity and these results may be useful for preparedness planning. We also know the conditions which must be present for medium to high wildland fire impact upon the population. This study further supports the notion that agencies should be able to strategically deploy resources and messaging immediately preceding the fire period with the goal of reducing human health risk factors and encouraging changes in community behaviors before, during and after a fire. Future fire model shows San Diego County will experience approximately two extreme fire seasons each decade by 2040. This project also promoted collaboration between public health and environmental health entities to better understand determinants of health during a disaster. In addition to developing a better understanding of the consequences of climate change on fire-induced respiratory illness, the project funding has provided support for San Diego County to improve their syndromic surveillance capacity and infrastructure.     

The Organizational Structures and Human Resources Allocation of Infectious Disease Surveillance System in Rural China

Objective

To understand the structure and capacity of current infection disease surveillance system, and to provide baseline information for developing syndromic surveillance system in rural China.

Introduction

To meet the long-term needs of public health and social development of China, it is in urgency to establish a comprehensive response system and crisis management mechanism for public health emergencies. Syndromic surveillance system has great advantages in promoting early detection of epidemics and reducing the burden of disease outbreak confirmation (1). The effective method to set up the syndromic surveillance system is to modify existing case report system, improve the organizational structures and integrate new function with the traditional system.

Methods

Since August 2011, an integrated syndromic surveillance project (ISSC) has been implemented in China. Before the launching of the project, a cross-sectional study was carried out in Fengxin County and Yongxiu County of Jiangxi province during October 11 to 18, 2010. Institution information were investigated in the county hospital, township hospital and County Center for Disease Control and Prevention (CDC) to understand the performance of existing case report system for notifiable infectious diseases with regard to its structure, capacity and data collection procedure. Health care workers from each township hospital and village health station were questionnaire interviewed for information on qualification of human resources, basic healthcare delivery condition, hardware and software needs for ISSC.

Results

An internet-based real-time (quasi real-time) case report system for notifiable infectious diseases, based on the three-tier public health service System, had been established in these two counties since 2004. The farthest end of net user in case report system was township hospital. Blood routine test, urine routine test, B ultrasound and electrocardiogram were available in all township hospitals. There was no laboratory equipment in village health stations in these two counties. All the township hospitals in these two counties were equipped with land-line telephones and desktop computers. The internet covers all township hospitals in both counties. Most clinical doctors in township hospital(TH) and village health station(VHS) were male. The age of doctors ranged from 21 to 72 years old, with the average at 42 and median at 40 years. The village health workers were significantly older, less educated and served in health care longer than the township hospital doctors. In Yongxiu County, 95.6% of the village health stations were equipped with computers, including private-owned computers, and 80.7% of them had access to the internet; while in Fengxin County, 66.5% of the village health stations possessed computers, among which most were private property of village doctors, and only 44.2% of them had access to the internet.

Conclusions

The current case report system, with full coverage and stable human resource, has established a solid basis for developing syndromic surveillance system in rural China. The syndromic surveillance system could play its role in early detection of infectious disease outbreaks in rural area where laboratory service for infectious disease diagnosis are not available. However, the lack of computerized patient registration in village and township health care facilities and incomplete internet coverage in rural area and relatively low quality of human resource in village level should be taken into consideration seriously before establishing the syndromic surveillance system in rural China.     

Nontraumatic Oral Health Classification for Alternative Use of Syndromic Data

Objective

To develop a nontraumatic oral health classification that could estimate the burden of oral health-related visits in North Carolina (NC) Emergency Departments (EDs) using syndromic surveillance system data.

Introduction

Lack of access to regular dental care often results in costly, oral health visits to EDs that could otherwise have been prevented or managed by a dentist (1). Most studies on oral health-related visits to EDs have used a wide range of classifications from different databases, but none have used syndromic surveillance data. The volume, frequency, and included details of syndromic data enabled timely burden estimates of nontraumatic oral health visits for NC EDs.

Methods

Literature review, input by subject matter experts (SMEs), and analysis of syndromic data was used to create the nontraumatic oral health classification. BioSense, a near real-time, national-level, electronic health surveillance system was the source of the NC ED syndromic data. Visits with at least one oral health-related ICD-9-CM code were extracted for NC fiscal years 2008–2010. Univariate analyses of chief complaint (CC) and final diagnosis data along with SME consultation were used to determine the CC substrings and ‘white list’ of ICD-9-CM codes used as inclusion criteria to classify visits as oral health-related. These analyses and consultations also determined the trauma-related codes and substrings used to exclude visits.

Results