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.     

Surveillance for Radiation-Related Exposures Reported to the National Poison Data System

Objective

To describe radiation-related exposures of potential public health significance reported to the National Poison Data System (NPDS).

Introduction

For radiological incidents, collecting surveillance data can identify radiation-related public health significant incidents quickly and enable public health officials to describe the characteristics of the affected population and the magnitude of the health impact which in turn can inform public health decision-making. A survey administered by the Council of State and Territorial Epidemiologists (CSTE) to state health departments in 2010 assessed the extent of state-level planning for surveillance of radiation-related exposures and incidents: 70%–84% of states reported minimal or no planning completed. One data source for surveillance of radiological exposures and illnesses is regional poison centers (PCs), who receive information requests and reported exposures from healthcare providers and the public. Since 2010, the Centers for Disease Control and Prevention (CDC) and the American Association of Poison Control Centers (AAPCC) have conducted ongoing surveillance for exposures to radiation and radioactive materials reported from all 57 United States (US) PCs to NPDS, a web-based, national PC reporting database and surveillance system.

Methods

We collaborated with the American Association of Poison Control Centers (AAPCC), Poisindex® and Thomson Reuters Healthcare to develop an improved coding system for tracking radiation-related exposures reported to US PCs during 2011 and trained PC staff on its usage. We reviewed NPDS data from 1 September 2010 – 30 June 2012 for reported exposures to pharmaceutical or nonpharmaceutical radionuclides; ionizing radiation; radiological or nuclear weapons; or X-ray, alpha, beta, gamma, or neutron radiation. CDC medical toxicology and epidemiology staff reviewed each reported exposure to determine whether it was of potential public health concern (e.g. exposures associated with an ongoing public health emergency, several reported exposures clustered in space and time). When further information was needed to classify the potential public health importance of a call, CDC and AAPCC staff contacted the regional PC where each call originated. When exposures were spatially and temporally clustered, we reviewed news stories in the public media for evidence of an associated radiation incident.

Results

Of 419 exposures reported during the study period, 25 were associated with a radiation-related incident. Of these, 4 were related to an exposure to x-ray radiation from an industrial radiography incident, 11 were related to a transportation accident involving potential contamination with radioactive material, and 10 were related to the Fukushima Daiichi Japan nuclear reactor disaster. Public health, hazardous materials, or hospital radiation safety staff were involved in responding to each of these events. We also identified 26 reported exposures associated with a regional radiation anti-terrorism exercise. The reported exposures were followed-up and removed from analysis once we determined they were part of the exercise. The remaining (n=368; 88%) were either requests for information, confirmed non-exposures, or exposures deemed unrelated or non-significant.

Conclusions

The capability to monitor self- or clinician-reported exposures to radiation and radioactive materials is available in NPDS for state and local public health use in collaboration with their regional PC and may improve public health capacity to identify and respond to radiological emergencies. Next steps include testing the system’s capability to accurately classify and rapidly respond to a cluster of calls to PCs reporting radiation exposures associated with a “dirty bomb” exercise during July, 2012.     

State and Local Health Agency Engagement in HIE: A Cross-Sectional Survey

Objective

To characterize state and local health agency relationships with health information exchange organizations.

Introduction

There is growing interest in leveraging available health information exchange (HIE) infrastructures to improve public health surveillance (1). The Health Information Technology for Clinical and Economic Health Act and Meaningful Use criteria for electronic health record (EHR) systems are among the factors driving the development, adoption and use of HIEs. HIEs deliver or make accessible clinical and administrative data as patients are admitted, discharged, and transferred across hospitals, clinics, medical centers, counties, states and regions (2). While several HIE infrastructures exist (3), there is little evidence on the engagement in HIE initiatives by state and local health agencies.

Methods

An online survey of state and local health officials was conducted in six states where HIEs were known to be present. Half of the states were funded by the Centers for Disease Control and Prevention (CDC) to engage public health agencies in HIE activities; the other half received no such funding. A total of 143 officials were invited to participate; 73 (51%) responded. The survey asked respondents about their agencies awareness, engagement, and data exchange with HIEs. The survey further asked agencies about their perceptions of barriers and challenges to public health engagement with HIE organizations.

Results

Just 25% of agencies had a formal relationship, typically created through a memorandum of understanding or data usage agreement, with at least one nearby HIE. The majority (54%) of agencies either had no relationship (20%) or only an informal relationship (34%) with an HIE. The remaining agencies (18%) reported that no HIE existed in their jurisdiction. Agencies in states that had received CDC funding for HIE engagement were more likely (14 versus 2) to be formally partnered with an HIE.

Conclusions

Few public health agencies are formally engaged in HIE. Financial costs, human resources, and concerns regarding privacy/security were the top cited barriers to broader engagement in HIE. For public health to be an active participant in and reap the benefits of HIE, greater investment in state and local public health informatics capacity, including human resources, and education regarding HIE privacy and security practices are needed.     

Identification and Assessment of Public Health Surveillance Gaps under the IHR (2005)

Objective

To conceive and develop a model to identify gaps in public health surveillance performance and provide a toolset to assess interventions, cost, and return on investment (ROI).

Introduction

Under the revised International Health Regulations (IHR [2005]) one of the eight core capacities is public health surveillance. In May 2012, despite a concerted effort by the global community, the World Health Organization (WHO) reported out that a significant number of member states would not achieve targeted capacity in the IHR (2005) surveillance core capacity.Currently, there is no model to identify and measure these gaps in surveillance performance. Likewise, there is no toolset to assess interventions by cost and estimate the ROI.We developed a new conceptual framework that: (1) described the work practices to achieve effective and efficient public health surveillance; (2) could identify impediments or gaps in performance; and (3) will assist program managers in decision making.

Methods

Published articles and grey-literature reports, manuals and logic model examples were gathered through a literature review of PubMed, Web of Science, Google Scholar, and other databases. Logic models were conceived by categorizing discrete surveillance inputs, activities, outputs, and outcomes. Indicators were selected from authoritative sources or developed and then mapped to the logic model elements. These indicators will be weighted using the principle component analysis (PCA), a method for enhanced precision of statistical analysis. Finally, on the front end of the tool, indicators will graphically measure the surveillance gap expressed through the tool’s architecture and provide information using an integrated cost-impact analysis.

Results

We developed five public health surveillance logic models: for IHR (2005) compliance; event-based; indicator-based; syndromic; and predictive surveillance domains. The IHR (2005) domain focused on national-level functionality, and the others described the complexities of their specific surveillance work practices. Indicators were then mapped and linked to all logic model elements.

Conclusions

This new framework, intended for self-administration at the national and subnational levels, measured public health surveillance gaps in performance and provided cost and ROI information by intervention. The logic model framework and PCA methodology are tools that both describe work processes and define appropriate variables used for evaluation. However, both require real-world data. We recommend pilot testing and validation of this new framework. Once piloted, the framework could be adapted for the other IHR (2005) core capacities.     

Disease Surveillance and Achieving Synergy In Public Health Quality Improvement

Objective

To examine disease surveillance in the context of a new national framework for public health quality and to solicit input from practitioners, researchers, and other stakeholders to identify potential metrics, pivotal research questions, and actions for achieving synergy between surveillance practice and public health quality.

Introduction

National efforts to improve quality in public health are closely tied to advancing capabilities in disease surveillance. Measures of public health quality provide data to demonstrate how public health programs, services, policies, and research achieve desired health outcomes and impact population health. They also reveal opportunities for innovations and improvements. Similar quality improvement efforts in the health care system are beginning to bear fruit. There has been a need, however, for a framework for assessing public health quality that provides a standard, yet is flexible and relevant to agencies at all levels.The U.S. Health and Human Services (HHS) Office of the Assistant Secretary for Health, working with stakeholders, recently developed and released a Consensus Statement on Quality in the Public Health System that introduces a novel evaluation framework. They identified nine aims that are fundamental to public health quality improvement efforts and six cross-cutting priority areas for improvement, including population health metrics and information technology; workforce development; and evidence-based practices (1).Applying the HHS framework to surveillance expands measures for surveillance quality beyond typical variables (e.g., data quality and analytic capabilities) to desired characteristics of a quality public health system. The question becomes: How can disease surveillance help public health services to be more population centered, equitable, proactive, health-promoting, risk-reducing, vigilant, transparent, effective, and efficient—the desired features of a quality public health system?Any agency with a public health mission, or even a partial public health mission (e.g., tax-exempt hospitals), can use these measures to develop strategies that improve both the quality of the surveillance enterprise and public health systems, overall. At this time, input from stakeholders is needed to identify valid and feasible ways to measure how surveillance systems and practices advance public health quality. What exists now and where are the gaps?

Methods

Improving public health by applying quality measures to disease surveillance will require innovation and collaboration among stakeholders. This roundtable will begin a community dialogue to spark this process. The first goal will be to achieve a common focus by defining the nine quality aims identified in the HHS Consensus Statement. Attendees will draw from their experience to discuss how surveillance practice advances the public health aims and improves public health. We will also identify key research questions needed to provide evidence to inform decision-making.

Results

The roundtable will discuss how the current state of surveillance practice addresses each of the aims described in the Consensus Statement to create a snapshot of how surveillance contributes to public health quality and begin to articulate practical measures for assessing quality improvements. Sample questions to catalyze discussion include:

• —How is surveillance used to identify and address health disparities and, thereby, make public health more equitable? What are the data sources? Are there targets? How can research and evaluation help to enhance this surveillance capability and direct action?
• —How do we identify and address factors that inhibit quality improvement in surveillance? What are the gaps in knowledge, skills, systems, and resources?
• —Where can standardization play a positive role in the evaluation of quality in public health surveillance?
• —How can we leverage resources by aligning national, state, and local goals? —What are the key research questions and the quality improvement projects that can be implemented using recognized models for improvement?
• —How can syndromic surveillance, specifically, advance the priority aims?

The roundtable will conclude with a list of next steps to develop metrics that resonate with the business practices of public health at all levels.     

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].     

Recommendations for Syndromic Surveillance Using Inpatient and Ambulatory EHR Data

Objective

To develop national Stage 2 Meaningful Use (MUse) recommendations for syndromic surveillance using hospital inpatient and ambulatory clinical care electronic health record (EHR) data.

Introduction

MUse will make EHR data increasingly available for public health surveillance. For Stage 2, the Centers for Medicare & Medicaid Services (CMS) regulations will require hospitals and offer an option for eligible professionals to provide electronic syndromic surveillance data to public health. Together, these data can strengthen public health surveillance capabilities and population health outcomes (Figure 1).Open in a separate windowFigure 1:Syndromic surveillance data can inform public health functions.To facilitate the adoption and effective use of these data to advance population health, public health priorities and system capabilities must shape standards for data exchange. Input from all stakeholders is critical to ensure the feasibility, practicality, and, hence, adoption of any recommendations and data use guidelines.

Methods

ISDS, in collaboration with the Division of Informatics Solutions and Operations at the Centers for Disease Control and Prevention (CDC), and HLN Consulting, convened a multi-stakeholder Work-group of clinicians, technologists, epidemiologists, and public health officials with expertise in syndromic surveillance. Recommended MUse guidelines were developed by performing an environmental scan of current practice and by using an iterative, expert and community input-driven process. The Workgroup developed initial guidelines and then solicited and received feedback from the stakeholder community via interview, e-mail, and structured surveys. Stakeholder feedback was analyzed using quantitative and qualitative methods and used to revise the recommendations.

Results

The MUse Workgroup defined electronic syndromic surveillance (ESS) characteristics. Specifically, data are characterized by their timeliness, sensitivity rather than specificity, population focus, limited personally identifiable information, and inclusion of all patient encounters within a specific healthcare setting (e.g., emergency department, inpatient, outpatient). Based on stakeholder input (n=125) and Workgroup expertise, the guidelines identify priority syndromic surveillance uses that can assist with:

1. Monitoring population health;Informing public health services; andInforming interventions, health education, and policy by characterizing the burden of chronic disease and health disparities.

Similarly, the Workgroup identified data elements to support these uses in the hospital inpatient setting and possibly in the ambulatory care setting. They were aligned to previously identified emergency department and urgent care center data elements and Stage 1–2 clinical MUse objectives. Core data elements (required for certification) cover treating facility; patient demographics; subjective and objective clinical findings, including chief complaint, body mass index, smoking history, diagnoses; and outcomes. Other data elements were designated as extended (not required for certification) or future (for future consideration). The data elements and their specifications are subject to change based on applicable state and local laws and practices.Based on their findings and recommended guidelines detailed in the report, the Workgroup also identified community activities and additional investments that would best support public health agencies in using EHR technology with syndromic surveillance methodologies.

Conclusions

The widespread adoption of EHRs, catalyzed by MUse, has the potential to improve population health. By identifying and describing potential ESS uses of new sources of EHR data and associated data elements with the greatest utility for public health, the recommendations set forth by the ISDS MUse Workgroup will serve to facilitate the adoption of MUse policy by both healthcare and public health agencies.     

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.     

Framing the Use of Social Media Tools in Public Health

Objective

Recent scholarship has focused on using social media (e.g., Twitter, Facebook) as a secondary data stream for disease event detection. However, reported implementations such as (4) underscore where the real value may lie in using social media for surveillance. We provide a framework to illuminate uses of social media beyond passive observation, and towards improving active responses to public health threats.

Introduction

User-generated content enabled by social media tools provide a stream of data that augment surveillance data. Current use of social media data focuses on identification of disease events. However, once identification occurs, the leveraging of social media in monitoring disease events remains unclear (2, 3). To clarify this, we constructed a framework mapped to the surveillance cycle, to understand how social media can improve public health actions.

Methods

This framework builds on extant literature on surveillance and social media found in PubMed, Science Direct, and Web of Science, using keywords: “public health”, “surveillance”, “outbreak”, and “social media”. We excluded articles on online tools that were not interactive e.g., aggregated web-search results. Of 2,064 articles, 23 articles were specifically on the use of social media in surveillance work. Our review yielded five categories of social media use within the surveillance cycle (

Defining Public Health Situation Awareness – Outcomes and Metrics for Evaluation

Objective

Review concept of situation awareness (SA) as it relates to public health surveillance, epidemiology and preparedness [1]. Outline hierarchical levels and organizational criteria for SA [2]. Initiate consensus building process aimed at developing a working definition and measurable outcomes and metrics for SA as they relate to syndromic surveillance practice and evaluation.

Introduction

A decade ago, the primary objective of syndromic surveillance was bioterrorism and outbreak early event detection (EED) [3]. Syndromic systems for EED focused on rapid, automated data collection, processing and statistical anomaly detection of indicators of potential bioterrorism or outbreak events. The paradigm presented a clear and testable surveillance objective: the early detection of outbreaks or events of public health concern. Limited success in practice and limited rigorous evaluation, however, led to the conclusion that syndromic surveillance could not reliably or accurately achieve EED objectives. At the federal level, the primary rationale for syndromic surveillance shifted away from bioterrorism EED, and towards all-hazards biosurveillance and SA [4–6]. The shift from EED to SA occurred without a clear evaluation of EED objectives, and without a clear definition of the scope or meaning of SA in practice. Since public health SA has not been clearly defined in terms of operational surveillance objectives, statistical or epidemiological methods, or measurable outcomes and metrics, the use of syndromic surveillance to achieve SA cannot be evaluated.

Methods

This session is intended to provide a forum to discuss SA in the context of public health disease surveillance practice. The roundtable will focus on defining SA in the context of public health syndromic and epidemiologic surveillance. While SA is often noted in federal level documents as a primary rationale for biosurveillance [1, 4–6], it is rarely defined or described in operational detail. One working definition presents SA as “real-time analysis and display of health data to monitor the location, magnitude, and spread of an outbreak”, yet it does not elaborate on the methods, systems or evaluation requirements for SA in public health or biosurveillance [3]. In terms of translating SA into public health surveillance practice [1], we will discuss and define the requirements of public health SA based on its development and practice in other areas [2]. The proposed theoretical framework and evaluation criteria adapted and applied to public health SA [2] follow:

• - Level 1: Perceive relevant surveillance data and epidemiological information.
• - Level 2: Integrate surveillance and non-surveillance data in conjunction with operator goals to provide understanding of the meaning of the information.
• - Level 3: Through perceiving (Level 1) and integrating and understanding (Level 2) provide prediction of future events and system states to allow for timely and effective public health decision making.

Results

Sample questions for discussion: What is the relevance of syndromic surveillance and biosurveillance in the SA framework? Where does it fit within the current public health surveillance environment? To achieve the roundtable discussion objectives, the participants will work towards a consensus definition of SA for public health, and will outline measureable outcomes and metrics for evaluation of syndromic surveillance for public health SA.     

The Last Mile: Using Fax Machines to Exchange Data between Clinicians and Public Health

There is overlap in a wide range of activities to support both public health and clinical care. Examples include immunization registries (IR), newborn screening (NBS), disease reporting, lead screening programs, and more. Health information exchanges create an opportunity to share data between the clinical and public health environments, providing decision support to clinicians and surveillance and tracking information to public health. We developed mechanisms to support two-way communication between clinicians in the Indiana Health information Exchange (IHIE) and the Indiana State Department of Health (ISDH). This paper describes challenges we faced and design decisions made to overcome them.We developed systems to help clinicians communicate with the ISDH IR and with the NBS program. Challenges included (1) a minority of clinicians who use electronic health records (EHR), (2) lack of universal patient identifiers, (3) identifying physicians responsible for newborns, and (4) designing around complex security policies and firewalls.To communicate electronically with clinicians without EHRs, we utilize their fax machines. Our rule-based decision support system generates tailored forms that are automatically faxed to clinicians. The forms include coded input fields that capture data for automatic transfer into the IHIE when they are faxed back. Because the same individuals have different identifiers, and newborns’ names change, it is challenging to match patients across systems. We use a stochastic matching algorithm to link records. We scan electronic clinical messages (HL7 format) coming into IHIE to find clinicians responsible for newborns. We have designed an architecture to link IHIE, ISDH, and our systems.     

Towards Interoperability for Public Health Surveillance: Experiences from Two States

Objective

To characterize the use of standardized vocabularies in real-world electronic laboratory reporting (ELR) messages sent to public health agencies for surveillance.

Introduction

The use of health information systems to electronically deliver clinical data necessary for notifiable disease surveillance is growing. For health information systems to be effective at improving population surveillance functions, semantic interoperability is necessary.Semantic interoperability is “the ability to import utterances from another computer without prior negotiation” (1). Semantic interoperability is achieved through the use of standardized vocabularies which define orthogonal concepts to represent the utterances emitted by information systems. There are standard, mature, and internationally recognized vocabularies for describing tests and results for notifiable disease reporting through ELR (2). Logical Observation Identifiers Names and Codes (LOINC) identify the specific lab test performed. Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) identify the diseases and organisms tested for in a lab test.Many commercial laboratory and hospital information systems claim to support LOINC and SNOMED CT on their company websites and in marketing materials, and systems certified for Meaningful Use are required to support LOINC and SNOMED CT. There is little empirical evidence on the use of semantic interoperability standards in practice.

Methods

To characterize the use of standardized vocabularies in electronic laboratory reporting (ELR) messages sent to public health agencies for notifiable disease surveillance, we analyzed ELR messages from two states: Indiana and Wisconsin. We examined the data in the ELR messages where tests and results are reported (3). For each field, the proportion of field values that used either LOINC or SNOMED CT codes were calculated by dividing the number of fields with coded values by the total number of non-null values in fields.

Results

Results are summarized in Sample% OBX-3 Fields with LOINC% OBX-5 Fields with SNOMEDCTINPC Messages16.5%0.0%WDHS Messages0.0%12.3%Open in a separate window

Conclusions

Although Wisconsin and Indiana both have high adoption of advanced health information systems with many hospitals and laboratories using commercial systems which claim to support interoperability, very few ELR messages emanate from real-world systems with interoperable codes to identify tests and clinical results. To effectively use the arriving ELR messages, Indiana and Wisconsin health departments employ software and people workarounds to translate the incoming data into standardized concepts that can be utilized by the states’ surveillance systems. These workarounds present challenges for budget constrained public health departments seeking to leverage Meaningful Use Certified technologies to improve notifiable disease surveillance.     

Enhanced Surveillance during the Democratic National Convention,Charlotte, NC

Objective

To describe how the existing state syndromic surveillance system (NC DETECT) was enhanced to facilitate surveillance conducted at the Democratic National Convention in Charlotte, North Carolina from August 31, 2012 to September 10, 2012.

Introduction

North Carolina hosted the 2012 Democratic National Convention, September 3–6, 2012. The NC Epidemiology and Surveillance Team was created to facilitate enhanced surveillance for injuries and illnesses, early detection of outbreaks during the DNC, assist local public health with epidemiologic investigations and response, and produce daily surveillance reports for internal and external stakeholders. Surveillane data were collected from several data sources, including North Carolina Electronic Disease Surveillance System (NC EDSS), triage stations, and the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT).NC DETECT was created by the North Carolina Division of Public Health (NC DPH) in 2004 in collaboration with the Carolina Center for Health Informatics (CCHI) in the UNC Department of Emergency Medicine to address the need for early event detection and timely public health surveillance in North Carolina using a variety of secondary data sources. The data from emergency departments, the Carolinas Poison Center, the Pre-hospital Medical Information System (PreMIS) and selected Urgent Care Centers were available for monitoring by authorized users during the DNC.

Methods

Within NC DETECT, new dashboards were created that allowed epidemiologists to monitor ED visits and calls to the poison center in the Charlotte area, the greater Cities Readiness Initiative region and the entire state for infectious disease signs and symptoms, injuries and any mention of bioterrorism agents. The dashboards also included a section to view user comments on the information presented in NC DETECT. Data processing changes were also made to improve the timeliness of the EMS data received from PreMIS.

Results

The DNC dashboards added to NC DETECT streamlined the workflow by placing all syndromes and annotations of interest in one place, with the date ranges and locations already pre-selected. Graphs in the dashboards could be easily copied and pasted into situation reports. The prompt development of these user-friendly tools provided effective surveillance for this mass gathering and ensured timely control measures, if necessary.

Conclusions

Syndromic surveillance systems can be enhanced to provide detailed, specific surveillance during mass gathering events. Elements that facilitate this enhancement include strong communication between skilled users and the informatics team, in order to minimize the burden placed on the surveillance team system users, data sources and system developers during the event. The visualizations developed as part of these new dashboards will be leveraged to provide additional tools to other NC DETECT user groups, including hospital-based public health epidemiologists and local health department users.Open in a separate window     

Legal and Policy Barriers to Sharing Data Between Public Health Programs in New York City: A Case Study

Integration of public health surveillance data within health departments is important for public health activities and cost-efficient coordination of care. Access to and use of surveillance data are governed by public health law and by agency confidentiality and security policies.In New York City, we examined public health laws and agency policies for data sharing across HIV, sexually transmitted disease, tuberculosis, and viral hepatitis surveillance programs. We found that recent changes to state laws provide greater opportunities for data sharing but that agency policies must be updated because they limit increased data integration.Our case study can help other health departments conduct similar reviews of laws and policies to increase data sharing and integration of surveillance data.State and local laws mandate the reporting of specific infectious diseases to health departments, which, in turn, use these surveillance data to monitor trends, obtain funding, and allocate resources for controlling infectious diseases. Sharing infectious disease surveillance data within a health department is vital to understanding how one disease may place a person at risk for another disease (e.g., HIV and tuberculosis), how characteristics or behaviors may predispose a person to multiple infectious diseases (e.g., enteric infections and sexually transmitted diseases among men who have sex with men), and how diseases may be clustered in specific geographic areas. Understanding these relationships helps health departments and community provider partners integrate education, screening, and treatment programs to save costs and improve population health. In addition, sharing data is critical for routine case investigations and for investigating outbreaks, which are core functions of health departments.1 The public health need for health department programs to increase data sharing to develop more integrated and cost-efficient systems of care is also in keeping with the goals of the Affordable Care Act.2Local jurisdictional efforts to integrate surveillance data support the national-level goals of the Centers for Disease Control and Prevention (CDC).3 In 2010, the New York City Department of Health and Mental Hygiene (DOHMH) began implementing CDC’s Program Collaboration and Service Integration initiative.4 This initiative aims to strengthen collaboration within health departments across HIV/AIDS, sexually transmitted disease (STD), tuberculosis (TB), and viral hepatitis programs by decreasing duplication of efforts; improving data sharing to better understand and address co-occurrence, coinfection, and syndemics of disease; and facilitating delivery of integrated services to the public. Vital to this initiative are local and state health departments’ commitment and continued efforts to improve data sharing.5 Recent CDC guidelines are aimed at increasing data sharing by strengthening and standardizing data security and confidentiality procedures for state and local HIV, viral hepatitis, STD, and TB surveillance programs.6Despite the strong public health rationale for sharing data, several factors affect the ability of health departments to integrate infectious disease data, such as historically siloed funding coupled with the need for technological improvements and resources to implement, update, and maintain an integrated surveillance registry system. Moreover, the state and local laws that authorize the collection of data may actually impede the ability of health departments to share, analyze, and make use of data across separate disease programs.As part of New York City’s implementation of the Program Collaboration and Service Integration initiative, we carried out a case study to identify factors that affect data sharing, specifically examining the role of public health laws and agency policies on internal sharing of HIV, STD, TB, and viral hepatitis surveillance data.7 Our case study focused on HIV, STDs, TB, and viral hepatitis; however, the lessons learned can be applied to other reportable diseases and conditions. This case study can help other state and local health departments to conduct similar reviews of laws and policies to work toward increased data sharing and integration of surveillance data.     

A Piece of the Public Health Surveillance Puzzle: Social Contacts among School-Aged Children

Objective

To enhance public health surveillance and response for acute respiratory infectious diseases by understanding social contacts among school-aged children

Introduction

Timely and effective public health decision-making for control and prevention of acute respiratory infectious diseases relies on early disease detection, pathogen properties, and information on contact behavior affecting transmission. However, data on contact behavior are currently limited, and when available are commonly obtained from traditional self-reported contact surveys [1, 2]. Information for contacts among school-aged children is especially limited, even though children frequently have higher attack rates than adults, and school-related transmission is commonly predictive of subsequent community-wide outbreaks, especially for pandemic influenza.Within this context, high-quality data are needed about social contacts. Precise contact estimates can be used in mathematical models to understand infectious disease transmission [3] and better target surveillance efforts. Here we report preliminary data from an ongoing 2-year study to collect social contact data on school-aged children and examine the transmission dynamics of an influenza pandemic.

Methods

Our aim is to capture mixing patterns and contact rates of school-aged children in 24 schools and other non-school-related venues. We used a stratified design to ensure coverage of urban, suburban, and rural school districts, as well as climatically different areas (mountains and desert) in Utah. Elementary, middle, and high schools were chosen in each stratum. We defined a self-reported contact as anyone with whom the participant talked to face-to-face, played with, or touched. Contact logs collected subjective information (age, location, and duration) on self-reported contacts during a 2-day period. Objective contact data were collected by using proximity sensors [4] that recorded signals from other sensors within approximately 3–4 feet.Mixing patterns during school and non-school-related activities were summarized for participating school-aged children. We developed contact networks using proximity sensor data, providing visualizations of contact patterns as well as numeric contact measures. Contact networks were characterized with respect to degree distribution, and density. The degree for each person was calculated as the number of unique contacts. The density for a network was calculated as the number of observed contacts divided by the number of possible contacts.

Results

Two elementary schools, four summer camps, and one club participated in the study between May and August, 2012. Data were processed for the two schools and one camp. The mean degrees for the two schools were 28 and 29, with network sizes 109 and 129, respectively. The mean degree from camp was 43, whose network size was 141. The density of contacts was 0.26 and 0.22 for the schools and 0.31 for the camp. The density within classrooms at the two schools ranged from 0.78 to 0.98. School-aged children typically underreported contacts using the contact log compared with objective proximity sensor data; this difference was statistically significant.

Conclusions

The variability in these and other contact network characteristics represent factors that could impact influenza transmission. Quantifying these factors improves our understanding of influenza transmission dynamics, which in turn can be used to adapt surveillance methods and control and prevention strategies. Almost all contact among students in our two elementary schools occurs within the classroom and the contact patterns differ by classroom, due to desk arrangement or other characteristics. Thus, during an elementary school outbreak it may be beneficial to focus on classroom-specific surveillance and control strategies.The study is ongoing and we expect the variability in contact rates and mixing patterns will be even greater for middle and high schools where students switch classrooms and classmates each period. These schools could benefit from alternative surveillance and control strategies that account for the heightened overall mixing of the student body.     

Development of the Inventory Management and Tracking System (IMATS) to Track the Availability of Public Health Department Medical Countermeasures During Public Health Emergencies

Objective

To bridge gaps identified during the 2009 H1N1 influenza pandemic by developing a system that provides public health departments improved capability to manage and track medical countermeasures at the state and local levels and to report their inventory levels to the Centers for Disease Control and Prevention (CDC).

Materials and Methods

The CDC Countermeasure Tracking Systems (CTS) program designed and implemented the Inventory Management and Tracking System (IMATS) to manage, track, and report medical countermeasure inventories at the state and local levels. IMATS was designed by CDC in collaboration with state and local public health departments to ensure a “user-centered design approach.” A survey was completed to assess functionality and user satisfaction.

Results

IMATS was deployed in September 2011 and is provided at no cost to public health departments. Many state and local public health departments nationwide have adopted IMATS and use it to track countermeasure inventories during public health emergencies and daily operations.

Discussion

A successful response to public health emergencies requires efficient, accurate reporting of countermeasure inventory levels. IMATS is designed to support both emergency operations and everyday activities. Future improvements to the system include integrating barcoding technology and streamlining user access. To maintain system readiness, we continue to collect user feedback, improve technology, and enhance its functionality.

Conclusion

IMATS satisfies the need for a system for monitoring and reporting health departments’ countermeasure quantities so that decision makers are better informed. The “user-centered design approach” was successful, as evident by the many public health departments that adopted IMATS.     

Implementation of a Mobile-Based Surveillance System in Saudi Arabia for the 2009 Hajj

Objective

To develop and implement a mobile-based disease surveillance system in the Kingdom of Saudi Arabia (KSA) for the 2009 Hajj; to strengthen public health preparedness for the H1N1 Influenza A pandemic.

Introduction

The Hajj is considered to be the largest mass gathering to date, attracting an estimated 2.5 million Muslims from more than 160 countries annually (1). The H1N1 Influenza A pandemic of 2009 generated a global wave of concern among public health departments that resulted in the institution of preventive measures to limit transmission of the disease. Meanwhile, the pandemic amplified an urgent need for more innovative disease surveillance tools to combat disease outbreaks.A collaborative effort between the KSA Ministry of Health (MOH) and the U.S. Centers for Disease Control and Prevention (CDC) was initiated to implement and deploy an informatics-based mobile solution to provide early detection and reporting of disease outbreaks during the 2009 Hajj. The mobile-based tool aimed to improve the efficiency of disease case reporting, recognize potential outbreaks, and enhance the MOH’s operational effectiveness in deploying resources (2).

Methods

We designed a case-based system consisting of a mobile-based data collection toolkit and interactive map-based user interface to perform geospatial analysis and visualization. A train-the-trainer approach was adapted to provide training to the KSA MOH.

Results

More than 200 public health and information and communication technology (ICT) professionals were trained, and 100 mobile devices were deployed during the 2009 Hajj. Nine diseases and conditions that were considered as highest priority during the Hajj were under surveillance, including H1N1 Influenza A and Influenza-like Illness.Pilot testing of the system was conducted during the first week of Ramadan and a modified system was fully operational during the Hajj. Data collected on smartphones were sent to the system via a secured network. The data were processed immediately and visualized on highly interactive maps with local and global views.

Conclusions

Effective public health decision-making requires timely and accurate information from a variety of sources. Mobile-based systems (e.g., personal digital assistants and smartphones) for data collection, transmission, reporting, and analyses provide a faster, easier, and cheaper means to communicate standardized and shareable public health data for decision-making (3). Mobile-based systems have been recognized as a quick and effective response solution to mass gatherings and recommended as data gathering and communication systems with geographical information system (GIS) capability (2). This paper explored the development and implementation of the Global Positioning System/ Geographic Information System (GPS/GIS) enabled mobile-based disease surveillance system as a feasible and effective way to support and strengthen preparedness for H1N1 Influenza A during the 2009 Hajj.Mobile computing technology can be utilized to provide rapid and accurate data collection for public health decision-making during mass gatherings. The GIS-based interactive mapping tool provided a pioneering example of the power of a geographically based internet-accessible surveillance system with real-time data visualization. The technical challenges in the process of implementation and in the field were also identified.A need now exists for a comprehensive and comparative review of parameters such as handheld device cost, training required, and system evaluations because selecting the appropriate software/hardware and system remains a challenge not only to public health professionals, but to the development and application of informatics technology as well.