Data Sharing

Introduction: response to this, the Centers for Disease Control and Prevention (CDC), CSTE, and the American Association of Poison Control Centers (AAPCC) members created the Poison Center Public Health Community of Practice (CoP). The CoP acts as a platform, to facilitate sharing experiences, identify best practices, and develop relationships among federal agencies, state and local health departments (HD), and PCs. Since its inception, the CoP garnered over 250 members, hosted more than 25 webinars regarding PC-HD collaborations, and produced five newsletters highlighting subjects pertinent to PC and HD personnel. To date, the CoP's primary focus has been to strengthen PC-HD partnerships; however, recent events highlight opportunities to expand the public health impact of the CoP. In this roundtable, we will discuss how the CoP was leveraged by federal and state health agencies to build new multidisciplinary and inter-agency relationships and how these experiences have led to the proposed guidance.

Objective: - To discuss the development of a set of tools for interagency collaborations on health surveillance - To determine the core contents of the tools based on known gaps in health surveillance - To determine collaborators in development and timelines for completion

Asymptomatic Bacteriuria (ASB) is defined as the presence of bacteria in the urine of a patient without signs or symptoms of a urinary tract infection (UTI). It is one of the most common reasons for inappropriate antibiotic use in hospitalized patients. Without efforts to check inappropriate use, our communities could see increased numbers of highly resistant bacterial pathogens contributing to the public health threat of antimicrobial resistance. Treatment itself may be associated with subsequent antimicrobial resistance, adverse drug effects, and cost. The Houston Health Department (HHD) has made it a priority to address antibiotic resistance and stewardship by working collaboratively with members of the healthcare community to address this patient safety issue. As such HHD, in conjunction with infectious diseases experts from the HHD Antimicrobial Stewardship Executive Committee formed a joint learning collaborative to work on an asymptomatic bacteriuria stewardship project. The goal of the project was to engage with healthcare professionals across facilities within the Houston area to work collaboratively to help reduce unnecessary testing and treatment of ASB.

Objective: 1) To describe findings from the joint collaborative between the Houston Health Department and Houston-based hospitals 2) To promote cross sectional partnerships and collaborations across health agencies.

With the increase in the amount of public health data along with the growth of public health informatics, it is important for epidemiologists to understand the current trends in technology and the impact they may have in the field. Because it is unfeasible for public health professionals to be an expert in every emerging technology, this presentation seeks to provide them with a better understanding of how emerging technologies may impact the field and the level of expertise required to realize benefits from the new technologies. Furthermore, understanding the capabilities provided by emerging technologies may guide future training and continuing education for public health professionals.

Objective: The objective of this presentation is to explore emerging technologies and how they will impact the public health field. New technologies such as blockchain, artificial intelligence (AI), and the Internet of Things (IoT) will likely be incorporated into epidemiological methods and processes. This presentation will provide an overview of these technologies and focus on how they may impact public health surveillance in the future.

There are a wide variety of available web-based apps, such as CDC'™s Epidemic Information Exchange, that provide infectious disease information and disease distribution [1]. Publicly available, online data can be used to inform a user of general risks based on disease distribution maps and case count data. Unfortunately, each app contains different aspects of the data, which is often represented in different ways and incompatible formats. This heterogeneity can overwhelm a user with confusing information making it difficult to interpret or gain valuable insight into their own situational risk in a specified location. In addition, online resources do not filter information based on the user's current location or situational needs and, therefore, reduces the value of information a user may be interpreting. However, information formatted and represented appropriately in a single app could be used to better understand an individual's situational infectious disease risk. In addition, this information may further educate a user based on a situation or incident to prevent disease spread, especially in higher risk populations. To accomplish these goals, PNNL has developed an offline, Android app that provides the user with simple, easy to understand filterable global infectious disease information integrated with their location to provide personalized situational health risk and decision support in the field.

Objective: The Pocket Atlas of Infectious Diseases (PocketAID) mobile application developed at Pacific Northwest National Laboratory (PNNL) provides infectious disease education and decision support offline for an enhanced personal situational risk assessment anywhere in the world. The app integrates a user's location, demographic information, and infectious disease data to present the user with important information including personalized, calculated risk level. PocketAID features a global disease distribution map and epidemiological curve of country-based case counts by year. Filter options allow users to customize disease lists available to aid in situational awareness. PocketAID, first of its kind, is being developed for offline decision support use by Department of Defense's Defense Threat Reduction Agency (DTRA).

The opioid overdose crisis has rapidly expanded in North Carolina (NC), paralleling the epidemic across the United States. The number of opioid overdose deaths in NC has increased by nearly 40% each year since 2015.1 Critical to preventing overdose deaths is increasing access to the life-saving drug naloxone, which can reverse overdose symptoms and progression. Over 700 EMS agencies across NC respond to over 1,000,000 calls each year; naloxone administration was documented in over 15,000 calls in 2017.2 Linking EMS encounters with naloxone administration to the corresponding ED visit assists in understanding the health outcomes of these patients. However, less than 66% of NC EMS records with naloxone administration in 2017 were successfully linked to an ED visit record. This study explored methods to improve EMS and ED data linkage, using a multistage process to maximize the number of correctly linked records while avoiding false linkages.

Objective: To improve linkage between North Carolina's Emergency Medical Services (EMS) and Emergency Department (ED) data using an iterative, deterministic approach.

Sentinel surveillance, where selected jurisdictions follow standardized protocols to collect and report enhanced public health data not available through other routine surveillance efforts, is a key part of national surveillance of sexually transmitted diseases (STDs). Although four STDs are nationally notifiable conditions (chlamydia, gonorrhea, syphilis and chancroid), the burden of these conditions (over 2.3 million cases were reported in 2017) limits the amount of detailed clinical and demographic data available for all cases. Sentinel surveillance in clinical settings serving at-risk populations, such as STD clinics, provides an opportunity to collect enhanced data elements on persons seeking STD-related services, such as sex of sex partners and anatomic site of infection. However, there are challenges in combining data across jurisdictions as estimated effect measures may vary by jurisdiction (e.g., some may have higher observed burden of disease among certain populations) and the amount of data contributed by jurisdiction may vary; combined this could lead to biased estimates if heterogeneity is not taken into account.

Objective: To identify best practices for combining public health data for multi-jurisdiction surveillance projects.

The DoD and VDH both maintain local ESSENCE installations to monitor the health status of their military and civilian populations, respectively, and submit syndromic surveillance data to the NSSP ESSENCE to foster data sharing and collaborative initiatives among public health entities. Military Treatment Facilities (MTFs), housed on DoD installations, provide healthcare to all service members and their beneficiaries stationed in the area. Service members and their beneficiaries represent a substantial portion of the local community and interact with the civilian population throughout daily activities. Sharing syndromic surveillance data between DoD and public health jurisdictions can provide public health situational awareness among both civilian and military populations to support disease surveillance. DoD and VDH engaged in a pilot project to develop processes and procedures for data sharing, data access, and communication with the aim they can serve as best practices for other jurisdictions seeking to share syndromic surveillance data with DoD.

Objective: This panel will focus on the experiences from the Department of Defense (DoD) and Virginia Department of Health (VDH) data sharing project using the National Syndromic Surveillance Program (NSSP) ESSENCE and will discuss lessons learned, challenges, and recommendations within the following areas: 1) data sharing authority, 2) coordination and implementation of data sharing with a focus on personnel, training, and managing access and 3) communication between local, state, and federal agencies.

Austin Public Health creates a variety of syndromic surveillance reports for events throughout the Austin, Texas metropolitan area. These events range from responses to major disasters such as the 2017 Hurricane Harvey sheltering to ongoing special event monitoring such as University of Texas football games and the Austin City Limits music festival. Partnerships within the Austin metropolitan region are crucial to ensuring the information-sharing necessary to create robust reports, as well as during the follow-up process of requesting feedback from partners on the usefulness of the reports. Austin Public Health's Public Health Emergency Preparedness program utilizes a variety of tools and resources to create informative, event-specific, and engaging reports, fulfilling multiple reporting needs for all partners.

Objective: Austin Public Health's Public Health Emergency Preparedness program utilizes a variety of tools and resources to create informative, event-specific, and engaging syndromic surveillance reports to share 1) internally within Austin Public Health; 2) with City of Austin and Travis County partners; 3) local health care coalition members; and 4) the public during events that affect the Austin, Texas metropolitan area.

Historically, there has been a lack of data available to assess the health and well-being of urban American Indian/Alaska Natives (AI/ANs) in the United States. Furthermore, there has been limited data showing the increasing disparities that exists between urban AI/ANs and non-Hispanic Whites (NHW). Organizations looking to address these disparities have limited resources and mechanisms to address this rising problem.1 In 2017, Urban Indian Health Institute (UHI) released a series of Community Health Profiles (CHPs) detailing the health status of urban AI/AN communities to provide detailed information to assist in program planning, grant writing and advocacy through increased documentation of current health disparities faced by urban AI/AN populations.

Objective: To create an interactive, user friendly platform for partners and data users to increase awareness around relevant health disparities and strengths within the urban AI/AN community.

The ability to harness data science for use in improving population health and public health surveillance begins with the application of interoperability standards to electronic messaging for data exchange between HIT used by public health authorities (PHAs) and the providers who submit patient data to them. When electronic transmissions between these entities are not based on interoperability standards, the patient data that are exchanged may be incomplete, inaccurate, invalid, and/or untimely. As a result, local PHAs and the Centers for Disease Control and Prevention (CDC) may be unable to fulfill their goals of monitoring public health trends and improving population health.

Objective: To provide tools to generate national and local syndromic surveillance electronic messaging specifications and to test implementations in which the set of requirements have been implemented in order to confirm or refute the conformance to those requirements, thereby promoting healthcare information technology (HIT) interoperability in the public health sector.