Building Enhanced Public Health Data Systems With a Situational Awareness and Learning Tool: Focus Group Study.

BACKGROUND Situational awareness is the accurate and timely perception of factors in the environment, comprehension of their meanings, and projection of their future states. OBJECTIVE We aimed to develop a cloud-based Situational Awareness and Learning Tool (SALT) that generates near real-time analytic content from multi-modal data, enabling public health and hospital professionals to make informed decisions during complex population health challenges. METHODS Several focus groups were conducted with representatives from local health departments, hospitals, and emergency agencies. A first round identified data needs and requirements to inform SALT’s design. SALT was developed as a secure, cloud-based platform featuring automated deployment, role-based access, and version-controlled content publishing. A second round of focus groups evaluated the SALT prototype’s utility and gathered feedback for improvements. RESULTS Participants highlighted the need for integrated data from multiple sources, tailored dashboards for specific audiences, and legal frameworks to guide timely data sharing. SALT met these requirements by providing interactive visuals, secure access levels, and a collaborative content management system. The second focus group affirmed SALT’s effectiveness in enhancing decision-making and strategic planning, suggesting enhancements like clearer data labeling, expanded data coverage, and forecasting capabilities. CONCLUSIONS SALT addresses limitations exposed by the COVID-19 pandemic in public health data systems by offering a scalable platform for data sharing, rapid analysis, and situational awareness. It fulfills user needs for integrated, timely data and customized analytic products. SALT represents a viable solution for enhancing public health data systems in preparation for future pandemics and other complex, multisector population health challenges.

Heterogeneity and Interoperability in Local Public Health Information Systems.

Since the COVID-19 pandemic, telehealth usage has surged and remains in high demand even as public health restrictions have relaxed. Telehealth introduces unique challenges to patient care, particularly in maintaining situational awareness and patient safety. Despite telehealth's widespread use, its training is still underrepresented in medical curricula. Recognizing these gaps, we developed a focused module to teach medical students about the significant differences between virtual and in-person visits, emphasizing essential communication skills and tools for situational awareness through simulated telehealth consultations. Using a virtual platform, second-year (preclinical) medical students participated in a simulated telehealth visit during which they conducted a focused assessment of a standardized patient. While the chief complaint was a generalized symptom, the standardized patient had characteristics that suggested a more critical problem that would only be recognized with maintenance of appropriate situational awareness. Faculty members observed the students' performance and provided brief group feedback and discussion along with input from the standardized professionals. Over 2 years, 634 preclinical medical students completed the simulated telehealth session during a course dedicated to transitioning students to their clinical rotations. Feedback from more than 80% of the medical students indicated that the training was valuable and exceeded their expectations. Our innovative simulated telehealth consultation effectively enhances medical students' knowledge and proficiency in telehealth practices and situational awareness, providing them with essential skills for the evolving health care landscape.

BackgroundThe COVID-19 pandemic has highlighted the critical and ongoing need for leaders across health care, public health, and government to have real-time, hyper-local data. These data need to be relevant...

The idea for the Rendezvous and Proximity Operations Program (RPOP) was conceived by a small group of engineers at NASA's Johnson Space Center (JSC). RPOP was part of the tools and technologies implemented for the first Shuttle-Mir rendezvous and docking. Since that time RPOP was used on over 60 missions and became an essential tool for Shuttle rendezvous operations. RPOP serves three main functions: as guidance and navigation software, displays-and-controls mechanism, and situational-awareness tool. This document visits many of the on-orbit firsts for manned spaceflight that were demonstrated in RPOP, with particular focus on the displays and controls and situational awareness aspects. The underlying guidance and navigation algorithms are not exposed. Simultaneous comparison of sensor data from multiple sources, differentiation between multiple three-dimensional trajectories, at-a-glance determination of attitude and location via RPOP's 3D orbiter model, and near-real time updates of guided and unguided trajectory prediction constitute a subset of the RPOP functionality that is detailed. A discussion of the way that RPOP has influenced pilot-in-the-loop behavior for proximity operations, exemplified by the repeatability of mission-to-mission proximity operations trajectories, is presented. Furthermore, many of the concepts that have proven to work well in RPOP have become de facto standards for displays and controls for new manned programs. Astronauts have come to expect the same familiar and effective situational awareness displays to be made available in the Orion Multi-Purpose Crew Vehicle (MPCV); this expectation has driven the design of the next-generation of displays. For example, formal on-orbit handling-qualities assessments of MPCV have all included a RPOP-type display providing key information to the pilots. The lessons learned during the RPOP development and flight experience are not to be taken lightly, but rather ought to be fastidiously applied to future programs since they allow for reuse of proven guidance and navigation display concepts and flight techniques for on-orbit operations.

We consider in this paper situational awareness formation, which is essential for controlling the behavior of unmanned aerial vehicles (UAVs). We propose an approach to forming one of the elements of situational awareness by identifying objects in the environment and tracking their movements using computer vision tools. The convolutional neural networks, which perform semantic segmentation of the image obtained by UAV video surveillance tools, are used as the primary tool for solving these tasks. Several architectures of such networks are compared, and a comparative analysis of their effectiveness from the problem’s point of view is performed. Finally, as a demonstration example, the task of selecting a site in unfamiliar terrain for landing the UAV, satisfying the conditions of safety of performance of this operation is considered.KeywordsNeural networksDeep learningConvolutional neural networkMachine learningUnmanned aerial vehicleSituational awareness

Health informatics can play a critical role in supporting local health departments' (LHDs') delivery of certain essential public health services and improving evidence base for decision support. However, LHDs' informatics capacities are below an optimum level. Efforts to build such capacities face ongoing challenges. Moreover, little is known about LHD leaders' desires for the future of public health informatics. Conduct a qualitative analysis of LHDs' future informatics plans, perceived barriers to accomplishing those plans, and potential impact of future advances in public health informatics on the work of the public health enterprise. This research presents findings from 49 in-depth key informant interviews with public health leaders and informatics professionals from LHDs, representing insights from across the United States. Interviewees were selected on the basis of the size of the population their LHD serves, as well as level of informatics capacity. Interviews were transcribed, verified, and double coded. Major barriers to doing more with informatics included staff capacity and training, financial constraints, dependency on state health agency, and small LHD size/lack of regionalization. When asked about the role of leadership in expanding informatics, interviewees said that leaders could make it a priority through (1) learning more about informatics and (2) creating appropriate budgets for integrated information systems. Local health department leaders said that they desired data that were timely and geographically specific. In addition, LHD leaders said that they desired greater access to clinical data, especially around chronic disease indicators. Local health department leadership desires to have timely or even real-time data. Local health departments have a great potential to benefit from informatics, particularly electronic health records in advancing their administrative practices and service delivery, but financial and human capital represents the largest barrier. Interoperability of public health systems is highly desirable but hardly achievable in the presence of such barriers.

In view of the critical role local health departments (LHDs) play among agencies responsible for responding to natural and man-made emergencies, Bevc et al. examined the LHDs’ emergency preparedness and capacity. They compared LHDs in North Carolina with those across the country for preparedness along eight domains. Significant declines in emergency preparedness were noted from 2010 to 2012 for five out of eight domains, raising questions about our national priority concerning this important function of public health agencies. These findings have numerous implications, some of which are covered in this commentary.

The establishment of a common operating picture through shared situation awareness is critical for the management of first responder operations. Situation awareness is the knowledge of the state and physical location of people, objects and terrain within an area of interest. First responder operations can be quite complex, involving the coordination of and collaboration among teams distributed over large areas. Adding to this complexity is the use of heterogeneous networks with diverse radios, traffic flows and applications. This paper describes some initial results using distributed constraint optimization (DCOP) techniques to facilitate situation awareness for first responders. A brief background on DCOP is presented, along with how DCOP can be applied to enable situation awareness. An example demonstrating the application of DCOP algorithms to a particular situation awareness problem is presented. Finally, some critical issues that arise when utilizing DCOP are described, along with some approaches to addressing these issues. By integrating these DCOP techniques with situation awareness tools, we believe that many of the information distribution, interoperability, and networking difficulties faced in the first responder environment can be overcome.

Evaluating public health surveillance systems is critical to ensuring that conditions of public health importance are appropriately monitored. Our objectives were to qualitatively evaluate 6 state and local health departments that were early adopters of syndromic surveillance in order to (1) understand the characteristics and current uses, (2) identify the most and least useful syndromes to monitor, (3) gauge the utility for early warning and outbreak detection, and (4) assess how syndromic surveillance impacted their daily decision making. We adapted evaluation guidelines from the Centers for Disease Control and Prevention and gathered input from the Centers for Disease Control and Prevention subject matter experts in public health surveillance to develop a questionnaire. We interviewed staff members from a convenience sample of 6 local and state health departments with syndromic surveillance programs that had been in operation for more than 10 years. Three of the 6 interviewees provided an example of using syndromic surveillance to identify an outbreak (ie, cluster of foodborne illness in 1 jurisdiction) or detect a surge in cases for seasonal conditions (eg, influenza in 2 jurisdictions) prior to traditional, disease-specific systems. Although all interviewees noted that syndromic surveillance has not been routinely useful or efficient for early outbreak detection or case finding in their jurisdictions, all agreed that the information can be used to improve their understanding of dynamic disease control environments and conditions (eg, situational awareness) in their communities. In the jurisdictions studied, syndromic surveillance may be useful for monitoring the spread and intensity of large outbreaks of disease, especially influenza; enhancing public health awareness of mass gatherings and natural disasters; and assessing new, otherwise unmonitored conditions when real-time alternatives are unavailable. Future studies should explore opportunities to strengthen syndromic surveillance by including broader access to and enhanced analysis of text-related data from electronic health records. Health departments may accelerate the development and use of syndromic surveillance systems, including the improvement of the predictive value and strengthening the early outbreak detection capability of these systems. These efforts support getting the right information to the right people at the right time, which is the overarching goal of CDC's Surveillance Strategy.

BackgroundInterventions to improve care team situation awareness (SA) are associated with reduced rates of unrecognized clinical deterioration in hospitalized children. Recent safety events at our institution revealed common etiologic themes,...

Background:Optimal design of healthcare spaces can enhance patient care. We applied design thinking and human factors principles to optimize communication and signage on high risk patients to improve situation awareness in a new clinical space for the pediatric ICU.Objective:To assess the impact of these tools in mitigating situation awareness concerns within the new clinical space. We hypothesized that implementing these design‐informed tools would either maintain or improve situation awareness.Design, Settings, and Participants:A 15‐week design thinking process was employed, involving research, ideation, and refinement to develop and implement new situation awareness tools. The process included engagement with interprofessional clinical teams, scenario planning, workflow mapping, iterative feedback collection, and collaboration with an industry partner for signage development and implementation.Intervention:Improved and updated communication devices and bedside mitigation plans.Main Outcome and Measures:Process metrics included individual and shared situation awareness of PICU care teams and our patient outcome metric was the rate of cardiopulmonary resuscitation (CPR) events pre‐ and post‐transition.Results:When evaluating all patients, shared situation awareness for accurate high‐risk status improved from 81% pre‐transition to 92% post‐transition (p = .006). When assessing individual care team roles, accuracy of patient high‐risk status improved from 88% to 95% (p = .05) for RNs, 85% to 96% (p = .003) for residents, and 88% to 95% (p = .03) for RTs. There was no change in the rate of CPR events following the transition.

Situational awareness (SA) is critical to properly operating active power distribution systems during normal and outage conditions. Appropriate SA tools should provide an accurate estimate of system voltage and current variables, the operational network topology, and the power injections from distributed energy sources (DERs), including behind-the-meter (BTM) photovoltaics (PVs). Obtaining an accurate SA, especially by estimating network topology and gross load demand, is increasingly challenging with the proliferation of BTM DERs with intermittent power generation. Moreover, the SA required for distribution system restoration is even more challenging after a medium to a prolonged outage due to inaccurate estimates of cold load pickup (CLPU) and switch statuses. This paper proposes an integrated real-time model update (RTMU) module for SA enhancement to help distribution system operators (DSOs) understand the power system conditions in dynamic and DER-rich environments. The proposed RTMU consists of several modules to obtain the required level of SA for operational decision-making. It includes estimators for a) BTM PV power, b) network topology, and c) CLPU. The proposed approaches leverage multiple data resources, deep learning approaches, and domain knowledge of the power system to provide the required level of SA to DSOs. The dependencies among these modules are actively leveraged to enhance SA under normal conditions and during power outages. We demonstrate and analyze the performance of the proposed RTMU on a modified IEEE 123-node feeder and a utility distribution system from the Western United States.

New air traffic control concepts and automation tools designed to improve the capacity of the National Airspace System are continually researched, including those that test early prototypes and their impact on the operators to adequately perform the task at hand. This study investigated the workload, situation awareness and other human factors issues related to using a prototype surface automation tool (“GoSAFE-Ground Operations Situation Awareness and Efficiency Tool”) for managing precision taxi operations, with increased traffic relative to current day operations. Our team of controller participants working four air traffic positions handled airport traffic using GoSAFE under two different levels of automation: (1) Mixed voice/datalink [partially equipped] and (2) Datalink only [fully equipped]. The study found statistically significant differences on workload due to automation level. The impact of automation was also investigated for the four air traffic control positions. Results on one situation awareness measure were largely consistent with the workload findings. While realizing these differences, workload and situation awareness levels remained manageable and reasonable across all conditions and positions. Our controller participants also reported acceptability and feasibility ratings and provided feedback on the usability of the user interface. Results suggested that the GoSAFE automation helped the participants cope with the differences in their respective areas of responsibility and an increased volume of traffic, while maintaining adequate information resources required for effective air traffic control operations. The study-participants did have difficulty with some of the interface characteristics of the automation tool, such as use of color and data block size. As with any prototype surface automation tool, additional research and development needs to address these types of issues in order to insure effective use of the tool. This research will make it possible to ascertain the future impact of the tool on other system characteristics such as throughput and safety.

Timely and accurate situational awareness is one of the key elements of any effective military campaign. As such, significant effort has been invested in the DoD to share location, blue force tracking, and other track data to enable commanders to make effective decisions. What has been less available are network and link visualization tools for network administrators at the tactical edge to quickly diagnose problems and assess the performance of highly intermittent networks. Although many radio systems have built-in proprietary tools that show connectivity diagrams, these tools are extremely difficult to adapt to other systems due to their closed nature. In this paper, we present a real-time open source network visualization tool for rapid network and link situational awareness on heterogeneous networks. Using widely available software such as Google Earth and various distribution systems, we show that network connectivity over several heterogeneous radio systems can be easily visualized to aid in decision making.1