Information Challenges Associated With Accessing and Sharing of Patient Information in Disasters: A Qualitative Analysis.

As disasters increase in frequency and severity, so too does the health impact on affected populations. Disasters exacerbate the already challenging health information-sharing landscape. A reduced capacity to access and share patient information may have negative impacts on providers' ability to care for patients individually and to address disaster health outcomes at the population level. Between October 2018 and July 2019, we conducted 21 semistructured interviews with physicians experienced in providing healthcare during disasters to understand the challenges related to patient information sharing in disaster responses. Key informants noted challenges with patient information management-including accessing, sharing, and transferring information-and that it was a barrier to providing effective clinical care in disasters. Three major areas were identified as challenges: (1) lack of systematic mechanisms for patient information sharing during disaster handoffs, (2) lack of access to a patient's past medical history, and (3) population-level impacts of patient information-sharing breakdowns in disasters. Reducing barriers to effective patient information sharing is a critical need during disasters. Requirements generally fall to overburdened clinicians, and novel solutions that ease this responsibility and leverage existing infrastructure should be explored. Work conducted during the COVID-19 pandemic may inform new solutions. Integrated approaches that support information sharing in real time will improve patient care at the individual level and can support operational improvements to current and future disaster responses.

Applying an Innovative Model of Disaster Resilience at the Neighborhood Level : The COPEWELL New York City Experience.

Community resilience is a community's ability to maintain functioning (ie, delivery of services) during and after a disaster event. The Composite of Post-Event Well-Being (COPEWELL) is a system dynamics model of community resilience that predicts a community's disaster-specific functioning over time. We explored COPEWELL's usefulness as a practice-based tool for understanding community resilience and to engage partners in identifying resilience-strengthening strategies. In 2014, along with academic partners, the New York City Department of Health and Mental Hygiene organized an interdisciplinary work group that used COPEWELL to advance cross-sector engagement, design approaches to understand and strengthen community resilience, and identify local data to explore COPEWELL implementation at neighborhood levels. The authors conducted participant interviews and collected shared experiences to capture information on lessons learned. The COPEWELL model led to an improved understanding of community resilience among agency members and community partners. Integration and enhanced alignment of efforts among preparedness, disaster resilience, and community development emerged. The work group identified strategies to strengthen resilience. Searches of neighborhood-level data sets and mapping helped prioritize communities that are vulnerable to disasters (eg, medically vulnerable, socially isolated, low income). These actions increased understanding of available data, identified data gaps, and generated ideas for future data collection. The COPEWELL model can be used to drive an understanding of resilience, identify key geographic areas at risk during and after a disaster, spur efforts to build on local metrics, and result in innovative interventions that integrate and align efforts among emergency preparedness, community development, and broader public health initiatives.

The COPEWELL Rubric: A Self-Assessment Toolkit to Strengthen Community Resilience to Disasters.

Measurement is a community endeavor that can enhance the ability to anticipate, withstand, and recover from a disaster, as well as foster learning and adaptation. This project's purpose was to develop a self-assessment toolkit-manifesting a bottom-up, participatory approach-that enables people to envision community resilience as a concrete, desirable, and obtainable goal; organize a cross-sector effort to evaluate and enhance factors that influence resilience; and spur adoption of interventions that, in a disaster, would lessen impacts, preserve community functioning, and prompt a more rapid recovery. In 2016-2018, we engaged in a process of literature review, instrument development, stakeholder engagement, and local field-testing, to produce a self-assessment toolkit (or "rubric") built on the Composite of Post-Event Well-being (COPEWELL) model that predicts post-disaster community functioning and resilience. Co-developing the rubric with community-based users, we generated self-assessment instruments and process guides that localities can more readily absorb and adapt. Applied in three field tests, the Social Capital and Cohesion materials equip users to assess this domain at different geo-scales. Chronicling the rubric's implementation, this account sheds further light on tensions between community resilience assessment research and practice, and potential reasons why few of the many current measurement systems have been applied.

COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters.

OBJECTIVE: Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster. METHODS: We developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties. RESULTS: The conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature. CONCLUSIONS: The work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience. (Disaster Med Public Health Preparedness. 2018;12:127-137).

Use of Sub-Ensembles and Multi-Template Observers to Evaluate Detection Task Performance for Data That are Not Multivariate Normal.

The Hotelling Observer (HO) is widely used to evaluate image quality in medical imaging. However, applying it to data that are not multivariate-normally (MVN) distributed is not optimal. In this paper, we apply two multi-template linear observer strategies to handle such data. First, the entire data ensemble is divided into sub-ensembles that are exactly or approximately MVN and homoscedastic. Next, a different linear observer template is estimated for and applied to each sub-ensemble. The first multi-template strategy, adapted from previous work, applies the HO to each sub-ensemble, calculates the area under the receiver operating characteristics curve (AUC) for each sub-ensemble, and averages the AUCs from all the sub-ensembles. The second strategy applies the Linear Discriminant (LD) to estimate test statistics for each sub-ensemble and calculates a single global AUC using the pooled test statistics from all the sub-ensembles. We show that this second strategy produces the maximum AUC when only shifting of the HO test statistics is allowed. We compared these strategies to the use of a single HO template for the entire data ensemble by applying them to the non-MVN data obtained from reconstructed images of a realistic simulated population of myocardial perfusion SPECT studies with the goal of optimizing the reconstruction parameters. Of the strategies investigated, the multi-template LD strategy yielded the highest AUC for any given set of reconstruction parameters. The optimal reconstruction parameters obtained by the two multi-template strategies were comparable and produced higher AUCs for each sub-ensemble than the single-template HO strategy.

Collimator optimization in myocardial perfusion SPECT using the ideal observer and realistic background variability for lesion detection and joint detection and localization tasks.

In SPECT imaging, collimators are a major factor limiting image quality and largely determine the noise and resolution of SPECT images. In this paper, we seek the collimator with the optimal tradeoff between image noise and resolution with respect to performance on two tasks related to myocardial perfusion SPECT: perfusion defect detection and joint detection and localization. We used the Ideal Observer (IO) operating on realistic background-known-statistically (BKS) and signal-known-exactly (SKE) data. The areas under the receiver operating characteristic (ROC) and localization ROC (LROC) curves (AUCd, AUCd+l), respectively, were used as the figures of merit for both tasks. We used a previously developed population of 54 phantoms based on the eXtended Cardiac Torso Phantom (XCAT) that included variations in gender, body size, heart size and subcutaneous adipose tissue level. For each phantom, organ uptakes were varied randomly based on distributions observed in patient data. We simulated perfusion defects at six different locations with extents and severities of 10% and 25%, respectively, which represented challenging but clinically relevant defects. The extent and severity are, respectively, the perfusion defect's fraction of the myocardial volume and reduction of uptake relative to the normal myocardium. Projection data were generated using an analytical projector that modeled attenuation, scatter, and collimator-detector response effects, a 9% energy resolution at 140 keV, and a 4 mm full-width at half maximum (FWHM) intrinsic spatial resolution. We investigated a family of eight parallel-hole collimators that spanned a large range of sensitivity-resolution tradeoffs. For each collimator and defect location, the IO test statistics were computed using a Markov Chain Monte Carlo (MCMC) method for an ensemble of 540 pairs of defect-present and -absent images that included the aforementioned anatomical and uptake variability. Sets of test statistics were computed for both tasks and analyzed using ROC and LROC analysis methodologies. The results of this study suggest that collimators with somewhat poorer resolution and higher sensitivity than those of a typical low-energy high-resolution (LEHR) collimator were optimal for both defect detection and joint detection and localization tasks in myocardial perfusion SPECT for the range of defect sizes investigated. This study also indicates that optimizing instrumentation for a detection task may provide near-optimal performance on the more challenging detection-localization task.

Collimator optimization and collimator-detector response compensation in myocardial perfusion SPECT using the ideal observer with and without model mismatch and an anthropomorphic model observer.

The collimator is the primary factor that determines the spatial resolution and noise tradeoff in myocardial perfusion SPECT images. In this paper, the goal was to find the collimator that optimizes the image quality in terms of a perfusion defect detection task. Since the optimal collimator could depend on the level of approximation of the collimator-detector response (CDR) compensation modeled in reconstruction, we performed this optimization for the cases of modeling the full CDR (including geometric, septal penetration and septal scatter responses), the geometric CDR, or no model of the CDR. We evaluated the performance on the detection task using three model observers. Two observers operated on data in the projection domain: the Ideal Observer (IO) and IO with Model-Mismatch (IO-MM). The third observer was an anthropomorphic Channelized Hotelling Observer (CHO), which operated on reconstructed images. The projection-domain observers have the advantage that they are computationally less intensive. The IO has perfect knowledge of the image formation process, i.e. it has a perfect model of the CDR. The IO-MM takes into account the mismatch between the true (complete and accurate) model and an approximate model, e.g. one that might be used in reconstruction. We evaluated the utility of these projection domain observers in optimizing instrumentation parameters. We investigated a family of 8 parallel-hole collimators, spanning a wide range of resolution and sensitivity tradeoffs, using a population of simulated projection (for the IO and IO-MM) and reconstructed (for the CHO) images that included background variability. We simulated anterolateral and inferior perfusion defects with variable extents and severities. The area under the ROC curve was estimated from the IO, IO-MM, and CHO test statistics and served as the figure-of-merit. The optimal collimator for the IO had a resolution of 9-11 mm FWHM at 10 cm, which is poorer resolution than typical collimators used for MPS. When the IO-MM and CHO used a geometric or no model of the CDR, the optimal collimator shifted toward higher resolution than that obtained using the IO and the CHO with full CDR modeling. With the optimal collimator, the IO-MM and CHO using geometric modeling gave similar performance to full CDR modeling. Collimators with poorer resolution were optimal when CDR modeling was used. The agreement of rankings between the IO-MM and CHO confirmed that the IO-MM is useful for optimization tasks when model mismatch is present due to its substantially reduced computational burden compared to the CHO.

Optimization of energy window and evaluation of scatter compensation methods in myocardial perfusion SPECT using the ideal observer with and without model mismatch and an anthropomorphic model observer.

We used the ideal observer (IO) and IO with model mismatch (IO-MM) applied in the projection domain and an anthropomorphic channelized Hotelling observer (CHO) applied to reconstructed images to optimize the acquisition energy window width and to evaluate various scatter compensation methods in the context of a myocardial perfusion single-photon emission computed tomography (SPECT) defect detection task. The IO has perfect knowledge of the image formation process and thus reflects the performance with perfect compensation for image-degrading factors. Thus, using the IO to optimize imaging systems could lead to suboptimal parameters compared with those optimized for humans interpreting SPECT images reconstructed with imperfect or no compensation. The IO-MM allows incorporating imperfect system models into the IO optimization process. We found that with near-perfect scatter compensation, the optimal energy window for the IO and CHO was similar; in its absence, the IO-MM gave a better prediction of the optimal energy window for the CHO using different scatter compensation methods. These data suggest that the IO-MM may be useful for projectiondomain optimization when MM is significant and that the IO is useful when followed by reconstruction with good models of the image formation process.

Optimization and comparison of simultaneous and separate acquisition protocols for dual isotope myocardial perfusion SPECT.

Dual-isotope simultaneous-acquisition (DISA) rest-stress myocardial perfusion SPECT (MPS) protocols offer a number of advantages over separate acquisition. However, crosstalk contamination due to scatter in the patient and interactions in the collimator degrade image quality. Compensation can reduce the effects of crosstalk, but does not entirely eliminate image degradations. Optimizing acquisition parameters could further reduce the impact of crosstalk. In this paper we investigate the optimization of the rest Tl-201 energy window width and relative injected activities using the ideal observer (IO), a realistic digital phantom population and Monte Carlo (MC) simulated Tc-99m and Tl-201 projections as a means to improve image quality. We compared performance on a perfusion defect detection task for Tl-201 acquisition energy window widths varying from 4 to 40 keV centered at 72 keV for a camera with a 9% energy resolution. We also investigated 7 different relative injected activities, defined as the ratio of Tc-99m and Tl-201 activities, while keeping the total effective dose constant at 13.5 mSv. For each energy window and relative injected activity, we computed the IO test statistics using a Markov chain Monte Carlo (MCMC) method for an ensemble of 1,620 triplets of fixed and reversible defect-present, and defect-absent noisy images modeling realistic background variations. The volume under the 3-class receiver operating characteristic (ROC) surface (VUS) was estimated and served as the figure of merit. For simultaneous acquisition, the IO suggested that relative Tc-to-Tl injected activity ratios of 2.6-5 and acquisition energy window widths of 16-22% were optimal. For separate acquisition, we observed a broad range of optimal relative injected activities from 2.6 to 12.1 and acquisition energy window of widths 16-22%. A negative correlation between Tl-201 injected activity and the width of the Tl-201 energy window was observed in these ranges. The results also suggested that DISA methods could potentially provide image quality as good as that obtained with separate acquisition protocols. We compared observer performance for the optimized protocols and the current clinical protocol using separate acquisition. The current clinical protocols provided better performance at a cost of injecting the patient with approximately double the injected activity of Tc-99m and Tl-201, resulting in substantially increased radiation dose.

Building a national model of public mental health preparedness and community resilience: validation of a dual-intervention, systems-based approach.

OBJECTIVE: Working within a series of partnerships among an academic health center, local health departments (LHDs), and faith-based organizations (FBOs), we validated companion interventions to address community mental health planning and response challenges in public health emergency preparedness. METHODS: We implemented the project within the framework of an enhanced logic model and employed a multi-cohort, pre-test/post-test design to assess the outcomes of 1-day workshops in psychological first aid (PFA) and guided preparedness planning (GPP). The workshops were delivered to urban and rural communities in eastern and midwestern regions of the United States. Intervention effectiveness was based on changes in relevant knowledge, skills, and attitudes (KSAs) and on several behavioral indexes. RESULTS: Significant improvements were observed in self-reported and objectively measured KSAs across all cohorts. Additionally, GPP teams proved capable of producing quality drafts of basic community disaster plans in 1 day, and PFA trainees confirmed upon follow-up that their training proved useful in real-world trauma contexts. We documented examples of policy and practice changes at the levels of local and state health departments. CONCLUSIONS: Given appropriate guidance, LHDs and FBOs can implement an effective and potentially scalable model for promoting disaster mental health preparedness and community resilience, with implications for positive translational impact.

An academic-government-faith partnership to build disaster mental health preparedness and community resilience.

OBJECTIVES: Faculty and affiliates of the Johns Hopkins Preparedness and Emergency Response Research Center partnered with local health departments and faith-based organizations to develop a dual-intervention model of capacity-building for public mental health preparedness and community resilience. Project objectives included (1) determining the feasibility of the tri-partite collaborative concept; (2) designing, delivering, and evaluating psychological first aid (PFA) training and guided preparedness planning (GPP); and (3) documenting preliminary evidence of the sustainability and impact of the model. METHODS: We evaluated intervention effectiveness by analyzing pre- and post-training changes in participant responses on knowledge-acquisition tests administered to three urban and four rural community cohorts. Changes in percent of correct items and mean total correct items were evaluated. Criteria for model sustainability and impact were, respectively, observations of nonacademic partners engaging in efforts to advance post-project preparedness alliances, and project-attributable changes in preparedness-related practices of local or state governments. RESULTS: The majority (11 of 14) test items addressing technical or practical PFA content showed significant improvement; we observed comparable testing results for GPP training. Government and faith partners developed ideas and tools for sustaining preparedness activities, and numerous project-driven changes in local and state government policies were documented. CONCLUSIONS: Results suggest that the model could be an effective approach to promoting public health preparedness and community resilience.

Translating legal research on mental and behavioral health during emergencies for the public health workforce.

Translation strategies are critical for sharing research with public health practitioners. To disseminate our analyses of legal issues that arise relative to mental and behavioral health during emergencies, we created 10 brief translational tools for members of the public health workforce. In consultation with an interdisciplinary project advisory group (PAG), we identified each tool's topic and format. PAG members reviewed draft and final versions of the tools. We then worked with local health departments throughout the country to distribute the tools along with a brief survey to determine practitioners' perceived utility of the tools. Through survey responses, we learned that practitioners believed the tools provided information that would be useful during the planning, response, and recovery phases of an emergency. This article describes the creation of the PAG, the development of the tools, and lessons learned for those seeking to translate legal and ethical research findings for practitioner audiences.

The development of a model of psychological first aid for non-mental health trained public health personnel: the Johns Hopkins RAPID-PFA.

INTRODUCTION: The Johns Hopkins Center for Public Health Preparedness, which houses the Centers for Disease Control and Prevention-funded Preparedness and Emergency Response Learning Center, has been addressing the challenge of disaster-caused behavioral health surge by conducting training programs in psychological first aid (PFA) for public health professionals. This report describes our approach, named RAPID-PFA, and summarizes training evaluation data to determine if relevant knowledge, skills, and attitudes are imparted to trainees to support effective PFA delivery. BACKGROUND/RATIONALE: In the wake of disasters, there is an increase in psychological distress and dysfunction among survivors and first responders. To meet the challenges posed by this surge, a professional workforce trained in PFA is imperative. METHODS/ACTIVITY: More than 1500 participants received a 1-day RAPID-PFA training. Pre-/postassessments were conducted to measure (a) required knowledge to apply PFA; (b) perceived self-efficacy, that is, belief in one's own ability, to apply PFA techniques; and (c) confidence in one's own resilience in a crisis context. Statistical techniques were used to validate the extent to which the survey successfully measured individual PFA constructs, that is, unidimensionality, and to quantify the reliability of the assessment tool. RESULTS/OUTCOME: Statistically significant pre-/postimprovements were observed in (a) knowledge items supportive of PFA delivery, (b) perceived self-efficacy to apply PFA interventions, and (c) confidence about being a resilient PFA provider. Cronbach alpha coefficients ranging from 0.87 to 0.90 suggested that the self-reported measures possessed sufficient internal consistency. DISCUSSION: Findings were consistent with our pilot work, and with our complementary research initiatives validating a variant of RAPID-PFA with faith communities. LESSONS LEARNED/NEXT STEPS: The RAPID-PFA model promises to be a broadly applicable approach to extending community behavioral health surge capacity. Relevant next steps include evaluating the effectiveness of trained providers in real crisis situations, and determining if PFA training may have potential beyond the disaster context.

Design of the national health security preparedness index.

The importance of health security in the United States has been highlighted by recent emergencies such as the H1N1 influenza pandemic, Superstorm Sandy, and the Boston Marathon bombing. The nation's health security remains a high priority today, with federal, state, territorial, tribal, and local governments, as well as nongovernment organizations and the private sector, engaging in activities that prevent, protect, mitigate, respond to, and recover from health threats. The Association of State and Territorial Health Officials (ASTHO), through a cooperative agreement with the Centers for Disease Control and Prevention (CDC) Office of Public Health Preparedness and Response (OPHPR), led an effort to create an annual measure of health security preparedness at the national level. The collaborative released the National Health Security Preparedness Index (NHSPI(™)) in December 2013 and provided composite results for the 50 states and for the nation as a whole. The Index results represent current levels of health security preparedness in a consistent format and provide actionable information to drive decision making for continuous improvement of the nation's health security. The overall 2013 National Index result was 7.2 on the reported base-10 scale, with areas of greater strength in the domains of health surveillance, incident and information management, and countermeasure management. The strength of the Index relies on the interdependencies of the many elements in health security preparedness, making the sum greater than its parts. Moving forward, additional health security-related disciplines and measures will be included alongside continued validation efforts.

Design of a digital phantom population for myocardial perfusion SPECT imaging research.

Digital phantoms and Monte Carlo (MC) simulations have become important tools for optimizing and evaluating instrumentation, acquisition and processing methods for myocardial perfusion SPECT (MPS). In this work, we designed a new adult digital phantom population and generated corresponding Tc-99m and Tl-201 projections for use in MPS research. The population is based on the three-dimensional XCAT phantom with organ parameters sampled from the Emory PET Torso Model Database. Phantoms included three variations each in body size, heart size, and subcutaneous adipose tissue level, for a total of 27 phantoms of each gender. The SimSET MC code and angular response functions were used to model interactions in the body and the collimator-detector system, respectively. We divided each phantom into seven organs, each simulated separately, allowing use of post-simulation summing to efficiently model uptake variations. Also, we adapted and used a criterion based on the relative Poisson effective count level to determine the required number of simulated photons for each simulated organ. This technique provided a quantitative estimate of the true noise in the simulated projection data, including residual MC simulation noise. Projections were generated in 1 keV wide energy windows from 48-184 keV assuming perfect energy resolution to permit study of the effects of window width, energy resolution, and crosstalk in the context of dual isotope MPS. We have developed a comprehensive method for efficiently simulating realistic projections for a realistic population of phantoms in the context of MPS imaging. The new phantom population and realistic database of simulated projections will be useful in performing mathematical and human observer studies to evaluate various acquisition and processing methods such as optimizing the energy window width, investigating the effect of energy resolution on image quality and evaluating compensation methods for degrading factors such as crosstalk in the context of single and dual isotope MPS.

EPPM and willingness to respond: the role of risk and efficacy communication in strengthening public health emergency response systems.

This study examines the attitudinal impact of an Extended Parallel Process Model (EPPM)-based training curriculum on local public health department (LHD) workers' willingness to respond to representative public health emergency scenarios. Data are from 71 U.S. LHDs in urban and rural settings across nine states. The study explores changes in response willingness and EPPM threat and efficacy appraisals between randomly assigned control versus intervention health departments, at baseline and 1 week post curriculum, through an EPPM-based survey/resurvey design. Levels of response willingness and emergency response-related attitudes/beliefs are measured. Analyses focus on two scenario categories that have appeared on a U.S. government list of scenarios of significant concern: a weather-related emergency and a radiological "dirty" bomb event (U.S. Department of Homeland Security, 2007). The greatest impact from the training intervention on response willingness was observed among LHD workers who had low levels of EPPM-related threat and efficacy perceptions at baseline. Self-efficacy and response efficacy and response willingness increased in intervention LHDs for both scenarios, with greater response willingness increases observed for the radiological "dirty" bomb terrorism scenario. Findings indicate the importance of building efficacy versus enhancing threat perceptions as a path toward greater response willingness, and suggest the potential applicability of such curricular interventions for boosting emergency response willingness among other cadres of health providers.

Psychological first aid: a consensus-derived, empirically supported, competency-based training model.

Surges in demand for professional mental health services occasioned by disasters represent a major public health challenge. To build response capacity, numerous psychological first aid (PFA) training models for professional and lay audiences have been developed that, although often concurring on broad intervention aims, have not systematically addressed pedagogical elements necessary for optimal learning or teaching. We describe a competency-based model of PFA training developed under the auspices of the Centers for Disease Control and Prevention and the Association of Schools of Public Health. We explain the approach used for developing and refining the competency set and summarize the observable knowledge, skills, and attitudes underlying the 6 core competency domains. We discuss the strategies for model dissemination, validation, and adoption in professional and lay communities.

Investigating and improving pedestrian safety in an urban environment.

BACKGROUND: Prompted by a series of fatal and nonfatal pedestrian-vehicle collisions, university leadership from one urban institution collaborated with its academic injury research center to investigate traffic-related hazards facing pedestrians. METHODS: This descriptive epidemiologic study used multiple data collection strategies to determine the burden of pedestrian injury in the target area. Data were collected in 2011 through a review of university crash reports from campus police; a systematic environmental audit and direct observations using a validated instrument and trained raters; and focus groups with faculty, students, and staff. Study findings were synthesized and evidence-informed recommendations were developed and disseminated to university leadership. RESULTS: Crash reports provided some indication of the risks on the streets adjacent to the campus. The environmental audit identified a lack of signage posting the speed limit, faded crosswalks, issues with traffic light and walk sign synchronization, and limited formal pedestrian crossings, which led to jaywalking. Focus groups participants described dangerous locations and times, signal controls and signage, enforcement of traffic laws, use of cell phones and iPods, and awareness of pedestrian safety. Recommendations to improve pedestrian safety were developed in accordance with the three E's of injury prevention (education, enforcement, and engineering), and along with plans for implementation and evaluation, were presented to university leadership. CONCLUSIONS: These results underscore the importance of using multiple methods to understand fully the problem, developing pragmatic recommendations that align with the three E's of injury prevention, and collaborating with leadership who have the authority to implement recommended injury countermeasures. These lessons are relevant for the many colleges and universities in urban settings where a majority of travel to offices, classrooms, and surrounding amenities are by foot.