Hospital infectious disease emergency preparedness youtube,emergency food storage in a nutshell unplugged,black american christian movies youtube,survival zombie map list - Step 1

Dugas AF, Morton M, Beard R, Pines JM, Bayram JD, Hsieh Y, Kelen G, Uscher-Pines L, Jeng K, Cole G, Rothman R. Citation Dugas AF, Morton M, Beard R, Pines JM, Bayram JD, Hsieh Y, Kelen G, Uscher-Pines L, Jeng K, Cole G, Rothman R.
Department of Emergency Medicine, Johns Hopkins University, Baltimore, Maryland, United States.
Departments of Emergency Medicine and Health Policy, George Washington University, Washington, District of Columbia, United States. Department of Emergency Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA. Objective: To identify and prioritize potential Emergency Department (ED) and hospital-based interventions which could mitigate the impact of crowding during patient surge from a widespread infectious respiratory disease outbreak and determine potential data sources that may be useful for triggering decisions to implement these high priority interventions. Design: Expert panel utilizing Nominal Group Technique to identify and prioritize interventions, and in addition, determine appropriate “triggers” for implementation of the high priority interventions in the context of four different infectious respiratory disease scenarios that vary by patient volumes (high versus low) and illness severity (high versus low). Participants: Regional and national experts representing the fields of public health, disease surveillance, clinical medicine, ED operations, and hospital operations. Main Outcome Measure: Prioritized list of potential interventions to reduce ED and hospital crowding, respectively. Results: High priority interventions to mitigate ED surge included standardizing admission and discharge criteria and instituting infection control measures. Conclusions: We developed a prioritized list of potentially useful interventions to mitigate ED and hospital crowding in various outbreak scenarios. This work was supported by the Department of Homeland Security (PACER: National Center for Study of Preparedness and Response [2010-ST-061-PA0001]). To maintain high-quality care and manage the increase in ED volumes during an infectious respiratory disease outbreak, hospitals and EDs must have a response plan with the ability to implement timely and effective interventions designed to increase capacity and diminish the effects of crowding which can directly impact patient safety and quality of care. Utilizing the opinions of an expert panel, we compared and prioritized ED and hospital interventions to mitigate the impact of a surge due to infectious respiratory disease outbreaks with varying patient volume and severity of illness. We convened an expert panel for a one-day conference on November 4th, 2011 in Baltimore, Maryland. To accomplish our objectives, we used a mixed-methods design, involving an initial survey instrument followed by in-person discussion utilizing nominal group technique.15,16 Prior to the conference, the study team members (AD, MM, RB, KJ, RR) performed a review of the existing academic literature to identify potential ED and hospital-based interventions to manage crowding from a respiratory infectious disease outbreak. This initial list of potential interventions was distributed to the 34 invited panelists who committed to attend the conference one month in advance.
Panelists were instructed to separately rate each intervention by both ease of implementation and importance for each of the four infectious respiratory disease outbreak scenarios using a 1-5 Likert scale.
A full 1-day conference was held at the National Center for the Study of Preparedness and Catastrophic Response (PACER).17 Overview presentations were conducted by selected experts summarizing the current state of emergency department and hospital crowding, existing and novel surveillance mechanisms, and potential interventions to mitigate crowding as published in the peer-reviewed literature. During Exercise One, panelists were asked to prioritize potential interventions to mitigate surge in response to an infectious respiratory disease outbreak for each of four defined scenarios. In Exercise Two, panelists were asked to identify key data sources to trigger the implementation of a specific intervention in a given respiratory virus illness scenario.
To evaluate data from Exercise One, final categorization data were assigned a numerical score where Low Priority = 1, Medium Priority =3, and High Priority =5.
The highest ranked interventions noted above were chosen for subsequent prioritization of potential data elements to employ as triggers (Table 5).
Many EDs and hospitals are currently operating at or over capacity much of the time, where even small increases in patient volumes, such as those seen during seasonal influenza, worsen ED crowding and further prolong patient waiting times, which has been shown to be associated with untoward patient outcomes.1,6,7,8,9,10,18,19,20 A large-scale infectious respiratory disease outbreak requires advanced medical center planning and response in order to maintain good ED and hospital flow, and avoid any associated adverse impacts on patient care or outcomes. For ED settings, panelists gave overall higher priority to interventions in outbreak scenarios with high volume of patient visits, indicating the greatest concern for addressing outbreaks where ED crowding caused by sudden increased patient volume might worsen regardless of disease severity.
When considering hospital crowding, the panelists overall prioritized measures aimed at outbreaks with high severity. This study evaluates the priority of interventions across a variety of potential infectious respiratory disease outbreak scenarios encompassing a range of patient volumes and disease severities. Similar to other group consensus methods, results can vary based on the composition of the group. Information generated from these exercises may serve to guide ED and hospital administrators to focus on the highest-priority interventions for a particular scenario, based on anticipated patient volumes or disease severity. Although many of the highly rated interventions require, or would benefit from, coordination with departments of public health, local medical centers, and local and federal governments, the decision of whether and when to implement many of these interventions currently appears to occur at the medical center level. Expert panelists placed highest priority on ED interventions to mitigate surge in the setting of an infectious respiratory disease outbreak scenario with high patient volume, indicating the greatest concern for addressing outbreaks where ED crowding caused by sudden increased patient volume might worsen regardless of disease severity. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention (CDC). The Access Center at Albany Med facilitates patient transfers from other health care facilities to Albany Medical Center Hospital. Pediatric Infectious Diseases Our specialists work to help fight, treat and manage infectious diseases and other contagious illnesses affecting children. Pediatric infectious disease at Albany Med provides outpatient and inpatient for the evaluation and management of children and adolescents to age 18 with serious infections including but not limited to recurrent fevers, skin infections, Lyme disease and evaluation of children traveling to and from foreign countries.
Our physicians are also pediatric HIV specialists and providers for the Maternal Child Adolescent Treatment Services (MCATS) program.


Interventions to Mitigate Emergency Department and Hospital Crowding During an Infectious Respiratory Disease Outbreak: Results from an Expert Panel. Although there are numerous reports in the literature describing various interventions designed to mitigate ED and hospital crowding due to infectious respiratory disease outbreaks, it is difficult to compare the impact of interventions across sites due to lack of standardized outcome measures, as well as variability in medical center structure, patient populations, and the particular characteristics and dynamics of an individual outbreak.11,12,13,14 Furthermore, medical centers tend to implement multiple responses during an outbreak to help control both short and long-term patient surges, further complicating attempts to independently and accurately evaluate the impact of any individual intervention on the outcomes of interest, namely maintaining timely care within the ED and hospital. A secondary objective was to prioritize potential data sources which might trigger the decision to implement ED or hospital-based interventions for each of the outbreak types. In addition, study investigators distributed definitions and brief descriptions of four types of infectious respiratory disease outbreaks to allow the panelists the opportunity to express their varied opinions on interventions relative to expected patient volume and severity of illness.
Ease of implementation included: consideration of factors such as cost, operational complexity, facility (time) of setup, and intensity of resource utilization.
The conference leaders then presented the results of the pre-conference survey and distributed these results to the panelists in tabular form. Interventions were separated into two groups; those specifically for patients presenting with influenza-like illness (ILI) and those for patients without ILI. Considering the worst case scenario (high volume and high severity) and the recent 2009 H1N1 scenario (high volume, low severity), each group was given one intervention, which was highly rated in Exercise One, for each of the four scenarios. These numerical scores were averaged by scenario to obtain a numerical final score for each intervention in each scenario.
Tables 1 and 2 demonstrate the final ED scenario-based prioritization for each potential intervention for both ILI patients (Table 1), and non-ILI patients (Table 2).
Individual scenario-based ratings for the hospital interventions are shown in Tables 3 and 4. ED interventions selected were: (1) establishing an ED annex (1918 H1N1 Scenario), and (2) constructing a website to advise patients on the most appropriate setting for care (2009 H1N1 Scenario).
Although some interventions to manage ED and hospital crowding can be carried out at the institutional level, others, as noted by our expert panelists, require coordination with the local public health department, neighboring medical centers, or state and federal government to ensure alignment with the existing level of regulatory standards (e.g. To address a high patient volume outbreak, panelists prioritized several interventions, such as creating a website or telephone call center, to advise patients when to seek medical care and what the most appropriate setting for that care would be. Unlike ED volume issues which are more related to overall patient volume, severity of illness, even with low volume of patients, stressed demand for inpatient resources such as hospital beds, intensive care unit (ICU) space and ventilators.
Although the exercise was designed to assess multiple epidemiological scenarios, it is often the case that the exact parameters of the outbreak (i.e.
To mitigate this potential selection bias, we selected individuals across a wide range of expertise who are integral to the process of disease surveillance and implementation of clinical interventions. However, there is a need for more formal methods of assessing intervention quality and efficacy. Further, virtually all of the most highly rated data sources to trigger the decision of when to implement these interventions are collected directly by individual hospitals or EDs. This program is funded through the New York State Department of Health AIDS Institute and provides for multidisciplinary medical and support services to infants, children and adolescents to age 24A living with or at risk for HIV. For example, outbreaks can manifest as high or low severity of illness, and high or low levels of contagion, which ultimately contributes to the volume of patients seeking care. Of the 66 panelists invited, 34 (52%) attended the one day conference and were offered financial reimbursed for basic travel expenses only. Importance was defined as the likely effectiveness of the intervention in reducing ED or hospital crowding or augmenting surge.
After these initial presentations, the panelists completed two exercises for which they were assigned to one of two equally sized groups, based upon panelists’ relevant expertise. Infection control measures were included among the proposed interventions to focus efforts toward reducing disease spread and potentially reducing future patient volume. Additionally, each group was given a list of potential data sources based on those used in the literature, current medical practice, and current surveillance systems, but was also encouraged to consider and suggest alternate data sources that may serve as a “trigger” for implementation of the selected intervention. The hospital interventions selected were: (1) developing and implementing a ventilator triage protocol (1918 H1N1 Scenario), and (2) establishing alternate care sites (2009 H1N1 Scenario). Other highly ranked ED interventions were simple precautionary measures to protect non-ILI patients from being infected, such as hand sanitizers, masks, and cohorting infected patients, which are likely to have a delayed impact on ED crowding. Here, the highly rated interventions also focused on measures to protect staff and non-ILI patients from disease transmission, including setting up an inpatient quarantine area and stockpiling isolation equipment. These selected individuals represented those in decision making positions from numerous geographic regions and organizations, academic institutions and levels of government.
Although conducting randomized controlled trials may not be possible for public health interventions, standardizing reporting and assessment of interventions could provide a framework for describing and comparing interventions which could be reported in the literature. These data sources, such as ED and hospital volume and admission rates, and ED waiting times, are institutional data, monitored closely at the institutional level, but frequently have lags before reporting and analysis at the public health level. Conversely, panelists concluded that interventions addressing disease severity were the most important for inpatient management, operations and resource distribution, with less emphasis decreasing total numbers affected in the population. Hence, it is unclear if a single set of preparedness protocols would address varying types of outbreaks with differential volume of patients and severity of illness.
Panelists were encouraged to suggest additional “write-in” interventions not already listed. One group evaluated ED-based interventions, and one evaluated hospital-based interventions.


Examples of such data sources included ED wait times, hospital volume, laboratory data, syndromic and laboratory-based surveillance systems, and novel data sources that might be used to indicate increasing respiratory disease (e.g.
Additionally, numerical scores were averaged across all scenarios to obtain a total prioritization score for each intervention across all scenarios. The main data sources identified to serve as triggers came largely from medical center level crowding data as can be seen in Table 5. Communication and coordination between all of these stakeholders increases the breadth of potential response options, and the overall effectiveness.
This is consistent with previous task force recommendations to maximize ICU resources (both beds and staffing) as well as maintain strict infectious control policies.24 Additionally, a treatment algorithm for antiviral use rated highly, as antivirals would likely be in short supply and would require appropriate, scenario-driven allocation management.
However, for either increased volume or severity outbreaks, respondents shifted prioritizations to those interventions requiring more intensive resources.
Thus, information gleaned from this exercise may be most helpful for understanding overall priority of interventions rather than their priority in a specific artificial scenario. However, the results represent panelist’s opinions, and not the results of a formal literature meta-analysis or quantitative data analysis of U.S.
Despite emphasis on infectious respiratory disease surveillance, surveillance tools did not rank in the top three triggers for any of the four included scenarios. Data useful for setting triggers to implement high priority measures were predominantly those available at the local institutional level. Given the inherent difficulty of analyzing the published literature, and lack of differentiation in the operational approach to the various types of major emerging infectious outbreaks, it is necessary to approach this problem through a mixed methods approach. The panelists represented the fields of public health (8), disease surveillance (15), clinical medicine (13), emergency medicine operations (8), hospital operations (6), and systems experts (7), with some panelists representing more than one field. Each group was co-moderated by two subject matter experts (AD, MM, JP, JB, GK) with previous training through numerous instructional meetings and two mock moderation sessions to ensure uniform and unbiased facilitation of the proceedings. ED and hospital) was asked to discuss each associated intervention, (including the pre-panel “write-in” interventions), and suggest and similarly discuss any additional interventions not yet considered. Finally, scores for each intervention within a scenario were averaged to obtain a scenario prioritization score.
Top rated data sources consisted mainly of patient volume metrics (hospital volume, ED volume, boarding time in the ED, percent of patients with ILI, hospital capacity), patient acuity metrics (acuity ratio, ED admission rate, number of low acuity ILI patients), as well as measures of resource availability (ventilator supply, and staff availability).
Beyond the individual responses, these same organizations, with appropriate and timely sharing of data, combined with current surveillance systems, can inform the timing of when to implement the appropriate response. To our knowledge, only one paper isolates an ED input intervention showing that an ED vaccination campaign reduces ED visits for respiratory illness by 34%.23 Despite this evidence, this particular input intervention (ED vaccination) was rated lower by this expert panel, suggesting that cost and ease of implementation were important factors considered by the panel. For example, for the high-volume, high severity outbreak scenario (1918 pandemic), establishing an ED annex, stockpiling equipment, and adding staff were rated as highest priority. However, given that there is often some advanced indication of the nature of an impending outbreak, and outbreak characteristics such as volume and severity affect prioritization of resulting interventions, detailed prioritization based on the volume and severity of an outbreak may prove beneficial. These recommendations highlight the importance of advancing capabilities of surveillance systems to collect and coalesce institutional data sources in a timely manner, to provide both public health departments and medical institutions with better situational awareness which could improve the timeliness and effectiveness of planned responses. Strikingly, public health surveillance data were not considered as one of the top triggers to operationalize any of the priority measures, either for the ED or the inpatient services. Representatives included those from the federal organizations (2), state and city health departments (6), corporate and non-profit organizations (2), and academic institutions (24). Panel members were then asked to anonymously and independently categorize each intervention as low, medium, or high priority.
Panelists were asked to individually select the top three data sources that could be useful to ED or hospital leaders to “trigger” the decision to implement the top-rated interventions to mitigate ED or hospital crowding due to a respiratory infection outbreak. For Exercise Two, the individual resultant ratings for each potential data source were averaged to obtain a mean “importance” score for each potential data source. This expert panel sought to combine knowledge and experience of leaders in each of these fields to provide initial broad guidance and recommendations for prioritization and implementation of responses to mitigate crowding in the event of an infectious respiratory disease outbreak.
Although further breakdown of the rankings according to the panelists self-identified expert group category would be an interesting analysis, this was not possible as several panelists identified themselves as belonging to more than one expert group, preventing clear categorization.
We believe this study represents the first step in delineating high impact interventions according to hospital service (ED verses inpatient) and infectious disease outbreak characteristics. This study was reviewed and approved by the Institutional Review Board with a waiver of consent. Panelists were asked to consider both the ease of implementation and importance for a final overall priority consideration specific for each of the four respiratory infection outbreak scenarios. Similarly, using the nominal group technique, panelists proposed other potential data sources. All potential data sources were discussed and each panel member anonymously rated them on a 1-5 Likert scale with 1 being “not at all important” as a trigger and 5 as “very important” for a trigger for the selected interventions.
Systematic Review of Interventions to Mitigate the Effect of Emergency Department Crowding in the Event of a Respiratory Disease Outbreak.



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