Mahshid Abir

Design of a Model to Predict Surge Capacity Bottlenecks for Burn Mass Casualties at a Large Academic Medical Center

OBJECTIVES To design and test a model to predict surge capacity bottlenecks at a large academic medical center in response to a mass-casualty incident (MCI) involving multiple burn victims. METHODS Using the simulation software ProModel, a model of patient flow and anticipated resource use, according to principles of disaster management, was developed based upon historical data from the University Hospital of the University of Michigan Health System. Model inputs included: (a) age and weight distribution for casualties, and distribution of size and depth of burns; (b) rate of arrival of casualties to the hospital, and triage to ward or critical care settings; (c) eligibility for early discharge of non-MCI inpatients at time of MCI; (d) baseline occupancy of intensive care unit (ICU), surgical step-down, and ward; (e) staff availability-number of physicians, nurses, and respiratory therapists, and the expected ratio of each group to patients; (f) floor and operating room resources-anticipating the need for mechanical ventilators, burn care and surgical resources, blood products, and intravenous fluids; (g) average hospital length of stay and mortality rate for patients with inhalation injury and different size burns; and (h) average number of times that different size burns undergo surgery. Key model outputs include time to bottleneck for each limiting resource and average waiting time to hospital bed availability. RESULTS Given base-case model assumptions (including 100 mass casualties with an inter-arrival rate to the hospital of one patient every three minutes), hospital utilization is constrained within the first 120 minutes to 21 casualties, due to the limited number of beds. The first bottleneck is attributable to exhausting critical care beds, followed by floor beds. Given this limitation in number of patients, the temporal order of the ensuing bottlenecks is as follows: Lactated Ringers solution (4 h), silver sulfadiazine/Silvadene (6 h), albumin (48 h), thrombin topical (72 h), type AB packed red blood cells (76 h), silver dressing/Acticoat (100 h), bismuth tribromophenate/Xeroform (102 h), and gauze bandage rolls/Kerlix (168 h). The following items do not precipitate a bottleneck: ventilators, topical epinephrine, staplers, foams, antimicrobial non-adherent dressing/Telfa types A, B, or O blood. Nurse, respiratory therapist, and physician staffing does not induce bottlenecks. CONCLUSIONS This model, and similar models for non-burn-related MCIs, can serve as a real-time estimation and management tool for hospital capacity in the setting of MCIs, and can inform supply decision support for disaster management.

Transitions of Care for Stroke Patients: Opportunities to Improve Outcomes

The last 30 years have seen tremendous progress in primary and secondary stroke prevention in the United States with better control of hypertension, decreasing smoking rates, antithrombotic treatment for atrial fibrillation, use of statins, and blood transfusions for children with sickle cell disease.1 In 1996, intravenous tissue-type plasminogen activator was approved for treatment of acute ischemic stroke,2 and in 2014 to 2015, endovascular treatment of major arterial occlusion, primarily by stent retrievers, was demonstrated to result in better outcomes for patients with ischemic stroke when compared with patients treated with intravenous tissue-type plasminogen activator alone.3 During this same time period, the field of neurocritical care grew tremendously in terms of physician and nurse training, standardization of care, and technology. Finally, standardization and certification of primary and comprehensive stroke centers have improved the quality of acute stroke care and the use of secondary prevention medications when patients are hospitalized for acute stroke.4,5 These cumulative advances have resulted in the decline in stroke mortality rates from the third to the fifth cause of death in the United States.6 The bulk of these advances have occurred in 2 settings—the office of primary care physicians who manages stroke risk factors in persons with and without a prior stroke; and the acute care hospital. Yet, the stroke patient follows a complex path from first onset of symptoms to the years after the onset of stroke, and the transitions between the respective places of care along the path represent major challenges and opportunities. ### Transition From Place of Stroke Onset to Acute Hospital One of the first major transitions of care is when emergency medical services (EMS) respond to a 911 call for a potential stroke. EMS personnel assess …

Cluster Analysis of Acute Care Use Yields Insights for Tailored Pediatric Asthma Interventions

Study objective: We undertake this study to understand patterns of pediatric asthma‐related acute care use to inform interventions aimed at reducing potentially avoidable hospitalizations. Methods: Hospital claims data from 3 Camden city facilities for 2010 to 2014 were used to perform cluster analysis classifying patients aged 0 to 17 years according to their asthma‐related hospital use. Clusters were based on 2 variables: asthma‐related ED visits and hospitalizations. Demographics and a number of sociobehavioral and use characteristics were compared across clusters. Results: Children who met the criteria (3,170) were included in the analysis. An examination of a scree plot showing the decline in within‐cluster heterogeneity as the number of clusters increased confirmed that clusters of pediatric asthma patients according to hospital use exist in the data. Five clusters of patients with distinct asthma‐related acute care use patterns were observed. Cluster 1 (62% of patients) showed the lowest rates of acute care use. These patients were least likely to have a mental health–related diagnosis, were less likely to have visited multiple facilities, and had no hospitalizations for asthma. Cluster 2 (19% of patients) had a low number of asthma ED visits and onetime hospitalization. Cluster 3 (11% of patients) had a high number of ED visits and low hospitalization rates, and the highest rates of multiple facility use. Cluster 4 (7% of patients) had moderate ED use for both asthma and other illnesses, and high rates of asthma hospitalizations; nearly one quarter received care at all facilities, and 1 in 10 had a mental health diagnosis. Cluster 5 (1% of patients) had extreme rates of acute care use. Conclusion: Differences observed between groups across multiple sociobehavioral factors suggest these clusters may represent children who differ along multiple dimensions, in addition to patterns of service use, with implications for tailored interventions.

All-Cause Hospital Admissions Among Older Adults After a Natural Disaster

Study objective: We characterize hospital admissions among older adults for any cause in the 30 days after a significant natural disaster in the United States. The main outcome was all‐cause hospital admissions in the 30 days after natural disaster. Separate analyses were conducted to examine all‐cause hospital admissions excluding the 72 hours after the disaster, ICU admissions, all‐cause inhospital mortality, and admissions by state. Methods: A self‐controlled case series analysis using the 2011 Medicare Provider and Analysis Review was conducted to examine exposure to natural disaster by elderly adults located in zip codes affected by tornadoes during the 2011 southeastern superstorm. Spatial data of tornado events were obtained from the National Oceanic and Atmospheric Administration’s Severe Report database, and zip code data were obtained from the US Census Bureau. Results: All‐cause hospital admissions increased by 4% for older adults in the 30 days after the April 27, 2011, tornadoes (incidence rate ratio 1.04; 95% confidence interval 1.01 to 1.07). When the first 3 days after the disaster that may have been attributed to immediate injuries were excluded, hospitalizations for any cause also remained higher than when compared with the other 11 months of the year (incidence rate ratio 1.04; 95% confidence interval 1.01 to 1.07). There was no increase in ICU admissions or inhospital mortality associated with the natural disaster. When data were examined by individual states, Alabama, which had the highest number of persons affected, had a 9% increase in both hospitalizations and ICU admissions. Conclusion: When all time‐invariant characteristics were controlled for, this natural disaster was associated with a significant increase in all‐cause hospitalizations. This analysis quantifies acute care use after disasters through examining all‐cause hospitalizations and represents an important contribution to building models of resilience—the ability to recover from a disaster—and hospital surge capacity.

Ruptured subcapsular liver haematoma following mechanically-assisted cardiopulmonary resuscitation

A 64-year-old man with a history of ascending aortic surgery and pulmonary embolus presented with shortness of breath. He rapidly decompensated, prompting intubation, after which he lost pulses. Manual resuscitation was initiated immediately, with subsequent use of a LUCAS-2 mechanical compression device. The patient was given bolus thrombolytic therapy and regained pulses after 7 min of CPR. Compressions were reinitiated with the LUCAS-2 twice more during resuscitation over the subsequent hour for brief episodes of PEA. After confirmation of massive pulmonary embolism on CT, the patient underwent interventional radiology-guided ultrasonic catheter placement with local thrombolytic therapy and experienced immediate improvement in oxygenation. He later developed abdominal compartment syndrome, despite cessation of thrombolytic and anticoagulation therapy. Bedside exploratory abdominal laparotomy revealed a ruptured subcapsular haematoma of the liver. The patients haemodynamics improved following surgery and he was extubated 11 days postarrest with intact neurological function.

The Association of Inpatient Occupancy with Hospital-Acquired Clostridium Difficile Infection

Few studies have evaluated the relationship between high hospital occupancy and hospital-acquired complications. We evaluated the association between inpatient occupancy and hospital-acquired Clostridium difficile infection (CDI) using a novel measure of hospital occupancy. We analyzed administrative data from California hospitals from 2008–2012 for Medicare recipients aged ≥65 years with a discharge diagnosis of acute myocardial infarction, heart failure, or pneumonia. Using daily census data, we constructed patient-level measures of occupancy on admission day and average occupancy during hospitalization (range: 0-1), which were split into four groups. We used logistic regression with cluster standard errors to estimate the adjusted and unadjusted relationship of occupancy with hospital-acquired CDI. Across 327 hospitals, 558,344 discharges met our inclusion criteria. Higher admission day occupancy was associated with significantly lower adjusted likelihood of CDI. Compared to the 0-0.25 occupancy group, patients admitted on a day of 0.51-0.75 occupancy had 0.86 odds of CDI (95% CI 0.75-0.98). The 0.76-1.00 admission occupancy group had 0.87 odds of CDI (95% CI 0.75-1.01). With regard to average occupancy, intermediate levels of occupancy 0.26-0.50 (odds ratio [OR] = 3.04, 95% CI 2.33-3.96) and 0.51-0.75 (OR = 3.28, 95% CI 2.51-4.28) had over three-fold increased adjusted odds of CDI relative to the low occupancy group; the high occupancy group did not have significantly different odds of CDI compared to the low occupancy group (OR = 0.96, 95% CI 0.70-1.31). These findings should prompt exploration of how hospitals react to occupancy changes and how those care processes translate into hospital-acquired complications in order to inform best practices.

67 Development of a peer assessment tool to evaluate preparedness for large mass casualty incidents in the united states yields critical lessons

Statement of Purpose Geopolitical changes and increases in man-made and natural mass casualty incidents (MCIs) make preparation for such events more critical. The objective of this study is to understand those preparedness activities that are most effective in securing a successful response to MCIs. To achieve this goal, RAND was commissioned by the Department of Health and Human Services/Office of the Assistant Secretary for Preparedness and Response to develop a peer assessment tool that was pilot-tested in three communities across the United States that had recently experienced an incident. Approach An interview protocol was developed based on a literature review of past domestic and international MCIs, after action reports from previous domestic incidents, expert opinion, and previous RAND post-incident evaluation tools. The protocol, designed for use by peer assessors, was pilot-tested in three communities that had recently experienced MCIs and sought to elicit successes, challenges, innovative adaptations, lessons for other communities, and related recommendations. Results Use of this tool identified key preparedness activities in the areas of: scene management, communication, patient transfer optimisation; receiving hospital actions, receiving ED actions, emergency operation centre actions, interfacing with law enforcement and state or federal agencies, patient identification and family reunification, interfacing with the media; incorporation of mental health needs, inter-organisational relationship building; and preparedness investment. Based on peer-assessor and pilot-site feedback, use of this tool was deemed feasible with low burden on sites. Conclusions The results of these pilots, and the use of this tool following future incidents, can be used to create a de-identified database of best practices for disaster preparation, inform preparedness policy, improve response and guide federal preparedness investments. Significance Given the current world geopolitical climate effective MCI preparedness is critical. Based on three pilots, critical lessons have been learned that can guide the MCI preparation of hospitals, healthcare systems, and the larger response community.

Setting Foundations for Developing Disaster Response Metrics

There are few reported efforts to define universal disaster response performance measures. Careful examination of responses to past disasters can inform the development of such measures. As a first step toward this goal, we conducted a literature review to identify key factors in responses to 3 recent events with significant loss of human life and economic impact: the 2003 Bam, Iran, earthquake; the 2004 Indian Ocean tsunami; and the 2010 Haiti earthquake. Using the PubMed (National Library of Medicine, Bethesda, MD) database, we identified 710 articles and retained 124 after applying inclusion and exclusion criteria. Seventy-two articles pertained to the Haiti earthquake, 38 to the Indian Ocean tsunami, and 14 to the Bam earthquake. On the basis of this review, we developed an organizational framework for disaster response performance measurement with 5 key disaster response categories: (1) personnel, (2) supplies and equipment, (3) transportation, (4) timeliness and efficiency, and (5) interagency cooperation. Under each of these, and again informed by the literature, we identified subcategories and specific items that could be developed into standardized performance measures. The validity and comprehensiveness of these measures can be tested by applying them to other recent and future disaster responses, after which standardized performance measures can be developed through a consensus process. (Disaster Med Public Health Preparedness. 2017;11:505-509).

Using Timely Survey-Based Information Networks to Collect Data on Best Practices for Public Health Emergency Preparedness and Response: Illustrative Case From the American College of Emergency Physicians' Ebola Surveys.

OBJECTIVE Using the example of surveys conducted by the American College of Emergency Physicians (ACEP) regarding the management of Ebola cases in the United States, we aimed to demonstrate how survey-based information networks can provide timely data to inform best practices in responding to public health emergencies. METHODS ACEP conducted 3 surveys among its members in October to November 2014 to assess the state of Ebola preparedness in emergency departments. We analyzed the surveys to illustrate the types of information that can be gleaned from such surveys. We analyzed qualitative data through theme extraction and collected quantitative results through cross-tabulations and logistic regression examining associations between outcomes and potential contributing factors. RESULTS In the first survey, most respondents perceived their hospital as being reasonably prepared for Ebola. The second survey revealed significant associations between a hospitals preparedness and its perceived ability to admit Ebola patients. The third survey identified 3 hospital characteristics that were significantly and independently associated with perceived ability to admit Ebola patients: large size, previous Ebola screening experience, and physician- and nurse-led hospital preparedness. CONCLUSION Professional associations can use their member networks to collect timely survey data to inform best practices during and immediately after public health emergencies. (Disaster Med Public Health Preparedness. 2016;10:681-690).