Big Data Knowledge in Global Health Education.

The ability to synthesize and analyze massive amounts of data is critical to the success of organizations, including those that involve global health. As countries become highly interconnected, increasing the risk for pandemics and outbreaks, the demand for big data is likely to increase. This requires a global health workforce that is trained in the effective use of big data. To assess implementation of big data training in global health, we conducted a pilot survey of members of the Consortium of Universities of Global Health. More than half the respondents did not have a big data training program at their institution. Additionally, the majority agreed that big data training programs will improve global health deliverables, among other favorable outcomes. Given the observed gap and benefits, global health educators may consider investing in big data training for students seeking a career in global health.

Assessment of Mass Fatality Preparedness and Response Content in Dental Hygiene Education.

When mass fatality incidents (MFIs) occur, they can quickly overwhelm local, state, and government agencies, resources, and personnel. It is important to have a rapid and effective response with skilled, multidisciplinary victim identification teams since specific skill sets are necessary to participate in mass fatality preparedness and response. The aims of this study were to determine the extent of formal education related to mass fatality preparedness and response training in U.S. dental hygiene programs and to assess program directors' perceptions of the need for such training. A 23-item cross-sectional survey was emailed to 319 U.S. dental hygiene programs in 2015. Survey questions addressed if the program offered mass fatality preparedness and response training to its students and how much training was given, as well as collecting respondents' demographics and opinions regarding education and training. An overall response rate of 36% was obtained, with 111 program chairs completing the survey. The results showed that only a small percentage of responding programs incorporated coursework related to mass fatality and preparedness in their curricula. Of the responding programs, 84% had no formal instruction on the role of a dental hygienist in MFIs; however, 53 of 69 program directors agreed or strongly agreed that the role of dental hygienists in MFIs should be covered in dental hygiene curricula. The top three barriers to incorporating such training reported by respondents were time requirements, lack of faculty expertise, and lack of equipment. Future research is needed to establish standardized competencies for mass fatality preparedness and response in dental hygiene education.

Epidemiology of Pediatric Prehospital Basic Life Support Care in the United States.

Children have unique medical needs compared to adults. Emergency medical services personnel need proper equipment and training to care for children. The purpose of this study is to characterize emergency medical services pediatric basic life support to help better understand the needs of children transported by ambulance. Pediatric basic life support patients were identified in this retrospective descriptive study. Descriptive statistics were used to examine incident location, possible injury, cardiac arrest, resuscitation attempted, chief complaint, primary symptom, provider's primary impression, cause of injury, and procedures performed during pediatric basic life support calls using the largest aggregate of emergency medical services data available, the 2013 National Emergency Medical Services Information System (NEMSIS) Public Release Research Data Set. Pediatric calls represented 7.4% of emergency medical services activations. Most pediatric patients were male (49.8%), White (40.0%), and of non-Hispanic origin (56.5%). Most incidents occurred in the home. Injury, cardiac arrest, and resuscitation attempts were highest in the 15 to 19 year old age group. Global complaints (37.1%) predominated by anatomic location and musculoskeletal complaints (26.9%) by organ system. The most common primary symptom was pain (30.3%) followed by mental/psychiatric (13.4%). Provider's top primary impression was traumatic injury (35.7%). The most common cause of injury was motor vehicle accident (32.3%). The most common procedure performed was patient assessment (27.4%). Median EMS system response time was 7 minutes (IQR: 5-12). Median EMS scene time was 12 minutes (IQR: 8-19). Median transport time was 14 minutes (IQR: 8-24). Median EMS total call time was 51 minutes (IQR: 33-77). The epidemiology of pediatric basic life support can help to guide efforts in both emergency medical services operations and training.

A pilot model for predicting the success of prehospital endotracheal intubation.

OBJECTIVES: We sought to evaluate the success of prehospital, non-drug-assisted endotracheal intubation (ETI) performed by Virginia prehospital care providers and to develop a model designed to predict the probability of success of ETI. METHODS: We conducted a retrospective observational study on prehospital, non-drug-assisted ETI (N=4002) performed by Virginia prehospital care providers, from January 1, 2012, to December 31, 2012. Using descriptive statistics, we quantified patient, provider, and system characteristics. Success rates were calculated by provider certification level and number of ETI attempts. Procedure complications were evaluated for the entire cohort. Variables were recoded for modeling purposes. Univariate analyses using χ2 tests were performed to identify candidate parameters to be included in the model. We performed a backward stepwise logistic regression to predict ETI success. RESULTS: An overall success rate of 69.9% was found. Binary logistic regression revealed the following covariates associated with ETI success: community type, provider certification level, gender, age group, myocardial infarction, and ethnicity which were all significant (P<0.05) with a -2 log-likelihood value of 3705.574. This was the most parsimonious model evaluated and demonstrated good fit (Hosmer-Lemeshow test P=.646) but poor discrimination (area under the receiver operating characteristic curve=0.595). CONCLUSION: This study characterized prehospital ETI success using retrospective state data and found a low overall success rate. Binary logistic regression was performed to create a model and equation identifying a set of factors associated with ETI success.