The Need to Incorporate Post-Acute Care Entities Into the National Disaster Medical System.

The National Disaster Medical System (NDMS) is critical to healthcare preparedness and response in the United States but currently has limited capacity for handling large-scale mass-casualty surge events. Crises, such as the COVID-19 pandemic, have shown how quickly the US healthcare system can become overwhelmed, necessitating novel solutions for handling a large-scale influx of patients. This paper proposes the inclusion of post-acute care (PAC) entities, which provide long-term care rehabilitation and short-stay subacute rehabilitation support rather than acute or critical care, into the NDMS as one solution to increase its capacity during mass-casualty surges.

Mapping Interoperability Within the National Disaster Medical System Pilot Program.

Introduction: In the event of a large-scale combat operation, the United States could anticipate large numbers of casualties returning home in need of care for long periods of time. To ensure care for those wounded, military and civilian healthcare organizations will need to communicate, coordinate, and collaborate. The National Disaster Medical System (NDMS) Pilot Program aims to strengthen partnerships and improve military-civilian interoperability across the United States.

Implementation of SARS-CoV-2 Monoclonal Antibody Infusion Sites at Three Medical Centers in the United States: Strengths and Challenges Assessment to Inform COVID-19 Pandemic and Future Public Health Emergency Use.

Monoclonal antibody therapeutics to treat coronavirus disease (COVID-19) have been authorized by the US Food and Drug Administration under Emergency Use Authorization (EUA). Many barriers exist when deploying a novel therapeutic during an ongoing pandemic, and it is critical to assess the needs of incorporating monoclonal antibody infusions into pandemic response activities. We examined the monoclonal antibody infusion site process during the COVID-19 pandemic and conducted a descriptive analysis using data from 3 sites at medical centers in the United States supported by the National Disaster Medical System.

Use of Big Data in Disaster Recovery: An Integrative Literature Review.

Objective: Disasters of all varieties have been steadily increasing in frequency. Simultaneously, "big data" has seen explosive growth as a tool in business and private industries while opportunities for robust implementation in disaster management remain nascent. To more explicitly ascertain the current status of big data as applied to disaster recovery, we conducted an integrative literature review.

Applications of Artificial Intelligence and Machine Learning in Disasters and Public Health Emergencies.

Indexed literature (from 2015 to 2020) on artificial intelligence (AI) technologies and machine learning algorithms (ML) pertaining to disasters and public health emergencies were reviewed. Search strategies were developed and conducted for PubMed and Compendex. Articles that met inclusion criteria were filtered iteratively by title followed by abstract review and full text review.

Use of Big Data and Information and Communications Technology in Disasters: An Integrative Review.

ABSTRACTNovel approaches to improving disaster response have begun to include the use of big data and information and communication technology (ICT). However, there remains a dearth of literature on the use of these technologies in disasters. We have conducted an integrative literature review on the role of ICT and big data in disasters.

State of the Science in Dried Blood Spots.

Background: Advancements in the quality and availability of highly sensitive analytical instrumentation and methodologies have led to increased interest in the use of microsamples. Among microsamples, dried blood spots (DBS) are the most well-known. Although there have been a variety of review papers published on DBS, there has been no attempt at describing the full range of analytes measurable in DBS, or any systematic approach published for characterizing the strengths and weaknesses associated with adoption of DBS analyses.

Examining Public Health Workers' Perceptions Toward Participating in Disaster Recovery After Hurricane Sandy: A Quantitative Assessment.

Objective: We aimed to quantitatively gauge local public health workers' perceptions toward disaster recovery role expectations among jurisdictions in New Jersey and Maryland affected by Hurricane Sandy.

Methods: An online survey was made available in 2014 to all employees in 8 Maryland and New Jersey local health departments whose jurisdictions had been impacted by Hurricane Sandy in October 2012. The survey included perceptions of their actual disaster recovery involvement across 3 phases: days to weeks, weeks to months, and months to years.