The healthcare industry is full of underutilized data, data that could be used to make a lasting positive impact in communities across the nation. ImageTrend’s Collaborate initiative is taking on this challenge to aggregate this data for better insights. ImageTrend Collaborate brings together de-identified data to reach higher levels of awareness, including trends, comparisons, established benchmarks, public health issues and epidemics, evolving needs and recognizing new insights. With aggregate data, the potential for machine learning to advance greater analyses, complex ideas and predictability is possible.
Collaborate provides insight into clinical, operational and public health data that will contribute to the healthcare provided by organizations, specific sectors and the industry at large. ImageTrend’s Clinical and Research team plans to dive into topics like community paramedicine, critical care, opioids, pediatrics, trauma, violence and other urgent topics affecting our communities. The de-identified data set used for this program is in accordance with the HIPAA Safe Harbor Rule by excluding fields they have established as patient identifiable.
Below are a few examples of how Collaborate has contributed to pre-hospital research
American Heart Association “Don’t Die of Doubt™” Campaign
In collaboration with American Heart Association, ImageTrend’s Clinical and Reseach team analyzed pre-hospital data related to heart attacks and strokes during the COVID-19 Pandemic. A 29% decrease was found for all 9-1-1 Transports from April 2019 to April 2020 and there was a 70% increase in the average time it takes a patient to call 9-1-1 from when they first started experiencing stroke-like symptoms.
COVID-19 Data Insights
At the onset of the COVID-19 pandemic, we received an overwhelming request from our clients to help them gain insight on issues related to COVID-19 and pre-hospital care. Usage of Personal Protective Equipment (PPE) across the nation was a high priority as the threat of running low or out of equipment was a real concern. ImageTrend also pulled nationwide data to establish pre-hospital Influenza-Like Illness criteria based from provider impressions, symptoms and vitals that were indicative of influenza-like or COVID-like illnesses.
911 Responses – Updated May 27, 2020
PPE Data is collected from NEMSIS element eOther.03 – Personal Protective Equipment Used which is optional to collect.
ImageTrend Pre-hospital Influenza-Like Illness (ILI) Incidents
2019-2020 Season – 911 Responses – Updated May 19, 2020
* ImageTrend Collaborate™ Influenza-Like-Illness inclusion criteria from provider impressions or symptoms: acute bronchitis, common cold, COVID-19, influenza, pneumonia, SARS, or at least 1 impression/symptom from the categories of fever, respiratory symptoms, or other cold symptoms.
** CDC data is based on Emergency Department Visits captured from National Syndromic Surveillance Program (NSSP). CDC COVID-19-like illness (CLI) defined as fever and cough or shortness of breath or difficulty breathing or the presence of coronavirus diagnosis code. CDC influenza-like illness defined as fever of 100°F or greater and a cough and/or sore throat without a known cause other than influenza
For More Information
If you are interested in your organization participating in data sharing or would like to request research data, please complete the form.
CrewCare was originally created for first responders. We recognize the benefits the free app would have for other professions, so we have extended the technology to related emergency and health fields, including dispatch, hospital care providers, nurses and physicians. Sign up is confidential and only takes a few minutes to complete and you will be on your way to using this free resource.
As new needs arise, ImageTrend continues to make updates to the app. In light of the recent pandemic, CrewCare was recently updated to include questions in the Life Tile specifically related to the impact of COVID-19. This gives users a way to anonymously share their stressors and experience related to COVID-19.
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