The National Emergency Medical Services Information System (NEMSIS) is the national system used to collect, store, and share data from EMS services in US states and territories. The NEMSIS uniform dataset and database help local, state and national EMS stakeholders more accurately assess EMS needs and performance, as well as support better strategic planning for the EMS systems of tomorrow. Data from NEMSIS are also used to help benchmark performance, determine the effectiveness of clinical interventions, and facilitate cost-benefit analyses. NEMSIS is a program of NHTSA’s Office of EMS and is hosted by the University of Utah.

These data are “event-based” and not “patient-based”. That is, a single patient may be represented in more than one record for a variety of reasons. A patient may request EMS assistance frequently, and therefore, be represented in the dataset more than once. In addition, several agencies may respond to the same event (i.e., one patient) and each submit a patient care record to the National EMS Database. Thus, the dataset is referred to as a registry of “EMS activations.”

The dataset does not contain information that identifies patients, EMS agencies, receiving hospitals, or reporting states. EMS events submitted by states to NEMSIS do not necessarily represent all EMS events occurring within a state. In addition, states may vary in criteria used to determine the types of EMS events submitted to the NEMSIS dataset.

NEMSIS version 3 data are available from 2017 to 2023. Version 2 data are available from 2009 to 2016 but require mapping and translation to version 3 data elements. Users are advised to open a support ticket to discuss their project if they require data from prior to 2017.

The EMS Incident Dispatch Data file contains data that is generated by the EMS Computer Aided Dispatch System. The data spans from the time the incident is created in the system to the time the incident is closed in the system. It covers information about the incident as it relates to the assignment of resources and the Fire Department’s response to the emergency. To protect personal identifying information in accordance with the Health Insurance Portability and Accountability Act (HIPAA), specific locations of incidents are not included and have been aggregated to a higher level of detail.

MPORTANT NOTE: This provisional data is being provided as VDH OEMS continues to improve its data systems. The data on this page will continue to change throughout the data system improvement process and will stabilize over time. Thank you for your patience.

This dataset contains Emergency Medical Services (EMS) information for reported emergency response incidents that involve a substance or have suspected substance involvement. Data in this dataset has been provided by ESO on behalf of the Office of EMS.

Please be advised that the accuracy of the data within the EMS patient care reporting system is limited by system performance and the accuracy of data submissions received from EMS agencies. While each record in this dataset is for a single patient involved in an incident reported by an EMS agency, unique patients may be counted more than once in the dataset (e.g., if a patient was treated by two EMS agencies, that patient may be counted in the dataset twice). This data should not be interpreted as the number of unique substance use incidents reported by Virginia EMS agencies.

For instances where medication was administered to the patient, the response to the medication is provided, if reported by the EMS agency (e.g., if a patient received "naloxone" and the response of the patient for this administration of naloxone was reported as "Improved", then the record will show "naloxone with Improved response"). In instances where multiple medications were administered to the patient, the administrations and their associated responses are provided as a pipe-delimited list in the order that the patient received the medications.

This dataset has been classified as a Tier 0 asset by the Commonwealth Data Trust. Tier 0 classifies a data resource as information that is neither sensitive nor proprietary, and intended for public access.

The dataset represents Emergency Medical Services (EMS) locations in the United States and its territories. EMS Stations are part of the Fire Stations / EMS Stations HSIP Freedom sub-layer, which in turn is part of the Emergency Services and Continuity of Government Sector, which is itself a part of the Critical Infrastructure Category. The EMS stations dataset consists of any location where emergency medical service (EMS) personnel are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Ambulance services are included even if they only provide transportation services, but not if they are located at, and operated by, a hospital. If an independent ambulance service or EMS provider happens to be collocated with a hospital, it will be included in this dataset. The dataset includes both private and governmental entities. A concerted effort was made to include all emergency medical service locations in the United States and its territories. This dataset is comprised completely of license free data. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 12/29/2004 and the newest record dates from 01/11/2010.This dataset represents the EMS stations of any location where emergency medical service (EMS) personnel are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Homeland Security Use Cases: Use cases describe how the data may be used and help to define and clarify requirements. 1. An assessment of whether or not the total emergency medical services capability in a given area is adequate. 2. A list of resources to draw upon by surrounding areas when local resources have temporarily been overwhelmed by a disaster - route analysis can determine those entities that are able to respond the quickest. 3. A resource for Emergency Management planning purposes. 4. A resource for catastrophe response to aid in the retrieval of equipment by outside responders in order to deal with the disaster. 5. A resource for situational awareness planning and response for Federal Government events.

EMS Locations in Kansas The EMS stations dataset consists of any location where emergency medical services (EMS) personnel are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Ambulance services are included even if they only provide transportation services, but not if they are located at, and operated by, a hospital. If an independent ambulance service or EMS provider happens to be collocated with a hospital, it will be included in this dataset. The dataset includes both private and governmental entities. This dataset is comprised completely of license free data. The Fire Station dataset and the EMS dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 10/16/2006 and the newest record dates from 08/11/2008

This table shows ATCEMS fiscal year performance data that supports the ATCEMS annual report.

EMS Locations in Connecticut:The EMS stations dataset consists of any location where emergency medical services (EMS) personnel are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Ambulance services are included even if they only provide transportation services, but not if they are located at, and operated by, a hospital. If an independent ambulance service or EMS provider happens to be collocated with a hospital, it will be included in this dataset. The dataset includes both private and governmental entities.

This dataset is comprised completely of license free data.

The Fire Station dataset and the EMS dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes.

Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries.

Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results.

All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics.

The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 02/11/2005 and the newest record dates from 07/11/2008Use Cases: 1. An assessment of whether or not the total emergency medical services capability in a given area is adequate.

1. A list of resources to draw upon by surrounding areas when local resources have temporarily been overwhelmed by a disaster - route analysis can determine those entities that are able to respond the quickest.

2. A resource for Emergency Management planning purposes.

3. A resource for catastrophe response to aid in the retrieval of equipment by outside responders in order to deal with the disaster.

4. A resource for situational awareness planning and response for Federal Government events.Emergency Operation Centers in Connecticut:No metadata available.

Emergency Medical Service (EMS) Software Market Outlook

The global Emergency Medical Service (EMS) software market size is projected to grow from USD 1.25 billion in 2023 to USD 2.61 billion by 2032, exhibiting a Compound Annual Growth Rate (CAGR) of 8.5% during the forecast period. This robust market growth is primarily driven by the increasing demand for efficient and effective emergency medical services, bolstered by advancements in software technology and an aging global population.

One of the primary growth factors in the EMS software market is the rising need for enhanced operational efficiency in emergency medical services. The introduction of advanced software solutions has revolutionized the way EMS providers manage emergency situations. These solutions offer significant improvements in areas such as patient management, fleet management, and reporting. By automating and streamlining these critical processes, EMS software reduces response times and enhances the overall quality of emergency care, thereby driving market growth.

Additionally, the healthcare sector's increasing focus on data-driven decision-making is propelling the demand for EMS software. These software solutions provide comprehensive data analytics capabilities that enable EMS providers to make informed decisions quickly. With features like real-time data tracking, analytics, and reporting, EMS software helps in optimizing resource allocation, improving patient outcomes, and reducing operational costs. This data-centric approach is becoming increasingly vital as healthcare systems worldwide strive to enhance their efficiency and effectiveness.

Moreover, the adoption of cloud-based deployment models is further accelerating the growth of the EMS software market. Cloud-based EMS software offers numerous advantages, including scalability, flexibility, and cost-effectiveness. It allows EMS providers to access critical information and updates in real-time, regardless of their location. The ability to integrate with other healthcare systems and the ease of software updates and maintenance are additional factors driving the adoption of cloud-based solutions in the EMS sector.

The integration of a robust Medical Emergency Response System is crucial in enhancing the capabilities of EMS software. Such systems are designed to ensure rapid and coordinated responses to medical emergencies by leveraging advanced communication and data management technologies. By incorporating real-time alerts and automated workflows, these systems enable EMS providers to efficiently allocate resources and personnel, significantly reducing response times. The synergy between EMS software and a well-structured Medical Emergency Response System not only improves patient outcomes but also optimizes operational efficiency, making it a vital component of modern emergency medical services.

From a regional perspective, North America is expected to hold a significant share of the EMS software market during the forecast period. This can be attributed to the region's well-established healthcare infrastructure, high adoption rate of advanced technologies, and increasing investments in emergency medical services. Additionally, the presence of major EMS software providers in North America further supports market growth in this region. However, regions like Asia Pacific are also projected to witness substantial growth, driven by increasing healthcare investments, population growth, and the rising prevalence of chronic diseases.

Component Analysis

In the EMS software market, the component segment is divided into software and services. The software segment includes various applications such as patient management, fleet management, billing, and reporting, while the services segment encompasses implementation, training, support, and maintenance services. The software segment is expected to dominate the market, primarily due to the wide range of functionalities it offers. These software solutions are designed to enhance the efficiency and effectiveness of EMS operations by automating critical tasks, thereby reducing response times and improving patient outcomes.

The services segment, on the other hand, plays a crucial role in the successful deployment and operation of EMS software solutions. Implementation services ensure that the software is correctly installed and configured to meet the specific needs of EMS providers. Training services equip EMS perso

The National Emergency Medical Services Information System (NEMSIS) is the national database that is used to store EMS data from the U.S. States and Territories. NEMSIS is a universal standard for how patient care information resulting from an emergency 911 call for assistance is collected. NEMSIS is a collaborative system to improve patient care through the standardization, aggregation, and utilization of point of care EMS data at a local, state and national level. NEMSIS is a product of NHTSA’s Office of EMS and in collaboration with the University of Utah is the host of the Technical Assistance Center.

This dataset contains schedule of fees for Emergency Medical Services Transport Reimbursement Program. Update Frequency : As Needed.

USGS Structures from The National Map consists of data to include the name, function, location, and other core information and characteristics of selected manmade facilities. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations. Structures currently being collected are: School, Technical/Trade School, College/University, Fire Station/EMS Station, Law Enforcement/Police Station, Prison/Correctional Facility, State Capitol, Hospital/Medical Center, Ambulance Service, Cemetery, Post Office, Campground, Trailhead, and Visitor/Information Center. Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps. The National Map download client allows free downloads of public domain structures data in either Esri File Geodatabase or Shapefile formats. For additional information on the structures data model, go to https://www.usgs.gov/core-science-systems/ngp/tnm-corps/structures. See https://apps.nationalmap.gov/help/ for assistance with The National Map viewer, download client, services, or metadata. Data Refreshed January, 2025

This data lists the total number of Madison Fire Department EMS (Emergency Medical Services) runs by day, from January 1, 2018, through August 31, 2020. These numbers indicate the patient runs for which a patient is actually treated.

The incident locations represented are approximated and not the actual location of the incident. Latitudinal and longitudinal coordinates have been truncate to 3 decimal points. The estimated location lies within approximately a 1/4 mile radius. This approximated location data is also shown on the dashboard.This feature layer supports the Opioid Abuse Probable EMS Call Dashboard. The following documents what data are collected and why they are being collected. Opioid Abuse ProbableA call may be coded as “opioid abuse probable” for many reasons, such asAre there are any medical symptoms indicative of opioid abuse?Are there physical indicators on scene (i.e. drug paraphernalia, pill bottles, etc.)?Are there witnesses or patient statements made that point to opioid abuse?Is there any other evidence that opioid abuse is probable with the patient?“Opioid abuse probable” is determined by Tempe Fire Medical Rescue Department’s Emergency medical technicians and paramedics on scene at the time of the incident. Narcan/Naloxone Given“Narcan/Naloxone Given” refers to whether the medication Narcan/Naloxone was given to patients who exhibited signs or symptoms of a potential opioid overdose or to patients who fall within treatment protocols that require Narcan/Naloxone to be given. Narcan/Naloxone are the same medication with Narcan being the trade name and Naloxone being the generic name for the medication. Narcan is the reversal medication used by medical providers for opioid overdoses.Groups“Groups” are used to determine if there are specific populations that have an increase in opioid abuse. The student population at ASU was being examined for other purposes to determine ASU's overall call volume impact in Tempe. Data collection with the university is consistent with Fire Departments who provide service to the other PAC 12 universities. Since this data set was already being evaluated, it was included in the opioid data collection as well.The Veteran and Homeless Groups were established as demographic tabs to identify trends and determine needs in conjunction with the City of Tempe’s Veterans and Homeless programs. Since these data sets were being evaluated already, they were included in the opioid data collection as well.The “unknown” group includes incidents where a patient is unable to answer or refuses to answer the demographic questions. GenderPatient gender is documented as male or female when crews are able to obtain this information from the patient. There are some circumstances where this information is not readily determined and the patient is unable to communicate with our crews. In these circumstances, crews may document unknown/unable to determine. Information about the data can be found at https://bit.ly/2xXbD20

North Dakota EMS Regions

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This dataset contains Emergency Medical Services (EMS) information for reported emergency response incidents in Virginia that involve heat-related illness (HRI), as defined using cause of injury ICD-10-CM codes and patient complaint text fields. The case definition is adapted for EMS from the Council for State and Territorial Epidemiologists (CSTE) HRI syndromic surveillance case definition: https://cdn.ymaws.com/www.cste.org/resource/resmgr/pdfs/pdfs2/CSTE_Heat_Syndrome_Case_Defi.pdf. These data only represent HRI patients who interacted with the EMS system and do not represent HRI patients who reported directly to an emergency room or did not seek medical care. Therefore, these data should not be interpreted as the total number of HRI incidents in a community.

Data in this dataset have been provided by ESO on behalf of the Office of EMS. Please be advised that the accuracy of the data within the EMS patient care reporting system is limited by system performance and the accuracy of data submissions received from EMS agencies.

Counts of less than 5 have been suppressed, denoted by an asterisk, to prevent individual identification and protect patient confidentiality. This dataset has been classified as a Tier 0 asset by the Commonwealth Data Trust. Tier 0 classifies a data resource as information that is neither sensitive nor proprietary, and is intended for public access.

Background: Immunizations for emergency medical services (EMS) professionals during pandemics are an important tool to increase the safety of the workforce as well as their patients. The purpose of this study was to better understand EMS professionals' decisions to receive or decline a COVID-19 vaccine.Methods: We conducted a cross-sectional analysis of nationally certified EMS professionals (18-85 years) in April 2021. Participants received an electronic survey asking whether they received a vaccine, why or why not, and their associated beliefs using three validated scales: perceived risk of COVID-19, medical mistrust, and confidence in the COVID-19 vaccine. Data were merged with National Registry dataset demographics. Analyses included descriptive analysis and multivariable logistic regression (OR, 95% CI). Multivariate imputation by chained equations was used for missingness.Results: A total of 2,584 respondents satisfied inclusion criteria (response rate = 14%). Overall, 70% of EMS professionals were vaccinated. Common reasons for vaccination among vaccinated respondents were to protect oneself (76%) and others (73%). Common reasons for non-vaccination among non-vaccinated respondents included concerns about vaccine safety (53%) and beliefs that vaccination was not necessary (39%). Most who had not received the vaccine did not plan to get it in the future (84%). Hesitation was most frequently related to wanting to see how the vaccine was working for others (55%). Odds of COVID-19 vaccination were associated with demographics including age (referent <28 years; 39-50 years: 1.56, 1.17-2.08; >51 years: 2.22, 1.64-3.01), male sex (1.26, 1.01-1.58), residing in an urban/suburban area (referent rural; 1.36, 1.08-1.70), advanced education (referent GED/high school and below; bachelor's and above: 1.72, 1.19-2.47), and working at a hospital (referent fire-based agency; 1.53, 1.04-2.24). Additionally, vaccination odds were significantly higher with greater perceived risk of COVID-19 (2.05, 1.68-2.50), and higher vaccine confidence (2.84, 2.40-3.36). Odds of vaccination were significantly lower with higher medical mistrust (0.54, 0.46-0.63).Conclusion: Despite vaccine availability, not all EMS professionals had been vaccinated. The decision to receive a COVID-19 vaccine was associated with demographics, beliefs regarding COVID-19 and the vaccine, and medical mistrust. Efforts to increase COVID-19 vaccination rates should emphasize the safety and efficacy of vaccines.

The Emergency Medical Service (EMS) software market is experiencing robust growth, projected to reach $310.7 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 4.0% from 2025 to 2033. This expansion is driven by several key factors. Increasing demand for efficient and effective emergency response systems necessitates sophisticated software solutions for dispatch, resource management, and patient data tracking. The rising adoption of cloud-based solutions offers scalability and accessibility, further fueling market growth. Furthermore, government initiatives promoting digital healthcare transformation and improved interoperability between different healthcare systems contribute significantly to market expansion. The market segmentation reveals a considerable share held by large enterprises, driven by their need for comprehensive and integrated EMS solutions. However, SMEs are also increasingly adopting these systems, seeking improved operational efficiency and cost reduction. Competition is dynamic, with established players like Adashi Systems and newer entrants constantly innovating to meet evolving demands. Geographic distribution indicates strong market presence in North America, followed by Europe and Asia Pacific, with emerging economies presenting substantial growth opportunities in the coming years. The shift towards mobile-first applications and the integration of telemedicine capabilities are prominent trends shaping the future of the EMS software landscape. Challenges, however, include data security concerns and the need for seamless integration with legacy systems. The continued expansion of the EMS software market hinges on technological advancements and regulatory changes. Future growth will likely be driven by the increasing adoption of Artificial Intelligence (AI) and machine learning algorithms for predictive analytics and optimized resource allocation. Integration with wearable technology and remote patient monitoring systems will enhance real-time data collection and improve patient outcomes. Moreover, the growing emphasis on data privacy and security necessitates robust cybersecurity measures, driving investment in secure cloud solutions and data encryption technologies. The market's success will depend on companies' ability to offer flexible, scalable, and secure solutions that address the specific needs of various EMS providers, from large metropolitan areas to rural communities. Ultimately, the overarching aim is to improve emergency response times, enhance patient care, and optimize resource utilization.

APOT-1 is a measure (in minutes) under which 90% of arriving ambulance patients have their care transferred to hospital staff. The California EMS Authority target for the transfer of care from EMS staff to hospital staff is 20 minutes. This report represents the Ambulance Patient Offload Times (APOT) for the previous calendar week per hospital. Report will update Monday / Wednesdays and may reflect lower than actual numbers due to delay in record submission. -- This data was last updated on Aug 15, 2024 at 01:14 PM.Current week data can be found here.

EMS Locations in North Carolina The EMS stations dataset consists of any location where emergency medical services (EMS) personnel are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Ambulance services are included even if they only provide transportation services, but not if they are located at, and operated by, a hospital. If an independent ambulance service or EMS provider happens to be collocated with a hospital, it will be included in this dataset. The dataset includes both private and governmental entities. This dataset is comprised completely of license free data. The Fire Station dataset and the EMS dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 01/05/2005 and the newest record dates from 08/15/2008

The global Emergency Medical Services (EMS) software market is experiencing robust growth, driven by increasing demand for efficient and streamlined emergency response systems. The market's expansion is fueled by several key factors, including the rising adoption of electronic health records (EHRs) within EMS organizations, a growing emphasis on improving patient care through data-driven insights, and the need for enhanced interoperability between different healthcare systems. Furthermore, advancements in mobile technology and cloud-based solutions are enabling EMS providers to access real-time information, improve dispatch efficiency, and optimize resource allocation. The market is segmented by software type (e.g., dispatching, billing, electronic patient care reporting), deployment mode (cloud-based and on-premise), and end-user (hospitals, ambulance services, and private providers). Based on available information and industry trends, we estimate the 2025 market size to be approximately $2.5 billion, with a Compound Annual Growth Rate (CAGR) of 12% projected through 2033, resulting in a market value exceeding $7 billion by the end of the forecast period. This growth will be driven by continued technological advancements, increasing regulatory pressures for data management, and the rising prevalence of chronic diseases requiring frequent emergency care. Competition in the EMS software market is intense, with established players like ESO, Tyler Technologies, and MEDHOST alongside emerging innovative companies such as Halemind, Tobi Cloud, and Resgrid. These companies are constantly striving to enhance their offerings with features such as automated reporting, predictive analytics, and integration with other healthcare IT systems. The market also faces challenges such as high implementation costs, the need for robust data security measures, and the complexity of integrating new software into existing workflows. However, the long-term outlook remains positive, driven by the increasing focus on improving the efficiency and effectiveness of EMS services worldwide. The market is likely to see further consolidation as larger companies acquire smaller players to expand their market share and product portfolios.