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.

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.

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.

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.

This table contains data related to responses by regularly scheduled ambulances. Units that are not ambulances or are deployed on an irregular basis are excluded from this table.

Data contained in this table documents Austin-Travis County EMS (ATCEMS) Communications Center workload and performance.

Data contained in this table comes from several sources:
• 911 Call Count and Grade of Service are obtained from the ECaTS reporting system provided by the Capital Area Council of Governments (CAPCOG). • Call Processing Interval is calculated using data from the department Computer-Aided Dispatch (CAD) data warehouse. • MPDS Compliance is calculated by the Advanced Quality Assurance (AQUA) system used by Communications Center personnel to assess center performance. • Performance targets are determined by ATCEMS management.

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

This table contains performance data related to ATCEMS revenue collection processes. When using this data for research or other purposes, please cite it as: Emergency Medical Services Department. (2017). EMS - Monthly Finance Measures [Data set]. City of Austin, Texas Open Data Portal. https://doi.org/10.26000/001.000008. Since this table is updated on a monthly basis, include the date that the table was accessed in the citation.

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.

A. SUMMARY This dataset includes aggregated metrics of ambulance patient offload time for ambulance transports to San Francisco hospitals.

B. HOW THE DATASET IS CREATED This dataset contains aggregated data by hospital and month for two metrics: 90th percentile of ambulance patient offload time (APOT) and number of patients by discrete APOT category. The dataset also includes systemwide data for both metrics. APOT is defined as the interval between the arrival of an ambulance patient at an emergency department and the time that the patient is transferred to an emergency department gurney, bed, chair, or other acceptable location and the emergency department assumes responsibility for care of the patient.

C. UPDATE PROCESS The data is updated monthly by San Francisco Emergency Medical Services Agency.

D. HOW TO USE THIS DATASET This dataset is based on EMS patient care reports received from a state database. Please note that you must first filter by Hospital_full and Metric_unit before aggregating the Value field.

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

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 22, 2024 at 08:39 AM.Previous week data can be found here.

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.

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.

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.

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.

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Emergency Medical Services Market Size 2024-2028

The emergency medical services market size is forecast to increase by USD 7.37 billion at a CAGR of 5.8% between 2023 and 2028.

In the Emergency Medical Services (EMS) market, the integration of technology plays a pivotal role in enhancing the human ability to execute tasks effectively. Technology facilitates perform analysis and make informed decisions during critical situations. For instance, calculator and math calculations are essential in emergency situations, and enterprise software streamlines business processes.
Furthermore, artificial intelligence (AI) is increasingly being adopted to write code and enable autonomous decision-making. Favorable reimbursement policies and the increasing prevalence of infectious diseases fuel market growth. company competition intensifies as companies strive to offer advanced solutions to meet the evolving needs of the industry. In summary, technology advancements, reimbursement policies, and market competition are the key drivers shaping the market.

What will be the Size of the Market During the Forecast Period?

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The integration of technology in emergency medical services (EMS) has revolutionized the way human abilities are utilized to execute tasks, perform analysis, and make critical decisions. Enterprise software solutions have become essential tools in this industry, enabling EMS professionals to streamline business processes and ensure safety. Artificial Intelligence (AI) technology plays a significant role in enhancing the capabilities of EMS. AI systems can write code and perform complex math calculations, allowing human intelligence to focus on more critical aspects of patient care. These AI applications are being developed and implemented in various contexts to improve accuracy and efficiency.
Furthermore, simulation tools are another important aspect of technology in EMS. Machines can be programmed to mimic real-life scenarios, providing valuable training opportunities for EMS personnel. These simulations help ensure that decisions made during emergencies are based on accurate information and best practices. AI systems are increasingly being used in control rooms to analyze data and make decisions in real-time. Self-driving cars and autonomous vehicles are also being integrated into EMS operations, enabling faster response times and improved patient outcomes. The use of AI in EMS is not meant to replace human intelligence but rather to complement it.
Moreover, AI systems can process vast amounts of data quickly and accurately, providing valuable insights that can inform human decision-making. This partnership between human and AI intelligence is essential in ensuring the best possible patient care. Content management and user interface design are also critical components of technology in EMS. Effective communication and information sharing between EMS personnel and hospital staff are crucial for efficient patient care. User-friendly interfaces and seamless data transfer enable EMS professionals to access essential patient information quickly and make informed decisions on the go. In conclusion, technology plays a vital role in enhancing the capabilities of emergency medical services. From AI systems and simulation tools to content management and user interface design, technology is enabling EMS professionals to streamline business processes, improve decision-making, and ultimately provide better patient care.

How is this market segmented and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Product

  Life support and emergency resuscitation
  Patient monitoring systems
  Wound care consumables
  Patient handling equipment
  Others


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK


  Asia

    China


  Rest of World (ROW)

By Product Insights

The life support and emergency resuscitation segment is estimated to witness significant growth during the forecast period.

The life support and emergency resuscitation segment is a vital part of The market, playing a crucial role in saving lives during critical situations. This segment comprises various products and technologies intended to stabilize patients encountering life-threatening emergencies, including cardiac arrest, respiratory failure, and severe trauma. The expansion of this segment can be attributed to several factors, such as the increasing prevalence of cardiovascular diseases, trauma injuries, and other acute medical conditions. For example, cardiac arrest is a leading cause of mortality, with hundreds of thousands of out-of-hospital cardiac arrests reported yearly in numerous countries.

Cons

The global Emergency Medical Service (EMS) software market, valued at $316.6 million in 2025, is projected to experience robust growth, driven by increasing demand for efficient and streamlined emergency response systems. The market's Compound Annual Growth Rate (CAGR) of 4.2% from 2025 to 2033 indicates a steady expansion, fueled by several key factors. The rising adoption of cloud-based solutions offers scalability and cost-effectiveness for EMS agencies of all sizes, from large enterprises to smaller SMEs. Furthermore, advancements in mobile technology and integration with other healthcare systems are enhancing real-time data sharing and improving response times. This is leading to better patient outcomes and increased operational efficiency, making EMS software a critical investment for healthcare providers. The market segmentation reveals a strong preference for cloud-based solutions due to their accessibility and flexibility, contrasting with the more traditional on-premise deployments. Geographical analysis suggests North America and Europe will continue to dominate the market due to established healthcare infrastructure and higher technological adoption rates, while emerging markets in Asia-Pacific are poised for significant growth. Regulatory pressures for improved patient care and data security are further driving the adoption of sophisticated EMS software solutions. The competitive landscape is characterized by a mix of established players and emerging companies. Larger companies offer comprehensive, integrated solutions catering to the needs of larger organizations, while smaller, specialized firms focus on niche applications or specific geographic regions. The market is likely to witness increased consolidation and strategic partnerships as companies strive to expand their market share and offer a wider range of services. Future growth will depend on the continuous development of innovative features, such as predictive analytics for resource allocation, improved integration with wearable technology, and enhanced cybersecurity measures. The increasing focus on telehealth and remote patient monitoring will also contribute significantly to the expansion of the EMS software market in the coming years. Overall, the EMS software market demonstrates substantial potential for growth, driven by technological advancements, changing healthcare landscapes, and the increasing need for efficient and effective emergency medical response.

EMS Products Market size was valued at USD 526.8 billion in 2023 and is projected to reach USD 748.4 billion by 2031 growing at a CAGR of 6.2% from 2024 to 2031.

Key Market Drivers: Telemedicine and Connectivity: The integration of telemedicine systems to improve communication between emergency responders and healthcare professionals is projected to enable real-time consultation and decision-making, creating opportunities of growth for the market. IoT and Wearable Devices: The use of Internet of Things (IoT) technologies and wearable devices is projected to enable patient monitoring through the use of EMS personnel to collect important health data during transport and on the scene. In addition to this, developing mobile applications for emergency response coordination, patient information access, and communication among EMS teams will further bolster the growth of EMS Products Market. Remote Patient Monitoring: Also, the focus of healthcare providers on remote monitoring systems, such as EMS, allows them to check patients' vital signs while in transit and sharing of data with receiving institutions. Followed by the use of AI algorithms to help EMS professionals gather faster and more accurate clinical judgments based on patient data and symptoms. Predictive Analytics: The use of predictive analytics to forecast demand, optimize resource allocation, and enhance response times is projected to enhance demand in the market. There is a growing emphasis on meeting regulatory standards and certifications to ensure the quality and safety of EMS goods, benefiting the market. Interoperability Standards: The demand for standardized protocols and data formats to enable seamless communication and data exchange between various EMS systems is likely to create conducive environment for the market. Also, the growing prevalence of chronic diseases among the demographic groups is creating a demand for effective EMS goods and services.