This paper presents a comprehensive set of recommended performance measures for a medium-sized emergency medical services (EMS) organization processing approximately 50,000 calls per year. Drawing on research from the National Highway Traffic Safety Administration, peer-reviewed literature, and case studies from EMS providers, the paper covers operational and clinical performance indicators, system design and structure, human resources, response time metrics, finance and funding, quality management, and community demographics. The paper also applies business principles — including customer and employee satisfaction surveys and balanced scorecard frameworks — to EMS evaluation, arguing that EMS organizations benefit from treating service delivery with the same rigor applied to other service industries.
The paper demonstrates applied literature synthesis: it takes frameworks and findings from business management, healthcare quality research, and government policy documents and systematically adapts them to a specific organizational context. Rather than merely summarizing sources, it evaluates their applicability and recommends selective adoption based on the organization's size and constraints — a hallmark of professional-level analytical writing.
The paper opens with a premise statement positioning EMS as a service industry, then moves through thematic sections aligned with the NHTSA performance measurement framework: operational measures, clinical quality measures, system design, human resources, clinical care outcomes, response time, finance, quality management, community demographics, and customer/employee satisfaction. It closes with a conclusion that integrates the balanced scorecard concept and stakeholder theory. Each section links back to the central argument that multi-dimensional measurement is necessary for genuine EMS improvement.
This report starts from the premise that Emergency Medical Services (EMS) will be treated as any other service industry. As a consequence, EMS reflects a relationship between the service recipient — in this case, patients — and the service provider — in this case, the medium-sized organization being analyzed. This report draws on existing research and business literature, applying principles such as customer and employee satisfaction to present and analyze a comprehensive set of recommended performance measures for a medium-sized EMS organization processing approximately 50,000 calls per year.
The Littleton Fire Rescue service has been providing citizens with emergency medical services for decades. However, the performance of their EMS was not measured and its influence on patient outcomes could not be determined. The Littleton Fire Rescue department subsequently developed an applied research process intended to identify key performance indicators that could be used to measure the department's performance (Zygowicz, 2010).
The operational segment was of particular interest to researchers in this case, as operational performance measures have been identified in order to improve EMS system efficiency and to improve customer service. These measures can be successfully benchmarked by the EMS organization under review.
One of the measures proposed by the Littleton study refers to monitoring individual paramedic performance and providing feedback to crew members. This measure is intended to personalize recommendations for each crew member, thereby increasing their efficiency.
Another important operational measure is to determine the number of tracheal intubations performed by staff. If the reported number is lower than the state average, training programs must be acquired for the organization's personnel (Zygowicz, 2010).
Additional measures that should be benchmarked by the organization relate to its communication center or dispatch operations, light-and-siren response protocols, and primary EMS complaint categories. Collecting and analyzing data on patient satisfaction is probably the area that can provide the most useful information for developing measures that improve satisfaction. It is worth noting, however, that patient satisfaction surveys carry an inherent level of subjectivity. Patients' responses should therefore be measured against more objective indicators in order to build an accurate picture of the service's performance. To facilitate survey implementation, questionnaires can be sent to patients together with their transportation bills.
It is also recommended that the organization post information about its performance measures and associated indicators on its website. Publishing such results ensures the transparency of its activity (Zygowicz, 2010).
Myers, Slovis et al. (2007) conducted a significant body of research regarding clinical performance measures. Their study begins with some of the traditional performance measures, of which response time intervals are among the most important. Response time intervals are easy to quantify, which is helpful in dialogue with external stakeholders such as the public and central administration. Being able to quantify a clinical performance measure objectively reflects how well a center is performing.
Benchmarking response times remains a challenge because, as medical science has evolved, more individuals can perform basic resuscitation measures such as advanced life support (ALS) or cardiopulmonary resuscitation (CPR). CPR benchmarking now receives less attention in the measuring process, and the ALS response-time interval has become the norm in clinical performance measurement, indicating how quickly responders arrive and initiate ALS.
The average response time is already in use in the organization under analysis. The difficulty is that it is the only performance measure currently in use. Nevertheless, it is a useful measure for regulating human resources — particularly in terms of the number of paramedics deployed and how they are allocated to different case types.
Among other traditional performance measurements discussed by Myers et al. are out-of-hospital cardiac arrest survival rates. Their criticism of this approach is that it focuses only on a particular area of EMS action — cardiac arrest — which accounts for only approximately 2% of total EMS responses. Other approaches, such as ST-Segment Elevation Myocardial Infarction (STEMI) Performance Measures or Respiratory Distress Performance Measures, appear to have a similar limitation in scope.
The clinical performance benchmarking model proposed by Myers et al. is designed for large urban or suburban EMS systems. As the organization discussed here is a medium-sized EMS provider, the best approach in terms of clinical performance measures should be to focus on general measures and implement a series of quality performance measurement systems as described below.
As El Sayed (2011) noted, more and more emergency medical services have begun to be evaluated in a manner similar to healthcare services, where the quality of care is a central concern. Measurement of quality in EMS has looked to quality management systems used in the business industry (El Sayed, 2011), since the objective of this process is ultimately to improve the quality of service for the end consumer.
An important category of measures used in this area is process data. Process data examines the interaction between the patient and the prehospital or EMS provider, analyzing the different steps that constitute this interaction. This is a very useful approach because it involves a direct evaluation of service quality. However, the more complex the interaction and the level of services provided, the more difficult this analysis is likely to become.
In the case of this particular organization, its medium size (50,000 calls per year) encourages such an approach, since it is sufficiently manageable to allow proper implementation without excessive resource demands. The best path forward would likely be to implement a separate structure that monitors, records, and corrects service quality toward patients.
Another type of quality performance measurement discussed by El Sayed is outcome data. This approach examines the change in the patient's condition following EMS intervention. It is easy to implement and understand: it involves a transparent analysis of whether the patient's condition improved during or after EMS. It is also comprehensive, evaluating all different aspects of EMS from a wider perspective than the process data approach. Rather than being sequential, outcome research is more holistic, and its results likely better reflect real-world conditions.
There are also disadvantages to this approach. El Sayed points out that theory remains underdeveloped when it comes to standardizing norms related to outcome. For some medical facilities, improvement in a condition may indicate quality care; for others, it may simply reflect a routine standard or may result from factors unrelated to medical care.
This area is, however, gradually improving. For example, the U.S. National Highway Traffic Safety Administration (NHTSA) launched the EMS Outcomes Project, which defined six categories of potential outcomes ranging from survival to limited disability and cost-effectiveness.
In the particular case of this organization, the outcome model is an excellent, low-cost solution, though it requires customized research to determine how best to match the model to the organization's existing structure and characteristics. Some of the potential outcome categories identified by NHTSA can be retained as proposed.
Finally, structural data represents another category of quality measures. This approach evaluates the different physical components of the EMS system based on their capacities. One significant disadvantage of this approach is the limited link between structural components and final patient outcomes. With this in mind, the organization should implement minimal components of this category, evaluating physical components continuously but focusing only on whether they are functioning reasonably in comparison to established benchmarks.
Summarizing this section, from a quality measurement perspective, the outcome model should be favored given its low cost and holistic approach. At the same time, elements of the other two categories should be included to measure particular areas of interest and ensure a complete evaluation of EMS quality.
Before measuring the performance of financial, technical, and human resources, it is important to address the design and structure of EMS systems. These are the foundational factors upon which all other resources' efficiency depends. One of the measures proposed by the NHTSA (2009) refers to determining the type of Emergency Medical Dispatch Protocol Reference System (EMPRDS) used by the EMS dispatch center. The objective of this measure is to encourage EMS dispatch centers to use APCO, Medical Priority Dispatch System, Power Phone, or another recognized system that can facilitate and improve center efficiency relative to using no system at all.
One system design measure that requires minimum effort to implement and can contribute significantly to improving EMS performance concerns how the EMPRDS is connected with the lights-and-siren response mode — specifically, using services or systems that rely on EMPRDS to determine when lights and sirens are appropriate. Increasing the percentage of providers using such systems would likely improve EMS performance.
EMS performance can also be improved by connecting the responder-level dispatch to the EMPRDS in use, in order to determine the level of care capability of dispatched responders. This measure should be revisited on an annual basis.
With personnel efficiency playing such an important role in EMS performance, human resources performance measures have been included by the NHTSA (2009) in its recommendations. The measure proposed refers to identifying the turnover rate for EMS providers. Its objective is to reduce turnover and ensure that experienced personnel are retained in each service area. Turnover rate should be measured annually. The NHTSA proposes this as an interim measure to be applied until standardization of licensure and certification levels is achieved. Turnover can be calculated by comparing the number of identified licenses at each level against the previous year's figures.
Human resources have a significant impact on EMS performance and on patient satisfaction. Personnel activity should be assessed and improved through training programs oriented toward specific clinical care areas as well as communication with staff and patients.
Always verify citation format against your institution’s current style guide requirements.