Editor's note: Access the interactive EMS World Salary Calculator and Work Environment Survey at ems-stats.com.
Many factors influence the compensation rates of EMS providers; pay varies by region, population density of the community, qualifications, education obtained and certifications held.
Satisfaction in one’s pay also seems to vary. Not everyone has the same level of satisfaction in their pay. Is there a relationship between how many calls people run, how much they get paid, the type of community they work in, and their satisfaction with their pay?
In our first EMS World online salary survey, we asked EMS providers a series of questions covering a broad range of variables. We received responses from all 50 states, seven Canadian provinces, and outside North America. Here is what we asked about:
Job location by zip code (or other identifier if not in the U.S.);
Highest level of education;
Pay and pay type (hourly vs. salary);
Number of organization calls/patient contacts each year; and
Overall level of satisfaction with current pay.
The first version of this survey included 2,342 responses: 2,203 (94.06%) from the U.S., 45 (1.93%) from Canada, and 94 (4.01%) from the rest of the world. Generally, the most populous U.S. states returned the most responses, and the least populous had the fewest—New York, Texas, Ohio, Pennsylvania, and California had the most respondents, and Hawaii, Alaska, Rhode Island, Washington, D.C., and Montana the fewest.
Because the number of results from outside the U.S. was relatively small, all analysis on this first study is based on U.S. responses only. As the survey grows and responses increase, we will add regions and nations.
Below are some key takeaways from the data.
Satisfaction—How satisfied are EMS providers with their salary? Respondents were asked to rank their satisfaction with their current pay on a scale from 1 (extremely dissatisfied) to 10 (extremely satisfied).
We found that overall, the more money respondents were paid, the more likely they were to rank their satisfaction level higher. The less they earned, the more likely they would rank their satisfaction level lower.
The exception to this was volunteers and the small number of respondents who reported annual pay in the $10,000 range. Those providers reported a considerably higher level of satisfaction than others on the lower side of the pay scale.
Overall, reported satisfaction across all population densities, job descriptions, states, education levels, and pay levels was approximately 6.3 out of 10.
Satisfaction and population—We used zip codes to identify the population density of the areas where the respondents work. We found no obvious direct relationship between population density and satisfaction.
Levels of satisfaction with pay remain relatively consistent between low-population and high-population zip codes. In future surveys we will try to understand what might be driving this. This question should be answerable as the number of respondents increases and we have more data from both rural and urban areas and high- and low-cost states.
On a state-by-state basis, EMT and paramedic pay varies, although the survey questions did not provide an easy way to explain the differences; furthermore, there does not seem to be an obvious relationship between the lowest-paying and the highest-paying states. One possible explanation is the variability of employers: whether the respondents work for a public entity or private provider. A single additional question in the online survey should help answer this question in the future.
Paramedic and EMT salaries by state—Like those in many professions, EMS professionals tend to get paid more when they have more training and education. When we examined EMTs and paramedics separately, we found that higher levels of educational achievement generally corresponded with higher levels of pay within those groups. Of the 55 respondents who identified themselves as exclusively paid per call, the average rate per call was $15.02, ranging from a low of $1 to a high of $75. Dropping the two respondents who reported $60 per call and the one who reported $70 per call, the average pay per call was $12.13, with the majority making $11–$15 per call.
Finally, it is important to look at these salaries alongside cost of living by state. When adjusting for cost of living, the five states paying the highest salaries (EMT and paramedic combined) were: Idaho, $55,484; Kansas, $52,710; Minnesota, $50,697; District of Columbia, $49,909; and Colorado, $48,048. The lowest-paying states were: Alaska, $26,252; Vermont, $27,154; Hawaii, $28,639; North Dakota, $29,360; and Arkansas, $30,816.
EMS World thanks EMS Survey Team and FireStats LLC for their assistance with this survey. Next steps in Salary Survey for our readers: The EMS World Online Survey will be live on www.emsworld.com in June. The website will include interactive graphics and more detailed statistics on the questions and answers in this survey. You will have access to almost instant feedback and updates as new responses come in.
Sidebar: Survey Snapshots
The survey was conducted for EMS World by the EMS Survey Team using the SNAP Survey platform. Surveys were sent to EMS World’s e-mail subscribers list. In total 47,056 surveys were sent, with 2,140 responses returned. There were 202 respondents who took the survey online via the EMS World website.
All participants were required to enter a valid e-mail address to ensure authentic responses. If an e-mail address was not provided, the respondent could not complete the survey.
Participants were asked to complete the survey only for themselves, not on behalf of anyone else, and were asked to select the position that most accurately described their primary role.
Analysis of state data found that approximately one-third of states had fewer than 30 responses. This limits the ability to draw broad conclusions about those states.
EMS Survey Team thanks the Evaluation Center at Western Michigan University, which assisted with data review, and Roguebotic, which provided supporting graphics, illustrations, and visualizations of the findings.
Sidebar: How to Interpret Survey-Based Research
With the advent of online survey tools and social media, obtaining large amounts of quantitative data is easier than ever. However, not all surveys are well designed for research, and flawed survey data can lead even the most astute readers to wrong conclusions. When interpreting survey-based research, it is important to know the right data were collected and analyzed using appropriate methods. Here are some important things to keep in mind.
The question—Some questions are more suitable for survey research than others. A good survey research question is one where participants are likely to be knowledgeable informants, meaning they can provide accurate responses, and there is no easy alternative way to obtain objective, verifiable information. When possible, using questions from survey instruments that have already been tested and validated is helpful for comparing results to previous work.
Sampling methods—Researchers often can’t reach the entire population they wish to describe, so they survey a sample. Probability sampling is used when it is possible to list the entire population of interest and each person has a known (although not necessarily equal) chance of being selected. Convenience sampling simply means that the survey is administered to people based on their availability.
Bias—One common threat to validity in survey research is information bias. Recall bias occurs when survey participants do not accurately remember the answers to questions. Social desirability bias occurs when people provide untrue answers that are culturally acceptable. In general, people tend to overreport desirable behaviors and underreport undesirable behaviors.
In today’s oversurveyed world, a major limitation of questionnaire-based research is response bias. Response rates to surveys are often low, around 10%–20%. This poses a risk that the 20% of people who answer a survey may be different from the 80% who don’t.
The ability to critically evaluate research articles based on survey data is fundamental for drawing valid conclusions and incorporating findings into practice. Understand and keep in mind how the design and selection of survey questions, sampling approach, information bias, and response rates may influence the results.
Armed with these essential concepts, you will be able to better judge the degree to which conclusions reached by researchers are valid and form your own conclusions.
Remle P. Crowe, MS, NREMT, is an EMS research fellow at the National Registry of EMTs and PhD candidate in the College of Public Health at the Ohio State University.
Rebecca E. Cash, MPH, NRP, is an EMS research fellow at the National Registry of EMTs and pursuing her PhD in epidemiology at the Ohio State University’s College of Public Health.
Ashish R. Panchal, MD, PhD, is the research and fellowship director at the National Registry of EMTs and an associate professor of emergency medicine at the Ohio State University Wexner Medical Center.