Wilderness EMS Research

Wilderness EMS Research

Ian E. Blanchard

Tyler Williamson


This chapter discusses research and evidence-based medicine (EBM) in the context of wilderness emergency medical services (WEMS). It addresses many questions, including these: What is EBM? How does research contribute to EBM? How is research conducted? How does one find and interpret research? How is research applied to practice? How can one become involved with research?

Imagine you are backcountry skiing when a friend is hit by a small avalanche and pushed 50 ft through trees and rocks. She is partially buried, with her lower body under the snow. You quickly dig her out to find that she has sustained a “boot top” open fracture of the tibia/fibula on one leg because her ski failed to release, and a closed femur fracture on the other leg. There are thankfully no other injuries and she remains alert and oriented but is in extreme pain. It is about a 20-minute ski down to the highway, and a 90-minute drive from there to the nearest small town.

How will you stabilize and evacuate this skier? Do you know that your strategy is correct? What evidence are you using to inform your decisions? How confident are you in the evidence, your interpretation of it, and its application in this wilderness setting?


What Is Evidence-Based Medicine?

EBM has been described as the “conscientious, explicit, and judicious use of current best evidence in making decisions.”1 Imbedded within this definition is the idea that we combine the best available evidence with our own experience to make evidence-based decisions. We don’t only act when we have clear, convincing evidence. Rather, we combine “current best evidence” with our training and experience, taking account of the situation at hand to make sound treatment decisions aimed at optimizing patient care. Hence the name EBM—the ultimate practice result is “based” on evidence, not applied from evidence alone.2 See the WEMS: Introduction chapter for further discussion of EBM in wilderness EMS.

What does “current best evidence” mean? Sometimes the current best evidence includes results from multiple high-quality clinical trials. Sometimes, there have been no clinical trials and decisions must be made based on quality improvement data, or based solely on experience. Most times, there is some mix of quality improvement, lower quality studies, and (less often) a few small, medium quality studies that all contribute to the current best evidence. There are areas of medicine that have a great deal of evidence, but many more areas that do not. WEMS is decidedly part of that second group.

Research plays an important role in EBM. Relying solely on our experience may lead us to make erroneous conclusions on the effectiveness of an intervention. This may occur because we may not see enough patients that have a certain condition or injury, it may occur because the effect we think we are observing may be influenced or obscured by other effects, and/or because we don’t have access to accurate outcome information for patients and so never really know for certain what happened to them.

For example, perhaps a WEMS responder has seen two previous patients with an open tibia/fibula fracture. In one case intravenous (IV) antibiotics were administered shortly after injury, but despite this the responder heard from someone at the hospital that the patient developed an infection. In the second case IV antibiotics were administered 10 hours after injury, but the responder heard from a colleague that the patient did not develop an infection. Their experience may suggest that time to IV antibiotic administration is not important.

Research, however, may follow a greater number of patients to their outcome, account (in the analysis or design of the study) for differences in other factors that cause infections, and collect more accurate and precise information on the outcomes of the patients involved. Research may therefore reach a more detailed and thorough conclusion than the experience of a single provider. The knowledge gained from research can then be translated into personal action (eg, a change in treatment provided by a single provider) and/or system action (eg, a change in protocols, standing orders, or education for a system of providers).

Although not incorporating the latest research into our own care, or that of the system in which we operate, may result in providing less-than-optimal patient care, the alternative of not providing an intervention altogether because of a lack of evidence is also not ideal for patients. Some clinicians and systems may be tempted to justify not providing an intervention because of a lack of research, but that approach is problematic because it may take years for one research study to be conducted, and even then, that study may lead to more questions than answers and may not be entirely applicable to the WEMS setting. Therefore, regardless of whether we are individual clinicians or working as part of an organized WEMS system, we need to strike a balance. We may use current best evidence to guide our practice, which may include research studies when available, and other times it may be based solely on our own judgment and experience or that of others when research is not available.

What Are the Challenges in Applying Evidence-Based Medicine Principles to Wilderness EMS?

In theory, applying EBM principles may seem straightforward—we search for “current best evidence,” we interpret it, and then we apply it to our practice or the practice of our WEMS system. In reality, it is a lot harder, and this may be particularly so for those working in WEMS systems.

For example, in searching for evidence we may encounter a lack of research on the patients and scenarios encountered in the WEMS environment. Instead research may need to be “borrowed” from other settings, such as traditional EMS, military medicine, or in-hospital care. Interpreting evidence, especially research, can involve navigating seemingly difficult concepts and terms. Furthermore, applying EBM to our practice can be influenced by many factors. Physicians, for example, who routinely apply EBM principles, might be more comfortable applying evidence to their practice, compared with a wilderness first aider. Responders in an organized EMS system may not be empowered to deviate from existing protocols or policy despite their knowledge of the evidence, but they can advocate for changes to system protocols and procedures.

How Does Research Contribute to Evidence-Based Medicine?

Although there are numerous definitions for research—and no single universally accepted definition—it is in principle an activity designed to extend our current knowledge in a detailed and thorough manner.

We have mentioned that current best evidence should be used in EBM. By “best” we mean that the evidence should effectively address the area of interest and limit alternative explanations for the conclusions. For example, we may be trying to find evidence to answer the below question:

In adults injured in a wilderness setting, does the application of a traction splint, compared to a nontraction splint, relieve pain and decrease complications from a femur fracture?

The “best” evidence in this case would be the outcome of femur fracture patients. Our highest quality and most likely source for finding such evidence is a research study that has followed a suitably large number of patients who suffered a femur fracture in the wilderness setting to their outcome (to determine pain and complications). This study would extend our current knowledge of the treatment of femur fractures in the wilderness setting by providing detailed information on the outcomes of pain and complications arising from two different treatment approaches. If the study was designed and executed correctly, then this information would be systematic and thorough.

The described research study would provide important treatment information that experience alone may not provide. Research is a powerful tool to better understand not just treatment, but also patient preferences, cost, and many other aspects relating to WEMS care.

What Are the Types of Research?

If we think of research broadly, it may be divided into four pillars. These include the following:

1. Biomedical,

2. Clinical,

3. Health Services, and

4. Population Health.3

Let’s again use our situation of a backcountry skier in a remote location with an open tibia/fibula and closed femur fractures. Let’s imagine for a moment that we are assessing this patient and given her injuries, her fast pulse, pale and sweaty skin, and deteriorating level of consciousness, conclude that she is in shock. If we wanted to improve our treatment of patients in this scenario using EBM, we may want to understand from research the principles and best treatment for hemorrhagic hypovolemic shock.

We may start by understanding research from the first pillar (biomedical), which would describe the impact that hemorrhagic hypovolemia has on the molecular, cellular, organ system, and whole body levels. This may include the use of animal models.

Next we would want to understand clinical treatments that may help improve outcome. Research from the clinical pillar would provide information on the diagnosis and treatment of fractures. The goal of this pillar is to explore interventions to treat a fracture that optimize health and quality of life.

Next we would use research from the health services pillar to understand these interventions in the real world, such as WEMS systems. Through changes to policy and practice, this pillar optimizes the effectiveness of an intervention (how well does it work in practice?) and efficiency (is it worth doing?). This may include how patients access WEMS, the WEMS system itself, training, equipment, WEMS funding, etc. The health services pillar is particularly important for WEMS providers and systems because “cutting-edge” clinical treatments, which are generally developed in an ideal setting such as a hospital, may be neither possible nor feasible (because of environmental factors, cost, training, etc.) in a WEMS setting.

Finally, from the population health pillar we may want to understand the importance of wilderness to population health, and the social and educational factors that influence wilderness pursuits and WEMS incidents.

Why Is Health Services Research So Important to Wilderness EMS?

As the previous example illustrates, information from all pillars can inform a WEMS situation, but for WEMS systems, research describing the health services pillar may be the most directly relevant. This pillar primarily describes research that aims to assess effectiveness, which seeks to assess interventions in the actual setting that they are applied, to determine if an intervention works in practice. It also seeks to assess efficiency, which is the effect of an intervention in relation to the resources required to apply it, to determine if it is worth it.4 In other words, this pillar supports changes to practice that promote access to WEMS systems, quality of WEMS system care, and the ensuing costs of providing this care, with the overall goal of improving the health of patients that access a WEMS system.5

What Is Rigor in Research?

You may have heard the phrase “a rigorous research study,” but what does this actually mean? Although there are many definitions of rigor as a word, most contain the notion that something is exact or accurate. In research, there are many definitions of rigor, with the term applied differently depending on what research approach is taken (more on this later). For our purposes we will suggest that rigor is the degree of evidence provided to support the stated conclusions of a study. So more rigorous studies provide more support for the stated conclusions, therefore minimizing alternative explanations for the study conclusions. It is important to realize that rigor can apply not only to the approach taken to study a research question, but also the quality of how this approach was applied in the real world (eg, Were certain patients systematically excluded from the study? Were the researchers inaccurate in their collection of information?). For simplicity, let’s focus on the approach taken to study a research question first, and illustrate with an example.

Let’s say we want to design a study that assesses the impact of a traction splint on the level of pain in patients with a femur fracture to test the theory that patients that receive a traction splint have less pain than those that don’t. The most rigorous way to study this would be to measure pain on a patient that received a traction splint, then go back in time to the exact moment of injury, and provide the exact same treatment, but this time not apply a traction splint. We could then look at the difference in pain scores between when the patient received and did not receive a traction splint. In other words, ideally, the only thing that would change between the situations would be the traction splint; everything else (eg, the patient, their injury, other treatments, time to access the patient, mode of transport) would be the same. Perhaps this could be repeated on many patients, and we could conclude with a great deal of confidence the impact of a traction splint on pain.

The approach taken to study this research question would be considered extremely rigorous because there would be very few alternative explanations as to why the patient’s pain level differed between the two scenarios, after all the only thing that changed was the application of a traction splint. Although extremely rigorous, this study design would also be impossible, unless we invent time travel. So researchers will often try other approaches to get close to the same information. For example, they may randomly assign one patient to receive a traction splint, and another to not receive one. Unlike the earlier “time machine” approach, where one patient in two exactly similar situations received and did not receive a traction splint, there are now two patients and two different situations. Therefore, any differences between the characteristics of these patients and/or the treatment they received may explain differences we observe on level of pain (ie, it is not just the application of a traction splint that may explain differences in pain).

The approach to this study would be considered less rigorous than the “time machine” approach, but obviously more feasible.

There are many other approaches to research, and we will learn in the following sections why some approaches are more rigorous than others. We will also learn how the quality with which an approach is implemented in the real world can also impact rigor.

Why Is Rigor in Research Important?

Based on our previous example, and trying to apply EBM to our treatment of femur fractures, what research approach would give us the best information to inform our care? We would prefer the “time machine” approach because there would be less room for alternative explanations for the conclusions and therefore less chance of reaching a wrong conclusion. Because the “time machine” approach is impossible, we have to settle for the alternative approach of randomly selecting different patients to receive or not to receive a traction splint. This example, however, illustrates that as users of research we want the most rigorous research approach possible, because it reduces the chance of making incorrect conclusions. Obviously, we don’t need to say that making incorrect conclusions from research and then applying this to practice can have negative consequences for our patients and for our WEMS systems, in terms of both patient care and cost to the system.

If rigor is so important, and the avoidance of incorrect conclusions so critical, why aren’t all research studies as rigorous as possible? Rigorous studies are often expensive studies. In other words, the more rigorous a study, often the more resources it requires. This raises issues of practicality and feasibility—the impossibility of time travel is not the only impediment to rigorous research. As we will learn later in the chapter, the design of a research study has important implications for the resources it requires, and there is a balance between rigor and feasibility.

What Are the Steps in Conducting a Research Study?

Designing a research study is a process that has distinct steps (Figure 8.1). In general, research will start with an idea that leads to the development of a research question. A set of procedures will then be used to answer the research question (the research methods). Data are then collected and analyzed (the results), and conclusions are drawn. Action is then taken on the results and conclusions. In the case of health services research, it is hoped that the results and conclusions of the study will positively impact access, quality, or cost of care.

From Research Question to Methods

Now that we have specified our research question, we have to plan out how we may approach the research question in order to answer it. Research methods are the procedures that researchers employ to answer a research question. The research question will dictate what methods should be used; in other words, certain types of research methods are best used to answer certain types of research questions.

The three broad approaches to research are quantitative, qualitative, and mixed methods. Each broad approach uses specific methods, or in the case of mixed methods a complementary combination of quantitative and qualitative.

Quantitative methods in general focus on describing phenomena or differences numerically. Using our earlier example, we may compare pain scores between those that received a traction splint and those that did not. Quantitative methods are the most commonly used approach in medical sciences, and although useful for describing “what,” it does not often explain “why.”

That is where a qualitative approach may be best. Qualitative methods generally focus on exploring phenomena in-depth. Using our earlier example, we may want to assess not just a patient’s numerical pain score, but how a traction splint made them feel. The difficulty of adequately measuring suffering via a single numerical value, as well as the characteristics of catastrophizing and other pain modifiers, has been discussed elsewhere, and has great relevance to the field of WEMS.6 We may also want to explore barriers to the use of a traction splint in the WEMS setting from a provider’s perspective. Both of these research questions might be better answered using qualitative methods.

Finally, a mixed-methods approach may use both quantitative and qualitative methods to more comprehensively answer a research question. Using our example, to fully understand the implications of using a traction splint in the WEMS environment, the best study may first assess whether there was a quantitative difference in pain scores between those that received a traction splint and those that did not, then explore why this difference may or may not have occurred from the patients’ and providers’ perspectives. We will go into detail on all three of these approaches later in the chapter.

From Conclusions to Action

Once a study is complete, and often published, the results should be translated into action. This is sometimes called knowledge translation (KT). Action could mean that it changes personal practice, or in the case of those that work for a WEMS system that has standing protocols or procedures, perhaps results in a change to these policies. It is very important that users of research take into account how well the researchers answered their research question (in other words the rigor) before translating it into practice. As we have previously mentioned, rigor incorporates the ideas of using the best research methods (in balance with feasibility) to answer the research question, and applying these methods correctly. Another important aspect of applying research into practice is the idea that the setting of the study is sufficiently similar to your own setting to apply the research findings (we will cover this in more detail later in the chapter).

Finally, in some instances there may be conflicting conclusions from multiple studies. An important component of KT is getting the evidence straight, which means summarizing all known studies on a topic with due consideration to the rigor of these studies, and in combination with your own experience, translate the findings into practice.7

What Are the Basic Principles of Quantitative Research?

As mentioned previously, quantitative methods focus on describing with numbers. These descriptions are based on observation and measurement, and broadly employ two approaches, experimental and nonexperimental.

An experimental approach means the intervention that is the focus of the study is under the “control” of the researcher. Using our femur and traction splint example, an experimental study design may involve the researcher creating a process to randomly allocate who receives a traction splint and who receives a traditional splint in order to compare the two groups. In other words, the type of splint that a patient receives is under the “control” of the researcher.

By contrast, a nonexperimental approach would mean that the intervention is not under the “control” of the researcher. An example would be if certain WEMS system patients received a traction splint, and others did not (perhaps because the splint could not be transported to the scene or a variety of other reasons). In this case the intervention would not be under control of the researcher, but the researcher would still be able to observe and measure the outcome of patients who did and did not receive traction.

Randomized Controlled Trials

A randomized controlled trial (RCT) is considered by many quantitative researchers to be the gold standard design for studies of therapies or interventions. If we recall the section on rigor, randomly allocating an intervention to two or more groups of individuals is the closest thing we can get to the “time machine” approach.

In the “time machine” approach, we could put the traction splint on a patient, assess their pain, then travel back in time and put on a traditional splint. Remember, the reason this is so powerful is because everything about the patient is the same, and the only thing that differs is the splint. Therefore, any differences we see in outcome must be attributable to the splint. This is a concept called causality; the traction splint is causing a change in pain level. (Causality is important to differentiate from “correlation”—we will cover this later in the chapter.)

An RCT is an extension of this idea, except that two (or more) groups are created, one that gets the intervention and the other that does not. The key feature is that allocation of who gets what intervention is done randomly—in other words by chance. The reason why we want to do this randomly is that in theory the only systematic difference between the two groups should be the intervention (similar to the “time machine” example). All other known (or unknown) factors that may influence the outcome should be nearly the same. So if we apply this to our example of a traction splint, we could create a research study where one group of patients randomly receives a traction splint and the other group does not. These groups should theoretically only differ by the type of splint they received. This type of study design is an example of an experimental study design, because the researcher is controlling who gets the intervention and who does not.

So why would we not allow responders to decide who gets a traction splint and who does not? Why is it better to randomly decide? The reason is that we all have biases. It may be that responders believe that traction reduces pain, and so they may place a traction splint on those patients who appear to be genuinely in a lot of pain over those that appear to have less pain. This may result in the postsplinting pain scores between the two groups being similar, not because the traction splint is not effective, but because patients in the traction splint group had a higher pain score to start off with. You can see that bias is an important factor, but can often be addressed in the design or analysis phases of a research study (more on this later).

We now know why we need to randomize patients, but is randomization enough to prevent bias? Not entirely, we also ideally need to “blind” patients, providers, and outcome assessors
on what intervention they are receiving. This is to prevent changes in data collection, assessment, treatment, or perception of treatment based on knowledge of the intervention. In some RCTs this is possible, like a drug trial where two drugs can be made to look identical. For trials involving a traction splint, this is obviously impossible. In trials where it is not possible to blind the intervention (called unblinded or open trials), it is important to record other factors that may influence the outcome to make sure these other factors are not influencing the perceived or real effect of the intervention. For example, with our traction splint study, we may want to record presplinting pain scores to ensure that the group that received traction splints had the same initial score as those that did not.

One may come across numerous terminologies to describe who was blinded in a study. Some may suggest that a “single blind” study is when the patients involved in the study do not know what intervention they are being given, but the researchers do. A study may be “double-blind” when both the patients and the researchers who are following the patients do not know what intervention has been provided, although there is no universal agreement on these terms. It is important to note that there is often inconsistency of the meaning of “single blind” and “double blind,” and caution in your interpretation is needed.8,9 Although these terms are still used, a more modern approach describes who was blinded instead of using this terminology, making it easier for the reader to interpret.8

Observational Studies

Thus far, we have learned about how randomly assigning groups of patients to receive an intervention (an RCT) is the most rigorous approach we can use, without using a “time machine.” It is rigorous because we can infer causality between an intervention and an outcome (eg, traction and pain). It is important to realize though that there are many situations where using an RCT approach is either not feasible or is unethical.

An RCT is expensive and takes a tremendous amount of time and resources to implement. Imagine if we were to implement a study that randomly assigned WEMS patients to receive traction or no traction. First, we would likely need many different systems to participate in the study so that we could enroll enough patients to achieve an appropriate sample size (more on this later). Second, we would have to train enough WEMS providers on the study methods so that they could identify patients that meet inclusion criteria for the study, consent the patient to be part of the study, and then apply the intervention. Third, we would have to create a random allocation process, so that patients could be randomly assigned to a group. This would involve working with operations managers of the WEMS systems to ensure that crews had the right equipment on hand on the scene (ie, both types of splints), and that they were not aware of what intervention they were providing until after they consented the patient to participate (to reduce bias). In addition to this, we would need to have an extensive research team that may include epidemiologists, biostatisticians, clinicians, WEMS operations managers and responders, and perhaps other specialized academics, such as health economists, geographical information system (GIS) specialists, etc.

In addition to feasibility, there is also an ethical responsibility to not conduct an RCT if the alternative intervention is not thought to be clinically equivalent. For example, would it be ethical to conduct an RCT where one group of patients gets direct pressure for a severely bleeding wound, and another group gets no treatment to directly control bleeding? Definitely not, as direct pressure is the gold standard for controlling bleeding, and doing nothing would be unethical! This is a clear example of an unethical RCT, but sometimes it is not that clear. What about traction on a femur fracture? Would it be ethical to carry out an RCT where some patients received traction and others did not? That may depend on the balance of existing evidence around the benefit and harm of the intervention. Some RCTs are required to have a data monitoring committee, that ensures participants are not being harmed, or to establish futility (ie, when the trial reaches a point that it cannot hope to achieve its objectives no matter if all future patients had a certain outcome).

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Oct 16, 2018 | Posted by in EMERGENCY MEDICINE | Comments Off on Wilderness EMS Research

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