Physicians have always felt that their decisions were based on evidence; thus, the current term “evidence-based medicine” is somewhat of a misnomer. However, for many clinicians, the “evidence” is often a vague combination of recollected strategies effective in previous patients, advice given by mentors and colleagues, and a general impression of “what is being done” based on random journal articles, abstracts, symposia, and advertisements. This kind of practice results in wide variations in strategies for diagnosing and managing similar conditions, even when strong evidence exists for favoring one particular strategy over another. Variations exist among different countries, different regions, different hospitals, and even within individual group practices. These variations have led to a call for a more systematic approach to identifying the most appropriate strategy for an individual patient; this approach is called evidence-based medicine (EBM). EBM is built on reviews of relevant medical literature and follows a discrete series of steps.
EBM is not the blind application of advice gleaned from recently published literature to individual patient problems. Rather, EBM requires the use of a series of steps to gather sufficiently useful information to answer a carefully crafted question for an individual patient. Fully integrating the principles of EBM also incorporates the patient's value system, which includes such things as costs incurred, the patient's religious or moral beliefs, and patient autonomy. Applying the principles of EBM typically involves the following steps:
Formulating a clinical question:
Questions must be specific. Specific questions are most likely to be addressed in the medical literature. A well-designed question specifies the population, intervention (diagnostic test, treatment), comparison (treatment A vs treatment B), and outcome. “What is the best way to evaluate someone with abdominal pain?” is not a good question. A better, more specific question may be “Is CT or ultrasonography preferable for diagnosing acute appendicitis in a 30-yr-old male with acute lower abdominal pain?”
Gathering evidence to answer the question:
A broad selection of relevant studies is obtained from a review of the literature. Standard resources are consulted (eg, MEDLINE, the Cochrane Collaboration [treatment options], the National Guideline Clearinghouse, ACP Journal Club).
Evaluating the quality and validity of the evidence:
Not all scientific studies are of equal value. Different types of studies have different scientific strengths and legitimacy, and for any given type of study, individual examples often vary in quality of the methodology, internal validity, and generalizability of results (external validity).
Levels of evidence are graded 1 through 5 in decreasing order of quality. Types of studies at each level vary somewhat with the clinical question (eg, of diagnosis, treatment, or economic analysis), but typically level 1 evidence (the highest quality) consists of systematic reviews or meta-analyses of randomized controlled trials and high-quality, single, randomized controlled trials. Level 2 evidence is well-designed cohort studies. Level 3 evidence is case-control studies. Level 4 evidence is case series and poor-quality cohort and case-control studies. Level 5 evidence is expert opinion not based on critical appraisal but is based on reasoning from physiology, bench research, or underlying principles.
For EBM analysis, the highest level of evidence available is selected. Ideally, a significant number of large, well-conducted level 1 studies are available. However, because the number of high-quality, randomized, controlled trials is vanishingly small compared with the number of possible clinical questions, less reliable level 4 or 5 evidence is very often all that is available. Lower-quality evidence does not mean that the EBM process cannot be followed, just that the strength of the conclusion is weaker.
Deciding how to apply the evidence to the care of a given patient:
Because the best available evidence may have come from patient populations with different characteristics from those of the patient in question, some judgment is required. Additionally, patients' wishes regarding aggressive or invasive tests and treatment must be taken into account as well as their tolerance for discomfort, risk, and uncertainty. For example, even though an EBM review may definitively show a 3-mo survival advantage from an aggressive chemotherapy regimen in a certain form of cancer, patients may differ on whether they prefer to gain the extra time or avoid the extra discomfort.
Dozens of clinical questions are faced during the course of even one day in a busy practice. Although some of them may be the subject of an existing EBM review available for reference, most are not, and preparing an EBM analysis is too time-consuming to be useful in answering an immediate clinical question. Even when time is not a consideration, many clinical questions do not have any relevant studies in the literature.
Clinical guidelines have become common in the practice of medicine; many specialty societies have published such guidelines. Most well-conceived clinical guidelines are developed using a specified method that incorporates principles of EBM and consensus recommendations made by a panel of experts.
Some clinical guidelines follow “if, then” rules (eg, if a patient is febrile and neutropenic, then institute broad-spectrum antibiotics). More complex, multistep rules may be formalized as algorithms. Guidelines and algorithms are generally straightforward and easy to use but should be applied only to patients whose clinical characteristics (eg, demographics, comorbidities, clinical features) are similar to those of the patient group used to create the guideline. Furthermore, guidelines do not take into account the degree of uncertainty inherent in test results, the likelihood of treatment success, and the relative risks and benefits of each course of action. To incorporate uncertainty and the value of outcomes into clinical decision making, clinicians must often apply the principles of quantitative or analytical medical decision making.
Last full review/revision March 2010 by Douglas L. McGee, DO
Content last modified March 2012