Evidence-based medicine (EBM) helps doctors incorporate the best available scientific evidence into their individual patient care decisions.
Today's doctors face a serious challenge trying to keep up with the vast amounts of new information on the latest available drugs, technology, and research. In fact, it is estimated that only 10% of the more than 4,500 medical articles published to databases every day are directly relevant to patient care. Evidence-based medicine provides doctors with a methodology to manage this vast amount of data.
Doctors who can easily access current best evidence are able to combine it with their own clinical expertise to determine how the research may help meet patients' individual treatment needs.
Doctors practice evidence-based medicine using a four-step process: ask a well-constructed clinical question; search for the best evidence to answer the question; critically evaluate the evidence; and apply the evidence to patients.
Ask a Well-Constructed Clinical Question
Asking a well-constructed clinical question involves use of the "PICO" mnemonic.
- P is for patient characteristics. These include age, gender, condition, social situation,
resources, values, and setting (rural or urban, inpatient or outpatient).
"For people under 60 with chronic low back pain..."
- I is for intervention. What treatment is your doctor considering? This could be a medication,
a diagnostic test, or a certain treatment.
"For people under 60 with chronic low back pain, is acupuncture..."
- C is for comparison. What option to the intervention can your doctor compare it to?
This could include alternative treatments or tests, or even no treatment at all.
"For people under 60 with chronic low back pain, is acupuncture as effective as wearing a brace..."
- O is for outcome. An outcome is the effect your doctor wants to achieve or avoid.
The outcome can be an effect from a treatment or its side effect.
"For people under 60 with chronic low back pain, is acupuncture as effective as wearing a brace in relieving pain."
Search for the Best Evidence to Answer the Question
Medical library databases house records of journal articles that contain the information, or evidence, needed to address the clinical question. Searching medical databases is similar to performing a Google search, but using sophisticated medical search engines instead.
Critically Evaluate the Evidence
The information obtained from searching the evidence must be evaluated. This involves assessing how well the research was conducted (the internal validity) and how well the results can be generalized to patients (external validity).
Apply the Evidence to Patients
Once the evidence has been critically evaluated, the doctor must decide whether the results apply to the specific patient. This involves identifying what is unique to the patient and the doctor, such as the doctor's knowledge, skill, and experience, as well as the patient's concerns and expectations.
It can be difficult to obtain high levels of evidence to answer some medical questions. This is especially true for problems with complex treatments or variations, such as orthopaedic surgery. In these situations, general guidelines based on evidence — called clinical practice guidelines — can help doctors make treatment decisions.
To develop a guideline, a panel of experts meticulously reviews the medical literature and scientific evidence to determine the highest level of evidence available to answer the specific medical question. The panel then uses its collective expertise to "fill in the gaps" where high-level evidence is lacking.
Guidelines provide doctors with the best available scientific evidence, and are a useful tool in making decisions about treatment options.
There are several different types of research studies and, depending upon the subject matter, some study results are more valid than others. This is often based upon a study's potential for bias.
Bias is defined as "prejudice in favor of or against one thing, person, or group compared with another, usually in a way considered to be unfair." There are many forms of bias that can occur in scientific experiments and drastically distort the results. Most of these biases are not intentional.
- Popularity bias may attract certain volunteers to a research study because it focuses on a popular trend, such as natural or organic treatment options.
- Publication bias may occur if a medical journal is more likely to publish a study with a positive result.
- Volunteer bias may occur when subjects who volunteer to participate in a study do not represent the population as a whole.
- Magnitude bias may occur if the reporting of research results exaggerates the occurrence of the problem. For example: Exposure to some agent may result in an additional 10,000 people becoming ill. Out of the total number of people affected, this represents only an increase of 0.0001%. The number 10,000 seems quite large, but 0.0001 is almost zero.
Double-blind Randomized Controlled Trial
The best way to minimize the chance of bias occurring in a scientific experiment is to perform a double-blind randomized controlled trial (RCT).
- Randomized means that patients are randomly placed into different treatment groups.
- Controlled means that some groups may not receive any treatment at all (or may receive a placebo).
- Double-blind means that neither the subjects nor the people involved in analyzing the results know which patients received the treatment and which did not.
Double-blind randomized controlled trials are usually conducted when the treatment being evaluated is a medicine. It is usually difficult and, more importantly, unethical to design this type of study when a complicated form of treatment, such as surgery, is involved. For example, doctors would not perform "fake" operations on patients to best evaluate whether performing a surgical procedure is better than other forms of treatment.
A cohort is a group of people who are being studied for a similar reason. They may have been exposed to a drug or toxin, or they may need a similar medical procedure. A cohort study follows this group of people over time, then compares them to a similar group of people who have not been exposed to the variable.
- Prospective cohort studies follow a group forward in time from the initial exposure.
- Retrospective cohort studies follow a group backward in time from a certain outcome.
A case-control study focuses on a certain medical condition. People with the condition (called cases) are compared to those who do not have the condition but are otherwise similar. The group without the condition is called the "controls" because they represent a healthy or normal condition. Examples of this type of study include those that demonstrated the strong association between lung cancer and smoking. Smokers (the cases) were compared to nonsmokers (the controls).
Case Series and Case Report Studies
A case series or case report is a collection of observations of a small group of similar patients (series), or of a single patient (report). A case report often documents an unusual appearance of a known disease or an account of a new disease or condition.
These types of research studies are observations with no control groups for comparison of outcomes.
In a meta-analysis, researchers carefully combine data from many similar studies in order to conduct a powerful statistical analysis. The results from this analysis are reported as if they were from one large study.
In evidence-based medicine, it is necessary to determine which research is the strongest and most authoritative. To evaluate the validity of a study's results, researchers consider the potential for bias. Some research studies are less susceptible to bias than others, depending upon the topic being analyzed. How well a study limits potential bias is tied to its validity, and determines where it falls within a hierarchy of evidence.
For example, to assess the effectiveness of a specific drug or new diagnostic test, the hierarchy of evidence generally looks like this:
- Randomized controlled trial
- Prospective cohort study
- Retrospective cohort study
- Case-control study
For any level in the hierarchy, a meta-analysis is more powerful than any single study. For instance, a meta-analysis of randomized controlled trials evaluating the benefit of Vitamin C in curing the common cold would be more powerful than the results of just one randomized controlled trial on the subject.
In cases where there is an obvious and large benefit to a treatment intervention, it may be unnecessary or even unethical to conduct randomized controlled trials. Patients in the control group would be deprived of the benefits of the intervention.
Randomized controlled trials may not be necessary when the mechanism of action of a drug or other intervention is well understood. In addition, trials may not be needed if the results can be reliably predicted from theory rather than experiment, or if a large number of consistent observational studies exist. For example, the benefits of pap smears, insulin, and penicillin are well known and the risk is very small that conclusions about their effectiveness would be wrong.
Real-life vs Trial Conditions
Randomized controlled trials often represent a "best-case" example. This means that patients in these studies are those most likely to follow all of the rules and conditions of the study. As a result, there is a greater chance for success.
In the real world, the results may be less effective. Randomized controlled trials may overestimate effectiveness because they take place under ideal, rather than real-life, conditions.
When technical interventions such as surgery are involved, the expertise of the surgeon may be as important as the results of a high-level study. For example, a randomized controlled trial may show that in certain circumstances, outcomes are better when a torn rotator cuff tendon is treated with arthroscopy. However, a surgeon who has many years of experience treating these tears with standard, open surgery may have better outcomes than a surgeon who is still mastering arthroscopic techniques.
There are more advantages to evidence-based medicine than simply providing a methodology for managing the large volume of available data.
Identifying Cost-Effective Treatment Options
The cost of health care remains high, and there are limited resources to serve large populations. As a result, there is increasing pressure for healthcare providers to demonstrate the effectiveness of the treatments they recommend, and to use the most cost effective measures to treat patients. EBM is a helpful tool in this regard.
Sharing Early Research Findings
Another advantage of EBM is that it helps to decrease the delay of "bench to bedside research." It can take many years for important breakthroughs discovered in the laboratory to become available to doctors and their patients. One study, published in Science, showed that the median time from initial discovery of a medical intervention to a highly cited article was 24 years.
This time period allows for extensive testing to evaluate the effectiveness and safety of a breakthrough. However, sometimes this delay can result in unnecessary harm if a new treatment has great promise. The EBM process allows better dissemination of early research findings to doctors and patients alike.
Evaluating Conflicting Results
EBM offers a way for practitioners to deal with conflicting results. It is not uncommon for one (or several) studies to show that an intervention is effective, while others show that the same intervention is not helpful. EBM provides a method of analyzing and "grading" the results of these studies, and even allows data from several studies to be combined in an effort to generate a more "powerful" answer.
Many misconceptions exist about what EBM is and is not. It is not cookbook medicine, managed care, cost-cutting measures, or rigid guidelines defining how a patient should be treated. When used appropriately, EBM is a rigorously systematic way for doctors to evaluate the appropriateness of available evidence for the care of an individual patient. EBM makes it possible for physicians to make treatment decisions based on an informed balance of patient values, clinical expertise, and available evidence.
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