Evidence-based medicine

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Evidence-based medicine is "the conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients.".[1] Alternative definitions are "the process of systematically finding, appraising, and using contemporaneous research findings as the basis for clinical decisions"[2] or "evidence-based medicine (EBM) requires the integration of the best research evidence with our clinical expertise and our patient's unique values and circumstances."[3] Better known as EBM, evidence based medicine emerged in the early 1990s as an additional guideline to help healthcare providers and policy makers evaluate the efficacy of treatment options.

Evidence-based practice is not restricted to medicine; dentistry, nursing and other allied health science are adopting "evidence-based medicine" as well. Even alternative medical approaches such as acupuncture and are being evaluated using the EBM methods. Evidence-Based Health Care or evidence-based practice extends the concept of EBM to all health professions, including purchasing and management [1].

Why do we need evidence-based medicine?

It is easy to assume that physicians always use scientific evidence conscientiously and judiciously in treating patients. In fact, most of the specific practices of physicians and surgeons are based on traditional techniques learned from their mentors in the care of patients during training. Additional modifications come from personal clinical experience, from information in the medical literature and continuing education courses. Although these practices almost always have a rational basis in biology, the actual efficacy of treatments is rarely tested by experimental trials in people. Further, even when the results of experimental trials or other evidence have been reported, there is a lag time between the acceptance of changes to medical practice and establishing them as routine in clinical care. EBM seeks to address these issues by promoting practices that have been shown to have validity using the scientific method.

Steps in evidence-based medicine

Ask

"Ask" - Formulate a well-structured clinical question.

Acquire

The ability to "acquire" evidence in a timely manner may improve healthcare.[4] Unfortunately, doctors may be led astray when acquiring information as often as they find correct answers.[5]

A proposed structure of the evidence search is the 5S search strategy,[6] which starts with the search of "summaries" (textbooks). A randomized controlled trial supports the efficiency of this approach.[7]

Appraise

To "Appraise" the quality of the answer found is very important as one third of the results of even the most visible medical research is eventually either attenuated or refuted.[8] There are many reasons for this[9]; two important reasons are publication bias[10] and conflict of interest[11]. These two problems interact, as conflict of interest often leads to publication bias.[12][10]

However an obvious important reason is that many (if not all) studies contain potential flaws in their design, and even when there are no clear methodological flaws, any outcome of a test that is evaluated by statistical test has a margin of error: this means that some positive outcomes will be "false positives".

Publication bias

Whether a treatment or medical intervention is effective or not may be judged either on the basis of the experience of the practising physician, or on the basis of what has been published by others. The publications with greatest authority are generally those that appear in the peer-reviewed scientific journals, and particularly in those journals generally thought to have the highest standards of editorial scrutiny. However, it is no simple matter to get a study published in any peer-reviewed journal, least of all in the best journals. Accordingly, many studies go unreported. It is often thought to be particularly difficult to publish small studies, the outcome of which conflicts with the reported outcomes of larger prviously published studies, or to publish studies where the outcome is equivocal - where no clear conclusion can be drawn. In part this reflects the wish of the best journals to publish influential papers, and in part it reflects simply the fact of authors choosing not to put their energies into publishing studies that are thought to be uninteresting. Such publication bias can be very difficult to recognise, but its effects generally tend to encourage publication of studies that support an already formed conclusion, while tending to discourage publication of contradictory or equivocal findings.[10][13] Publication bias may be more prevalent in industry sponsored research.[14]

In performing a meta-analyses, a file drawer[15] or a funnel plot analysis[16][17] may help detect underlying publication bias among the studies in the meta-analysis.

Conflict of interest

In any publication, there is always some issue of conflict of interest. Academic scientists gain their professional reputations by publishing, and it is always in their interest to be seen to be publishing interesting and important findings. They also have to answer to their sources of funding, whether the studies are funded by charities, public bodies or private industry. Accordingly all scientists are under pressure to publish, and under pressure to report and perhaps overstate any outcomes that might seem to be noteworthy; flat and purely factual summaries do not necessarily impress journal editors any more than they inspire casual readers.

However, when studies are funded by private industry there is inevitably some suspicion that they might be tainted by that association. In other words, when a particular outcome of a trial might lead to commercial advantage for its sponsor, will there not be some tendency, however inadvertent, to bias the design of the trial or bias its analysis to favour the desired outcome?

The responsibility for the integrity of the design and analysis of all studies lies squarely with the authors. If the academic and clinical scientists involved in any trial are lacking in competence or integrity, then indeed this might prejudice the value of the trial. It should be remembered that if any drug does have significant adverse effects, then it is very much in the interests of the pharmaceutical company manufacturing it that these be identified as quickly as possible, if only to minimise the very large costs of the inevitable eventual litigation. Thus, while it is in a pharmaceutical company's interests to report that its drug is better than a competitor's drug, or better than no treatment, it is very much not in their interests to suppress evidence of harm. However, for the scientists who are conducting the trials, things might seem a little different: if it becomes clear that a drug is useless or harmful, then the company will withdraw it and their funding for the studies will naturally cease. In the end, it is the integrity and competence of the academic and clinical scientists that determines the quality and value of trials, both for the public and indeed for their industrial sponsors.

In the design of randomized controlled trials, industry-sponsored studies may be more likely to select an inappropriate comparator group that would favor finding benefit in the experimental group. In other words, there is a tendency for industry-sponsored trials to compare the effectiveness of their drug with the effectiveness of an established current treatment rather than with a direct competitor that might also be better than the current treatment chosen for comparison [14]

Regarding the reporting of data in randomized controlled trials, industry-sponsored studies may be more likely to omit intention-to-treat analyses.[12]

Regarding the conclusions reached in randomized controlled trials, one study did not find evidence of overstatement[18]; however, a later study[19] found that industry sponsored studies are more likely to recommend the experimental drug as treatment of choice even after adjusting for the treatment effect. Similarly, industry sponsored studies may be more likely to conclude that drugs are safe, even when they have increased adverse effects.[20]

Unfortunately, the presence of authors with conflict of interests is not reliably indicated in journal articles.[21] In addition, when studied in the late 1990s, approximately 10% of some types of articles used 'ghost writers'.[22] Ghost writers mean that the credited author in the byline may not have been the real author and the real author may have a conflict of interest.

Other issues

Statistical analysis of the outcomes of a clinical trial is a complex and highly technical process. These often require the involvement of a professional medical statistician whose advice is needed in the design of the trial as well as in the analysis of its outcome. Flaws in the design of a trial can lead subsequently to weaknesses in statistical analysis. Ideally, a trial protocol should be carefully designed with statistical issues in mind, and with the hypothesis under test clearly formulated, and the agreed protocol should then be strictly adhered to. Often however problems arise during the test; for example, there may be unanticipated outcomes of the trial, or problems in patient recruitment or in compliance with the test protocol, and these problems can weaken the power and authority of the trial. Common problems include small sample sizes in some of the groups[23], problems of "multiple comparisons" when several different outcomes are being assessed, and biasing of study populations by selection criteria.

Apply

It is important to "apply" correctly the answers found. Common problems in applying evidence are 1) difficulties with numeracy and 2) recognition of the correct population that evidence applies to. Both patients and healthcare professionals have difficulties with health numeracy and probabilistic reasoning.[24]

Difficulties in applying evidence to the correct patient population

Studies document that extrapolating study results to the wrong patient populations (over-generalization)[25][26][27] and not applying study results to the correct population (under-utilization)[28][29] can both increase adverse outcomes.

The problem in over-generalization of study results may be more common among specialist physicians.[30] Two studies found specialists were more likely to adopt COX-2 drugs before the drugs were recalled by the FDA [31][32]. One of the studies went on to state "using COX-2s as a model for physician adoption of new therapeutic agents, specialists were more likely to use these new medications for patients likely to benefit but were also significantly more likely to use them for patients without a clear indication".[32] Similarly, orthopedists may provide more intensive care for back pain, but without benefit from the increased care.[33] Specialists may be less discriminating in their choice of journal reading. [34]

The problem of under-utilizing study results may be more common when physicians are practicing outside of their expertise. For example, specialist physicians are less likely to under-utilize specialty care[35][36], while primary care physicians are less likely to under-utilize preventive care[37][38].

Classification

Two types of evidence-based medicine have been proposed.[39]

Evidence-based guidelines

Evidence-based guidelines (EBG) is the practice of evidence-based medicine at the organizational or institutional level. This includes the production of guidelines, policy, and regulations.

Evidence-based individual decision making

Evidence-based individual decision (EBID) making is evidence-based medicine as practiced by the individual health care provider and an individual patient. There is concern that current evidence-based medicine focuses excessively on EBID.[39]

Evidence-based individual decision making can be further divided into three modes, "doer", "user", "replicator" by the intensity of the work by the individual.[40]

This categorization somewhat parallels the theory of Diffusion of innovations, but without pejorative terms, in which adopters of innovation are categorized as innovators (2.5%), early adopters (13%), early majority (33%), late majority (33%), and laggards (16%).[41] This categorization for doctors is supported by a preliminary empirical study of Green et al. that grouped doctors into Seekers, Receptives, Traditionalists, and Pragmatists.[42] The study of Green et al. has not been externally validated.

The same doctors may vary which group they resemble depending on how much time is available to seek evidence during clinical care.[43] Medicine residents early in training tend to prefer being taught the practitioner model, whereas residents later in training tended to prefer the user model.[44]

Doer

The "doer"[40] or "practitioner"[45] of evidence-based medicine does at least the first four steps (above) of evidence-based medicine and are performed for "self-acquired"[43] knowledge.

If the Doers are the same as the "Seekers" in the study of Green, then this group may be 3% of physicians.[42]

This group may also be the similarly small group of doctors who use formal Bayesian calculations[46] or MEDLINE searches[47].

User

For the "user" of evidence-based medicine, [literature] searches are restricted to evidence sources that have already undergone critical appraisal by others, such as evidence-based guidelines or evidence summaries"[40]. More recently, the 5S search strategy,[6] which starts with the search of "summaries" (evidence-based textbooks) is a quicker approach.[7]

If the Users are the same as the "Receptives" in the study of Green, then this group may be 57% of physicians.[42]

Replicator

For the "replicator", "decisions of respected opinion leaders are followed"[40]. This has been called "'borrowed' expertise".[43]

If the Replicators are the same as the "Traditionalists" and "Pragmatists" combined in the study of Green, then this group may be 40% of physicians.[42] This is a very broad group of doctors. Possibly the lowest end of this group may be equivalent to the laggards of Rogers. This much smaller group of doctors, ones who have "severely diminished capacity for self-improvement", may be at increased risk of disciplinary action by medical boards.[48]

Metrics used in evidence-based medicine

Diagnosis

  • Sensitivity and specificity
  • Likelihood ratios (Odds ratios)

Interventions

Relative measures

  • Relative risk ratio
  • Relative risk reduction

Absolute measures

  • Absolute risk reduction
  • Number needed to treat
  • Number needed to screen
  • Number needed to harm

Health policy

  • Cost per year of life saved[49]
  • Years (or months or days) of life saved. "A gain in life expectancy of a month from a preventive intervention targeted at populations at average risk and a gain of a year from a preventive intervention targeted at populations at elevated risk can both be considered large."[50]

Statistical significance

The outcome of a trial or study is often summarised by calculation of a "P-value" that expresses the likelihood that an observed difference (between treatment groups reflects a true difference in treatment effectiveness; the P value is a statistical calculation of the chance that the observed apparent difference reflects the chance outcome of random sampling. Some have argued that focussing on P values neglects other important sources of knowledge and information that should properly be used to assess the likely efficacy of a treatment [51] In particular, some argue that the P-value should be interpreted in light of how plausible is the hypothesis based on the totality of prior research and physiologic knowledge.[52][51][53]

Experimental trials: producing the evidence

For more information, see: Randomized controlled trial.

"A clinical trial is defined as a prospective scientific experiment that involves human subjects in whom treatment is initiated for the evaluation of a therapeutic intervention. In a randomized controlled clinical trial, each patient is assigned to receive a specific treatment intervention by a chance mechanism."[54] The theory behind these trials is that the value of a treatment will be shown in an objective way, and, though usually unstated, there is an assumption that the results of the trial will be applicable to the care of patients who have the condition that was treated.

The best evidence is thought to come from large multicentre clinical trials that are randomised and placebo-controlled, and which are conducted double-blind according to a predetermined schedule that is strictly adhered to. Trials should be large, so that serious adverse events might be detected even when they occur rarely. Multi-centre trials minimise problems that can arise when a single geographical locus has a population that is not fully representative of the global population, and they can minimise the effect of geographical variations in environmenet and health care delivery. Randomisation (if the study population is large enough) should mean that the study groups are unbiased. A double-blind trial is one in which neither the patient nor the deliverer of the treatment is aware of the nature of the treatment offered to any particular individual, and this avoids bias caused by the expectations of either the doctor or the patient. Placebo controls are important, because the placebo effect can often be very strong.

However such trials are very expensive, difficult to co-ordinate properly, and are often impractical to design optimally. For example, for many types of medical intervention, no satisfactory placebo treatment is possible. For several medical interventions, the use of a placebo, although feasible, is considered unethical (see Unethical use of placebos).

Evidence synthesis: summarizing the evidence

Systematic review

For more information, see: Systematic review.

A systematic review is a summary of healthcare research that involves a thorough literature search and critical appraisal of individual studies to identify the valid and applicable evidence. It often, but not always, uses appropriate techniques (meta-analysis) to combine these valid studies, and may grade the quality of the particular pieces of evidence according to the methodology used, and according to strengths or weaknesses of thstudy design.

While many systematic reviews are based on an explicit quantitative meta-analysis of available data, there are also qualitative reviews which nonetheless adhere to the standards for gathering, analyzing and reporting evidence.

Clinical practice guidelines

For more information, see: Clinical practice guideline.

Clinical practice guidelines are defined as "Directions or principles presenting current or future rules of policy for assisting health care practitioners in patient care decisions regarding diagnosis, therapy, or related clinical circumstances. The guidelines may be developed by government agencies at any level, institutions, professional societies, governing boards, or by the convening of expert panels. The guidelines form a basis for the evaluation of all aspects of health care and delivery."[55]

Medical informatics: Incorporating evidence into clinical care

For more information, see: Medical informatics.

Practicing clinicians usually cite the lack of time for reading newer textbooks or journals. However, the emergence of new types of evidence can change the way doctors treat patients. Unfortunately the recent scientific evidence gathered through well controlled clinical trials usually do not reach the busy clinicians in real time. Another potential problem lies in the fact that there may be numerous trials on similar interventions and outcomes but they are not systematically reviewed or meta-analyzed.

Medical informatics is an essential adjunct to EBM, and focuses on creating tools to access and apply the best evidence for making decisions about patient care.[3]

Before practicing EBM, informaticians (or informationists) must be familiar with medical journals, literature databases, medical textbooks, practice guidelines, and the growing number of other dedicated evidence-based resources, like the Cochrane Database of Systematic Reviews and Clinical Evidence.[56]

Similarly, for practicing medical informatics properly, it is essential to have an understanding of EBM, including the ability to phrase an answerable question, locate and retrieve the best evidence, and critically appraise and apply it.[57][58]

Studies of the effectiveness of teaching evidence-based medicine

A systematic review of the effectiveness of teaching EBM concluded "standalone teaching improved knowledge but not skills, attitudes or behaviour. Clinically integrated teaching improved knowledge, skills, attitudes and behaviour."[59] A second review concluded improvements in unvalidated measures of "knowledge, skills, attitudes or behavior."[60] Neither review examined improvements in clinical care.

Two systematic reviews of EBM provide the framework below for measuring outcomes.[61][62]

Information retrieval

Increasing use of information

A randomized controlled trial of volunteer senior medical students found that access to information portal on a handheld computer increased self-reported use of information.[63] The information portal contained multiple pre-appraised resources, including a textbook and drug resource, and would best resemble the "user" mode. The study was not able to isolate which resources in the portal had increased use. It is possible that the benefit was solely due to the textbook or drug resource.

A randomized controlled trial of teaching and encouraging use of MEDLINE by medical resident physicians showed increased searching for evidence during 6-8 weeks of observation.[64] Based on the median number of searches and hours spent searching, each search averaged 22 minutes, which may not be sustainable over the long term.

Improving clinical care

Teaching "user" mode only using syntheses and synopses, without summaries, has not shown benefit in two studies. A controlled trial of teaching the "user" mode (see above) was negative.[65] However, this study encouraged the use of syntheses and synopses and did not encourage the more practical "summaries" (evidence-based textbooks) of the "5S" search strategy.[6] A quasi-randomized, controlled investigation of teaching medical students the use of studies, syntheses, and synopses using an automated search engine was negative.[66]

Information awareness

A cluster randomized trial of McMaster Premium LiteratUre Service (PLUS) led to " increased the utilization of evidence-based information from a digital library by practicing physicians."[67]

No controlled studies have addressed improving clinical care by use of information awareness strategies.

A controlled trial of teaching Bayesian principles (probabilistic reasoning) "improves the efficiency of test ordering."[68]

Studies on how to teach evidence-based medicine

This sections includes implications based on the preceding discussion on studies of effectiveness. In addition, this section includes other studies or reports of teaching methods, even though these methods have not been subjected to study of effect on clinical outcomes.

Search strategies

A search strategy similar to the 5S strategy should be taught for use when the searcher has limited time available during clinical care. This is based on one positive study of its use[7] and two negative studies[65][66] of teaching the use using secondary and primary publications. In addition, indirect evidence on the time needed to search also supports the emphasis on using tertiary publications. Doctors may have two minutes available to search[47], whereas using MEDLINE may take 20 minutes or more.[69][64]

Teaching MEDLINE searching would be appropriate for Doers who might be willing to invest time in searching MEDLINE when not hurried by clinical care. Based on studies of common errors in searching MEDLINE, learners should be taught Medical Subject Headings (MeSH) terms and their explosion, appropriate limits, and best evidence to search for.[70] The mnemonic PEARL may guide how to each.[71] PEARL stands for:

  1. "Choose a 'Preplanned search intervention'"
  2. "Allow learners to 'Execute the search,' thus committing themselves"
  3. "'Allow learners to teach other learners' about their search process
  4. "'Review the quality of evidence' for the information found"
  5. "Discuss 'Lessons of the search.'"

Clinical reasoning

There are various methods of clinical reasoning include probabilistic (Bayesian), causal (physiologic), and deterministic (rule-based).[72] In addition, medical experts rely more on pattern recognition which is faster and less prone to error[73]; however, clinical experts seem flexible and may use whichever method of reasoning most easily represents and solves a given problem.[74] Scales to measure clinical reasoning have been proposed.[75] Explicit Bayesian thinking with precise numbers is rarely done.[76][46] Basic science knowledge is probably "encapsulated" into clinical knowledge.[77]

Competing-hypotheses heuristic[78]
Finding Disease A Disease B
Fever 66% cell B
Rash cell C cell D
The most important missing information is cell B

Possible strategies to improve clinical reasoning have been reviewed[79][80] and using problem-based learning[80], include teaching appropriate problem representation creating a one-sentence summary of a case[79], standardized patients[81], teaching hypothetico-deductive reasoning[82][83], cognitive forcing strategies[84][85] to avoid premature closure[86], teaching the competing-hypotheses heuristic[78], and using fuzzy-trace theory[87].

Studies are inconclusive on using cognitive feedback[88] and teaching logic[89][90].


Criticisms of evidence-based medicine

There are a number of criticisms of EBM.[91][40] Most generally, EBM has been criticized as an attempt to define knowledge in medicine in the same way that was done unsuccessfully by the logical positivists in epistemology, "trying to establish a secure foundation for scientific knowledge based only on observed facts".[92]

Unethical use of placebos

According to EBM, placebo control is an important element of the gold standard trial. The Declaration of Helsinki by the the World Medical Association condems the use of placebos if a beneficial treatment has already been recognized.[93] Many scientists and ethicists consider that the U.S. Food and Drug Administration, by demanding placebo-controlled trials, encourages the systematic violation of the Declaration of Helsinki.[94] The use of placebo controls remains a convenient way to avoid direct comparisons with a competing drug.

Lack of randomized controlled trials for clinical decisions

Randomized controlled trials are available to support to 21%[95] 53%[96] of principle therapeutic decisions.[97] Due to this, evidence-based medicine has evolved to accept lesser levels of evidence when randomized controlled trials are not available.[98]

Ulterior motives

An early criticism of evidence-based medicine is that it will be a guise for rationing resources or other goals that are not in the interest of the patient.[99][100] In 1994, the American Medical Association helped introduce the "Patient Protection Act" in Congress to reduce the power of insurers to use guidelines to deny payment for a medical services.[101]

As a possible example, Milliman Care Guidelines state they produce "evidence-based clinical guidelines since 1990".[102] In 2000, an academic pediatrician sued Milliman for using his name as an author on a practice guidelines that he stated were "dangerous" [103][104][105] A similar suit disputing the origin of care decisions at Kaiser has been filed.[106] The outcomes of both suits are not known.

Conversely, clinical practice guidelines by the Infectious Disease Society of America are being investigated by Connecticut's attorney general on grounds that the guidelines, which do not recognize a chronic form of Lyme disease, are anticompetitive.[107][108]

Fallibility of knowledge

Evidence-based medicine has been criticized on epistemologic grounds as "trying to establish a secure foundation for scientific knowledge based only on observed facts"[92] and not recognizing the fallible nature[109] of knowledge in general. The inevitable failure of reliance on empiric evidence as a foundation for knowledge was recognized over 100 years ago and is known as the "Problem of Induction" or "Hume's Problem".[110]

Complexity theory is proposed as further explaining the nature of medical knowledge,[111][112] though probably still cannot solve issues of fallibility of knowledge and the failure of induction.

References

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