Evidence-based medicine: Difference between revisions

From Citizendium
Jump to navigation Jump to search
imported>Supten Sarbadhikari
imported>Robert Badgett
Line 120: Line 120:
===Health policy===
===Health policy===
* Cost per year of life saved<ref name="pmid7604170">{{cite journal |author=Tengs TO ''et al'' |title=Five-hundred life-saving interventions and their cost-effectiveness |journal=Risk Anal |volume=15 |pages=369–90 |year=1995 |pmid=7604170 |doi=}}</ref>
* Cost per year of life saved<ref name="pmid7604170">{{cite journal |author=Tengs TO ''et al'' |title=Five-hundred life-saving interventions and their cost-effectiveness |journal=Risk Anal |volume=15 |pages=369–90 |year=1995 |pmid=7604170 |doi=}}</ref>
* 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."<ref name="pmid9691106">{{cite journal |author=Wright JC, Weinstein MC |title=Gains in life expectancy from medical interventions--standardizing data on outcomes |journal=N Engl J Med |volume=339 |pages=380–6 |year=1998 |pmid=9691106 |doi=}}</ref>
* Cost of Preventing an Event (COPE)<ref name="pmid18170986">{{cite journal |author=Maharaj R |title=Adding cost to NNT: the COPE statistic |journal=ACP J. Club |volume=148 |issue=1 |pages=A8 |year=2008 |pmid=18170986 |doi= |issn=|url=http://www.acpjc.org/Content/148/1/issue/ACPJC-2008-148-1-A08.htm}}</ref>. For example, to prevent a major vascular event n a high-risk adult , the [[number needed to treat]] is 19, the number of years of treatment are 5, and the daily cost of the generic drug is 68 cents. The COPE is 19 * 5 * ( 365 * .68) which equals $23,579 in the United States.
* 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."<ref name="pmid9691106">{{cite journal |author=Wright JC, Weinstein MC |title=Gains in life expectancy from medical interventions--standardizing data on outcomes |journal=N Engl J Med |volume=339 |pages=380–6 |year=1998 |pmid=9691106 |doi=}}</ref>


==Research studies: producing the evidence==
==Research studies: producing the evidence==

Revision as of 16:50, 7 February 2008

This article has a Citable Version.
 Main Article
 Discussion
Related Articles  [?]
Bibliography  [?]
External Links  [?]
Citable Version  [?]
 
https://en.citizendium.org/wiki/index.php?title=Evidence-based_medicine&printable=yes
This editable Main Article has an approved citable version (see its Citable Version subpage). While we have done conscientious work, we cannot guarantee that this Main Article, or its citable version, is wholly free of mistakes. By helping to improve this editable Main Article, you will help the process of generating a new, improved citable version.

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 1990's to help healthcare providers and policy makers evaluate the efficacy of different treatments.

Evidence-based practice is not restricted to medicine; dentistry, nursing and other allied health science are adopting "evidence-based medicine" as well as alternative medical approaches, such as acupuncture[4][5]. Evidence-Based Health Care or evidence-based practice extends the concept of EBM to all health professions, including management[6][7] and policy[8][9][10].

Classification

Two types of evidence-based medicine have been proposed.[11]

Evidence-based guidelines

Evidence-based guidelines is EBM at the organizational or institutional level, and involves producing guidelines, policy, and regulations.

Evidence-based individual decision making

Evidence-based individual decision making is EBM as practiced by an individual health care provider when treating an individual patient. There is concern that evidence-based medicine focuses excessively on the physician-patient dyad and as a result missing many opportunities to improve healthcare.[11]

Why do we need EBM?

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 EBM

See also Teaching evidence-based medicine
The 5 S search strategy[12]

Studies: original research studies that can be found using search engines like PubMed.

Synthesis: systematic reviews or Cochrane Reviews.

Synopses: in EBM journals, ACP Journal club etc. give brief descriptions of original articles and reviews as they appear .

Summaries: in EBM textbooks integrate the best available evidence from syntheses to give evidence-based management options for a health problem.

Systems: e.g. computerized decision support systems that link individual patient characteristics to relevant evidence.

Ask

To "ask" and formulate a well-structured clinical question, i.e. one that is directly relevant to the identified problem, and which is constructed in a way that facilitates searching for an answer. The question should have four elements: the patient or problem; the medical intervention or exposure (e.g., a cause for a disease); the comparison intervention or exposure; and the clinical outcomes. The better focused the question is, the more relevant and specific the search for evidence will be.

Acquisition of evidence

The ability to "acquire" evidence, also called information retrieval, in a timely manner may improve healthcare.[13][14] Unfortunately, doctors may be led astray when acquiring information if they do not systematically review all available evidence, because individual trials may be flawed or their outcomes may not be fully representative.[15] One proposed structure for a comprehensive evidence search is the 5S search strategy,[12] which starts with the search of "summaries" (textbooks). [16]

Appraisal of evidence

The U.S. Preventive Services Task Force (USPSTF) [17] grades its recommendations for treatments according to the strength of the evidence and the expected overall benefit (benefits minus harms). Its grades are:

A.— Good evidence that the treatment improves health outcomes, and benefits substantially outweigh harms.

B.— Fair evidence that the treatment improves health outcomes and that benefits outweigh harms.

C.— Fair evidence that the treatment can improve health outcomes but the balance of benefits and harms is too close to justify a general recommendation.

D.— Recommendation against routinely providing the treatment to asymptomatic patients. There is fair evidence that [the service] is ineffective or that harms outweigh benefits.

I.— The evidence is insufficient to recommend for or against routinely providing [the service]. Evidence that the treatment is effective is lacking, of poor quality, or conflicting and the balance of benefits and harms cannot be determined.

The USPSTF also grades the quality of the overall evidence as good, fair or poor:

Good: Evidence includes consistent results from well-designed, well-conducted studies in representative populations that directly assess effects on health.

Fair: Evidence is sufficient to determine effects on health outcomes, but its strength is limited by the number, quality, or consistency of the individual studies, generalizability to routine practice, or indirect nature of the evidence on health outcomes.

Poor: Evidence is insufficient to assess the effects on health outcomes because of limited number or power of studies, flaws in their design or conduct, gaps in the chain of evidence, or lack of information on important health outcomes.

To "Appraise" the quality of the evidence is very important, as one third of the results of even the most visible medical research is eventually either attenuated or refuted.[18] There are many reasons for this[19]; two of the most common being publication bias[20] and conflict of interest[21] (see article on Medical ethics). These two problems interact, as conflict of interest often leads to publication bias.[22][20]

Complicating the appraisal process further, many (if not all) studies contain some 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".

It is very common to read only the abstract of an article.[23] However, many abstracts contain errors compared to the body of the article.[24] Fortunately, these are usually errors of omission rather than contradiction.

Methods proposed for assessing validity

"Levels of evidence" are used for describing the strength of an individual original research study.[25][26][27][28]

Guides also exist for assessing a body of literature; these guides include the U.S. Preventive Services Task Force (USPSTF) (see yellow text box) and the American College of Chest Physicians[27][28]. More recent methods by the Grade Working Group[29] combine the quality of research studies with their clinical relevance.[30] For example, this allows comparing a randomized control trial in a population that is not exactly like the population of interest versus a cohort study that is from a relevant population. The concept that there are multiple dimensions in assessing evidence has been expanded to a proposal that assessing evidence is not a linear process, but is circular.[31]

Common threats to validity

Publication bias
Whether a treatment or medical intervention is effective or not may be judged either by the experience of the practising physician, or by what has been published by others. The publications with greatest authority are generally those in the peer-reviewed scientific journals, and particularly those journals with the highest standards of editorial scrutiny. However, it is not simple 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 difficult to publish small studies, the outcome of which conflicts with the reported outcomes of larger previously published studies, or to publish studies from which 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 authors choosing not to publish studies that are thought to be uninteresting. Such publication bias can be difficult to recognise, but its effects tend to encourage publication of studies that support an already formed conclusion, while discouraging publication of contradictory or equivocal findings.[20][32] Publication bias may be more common in industry sponsored research.[33]

In performing a meta-analyses, a file drawer[34] or a funnel plot analysis[35][36] may help detect underlying publication bias among the studies in the meta-analysis.

Conflict of interest
The presence of a conflict of interest has many effects in medical publishing. See Medical ethics: conflicts of interest for more information.

Statistical analysis
Statistical analysis of the outcomes of a clinical trial is a complex and highly technical process that often needs a professional medical statistician to advise on the design of the trial as well as on the analysis of its outcome. Flaws in the design of a trial can lead to weaknesses in statistical analysis. Ideally, a trial 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, 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[37], problems of "multiple comparisons" when several outcomes are being assessed, and biasing of study populations by selection criteria.

The outcome of a study is often summarised by 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 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 [38] 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.[39][38][40]

Application

It is important to "apply" the best practices found to the correct situation. One common problem in applying evidence is that both patients and healthcare professionals often have difficulties with health numeracy and probabilistic reasoning.[41]

A second problem is successful clinical reasoning at the bedside.[42] Successful reasoning is associated with the use of pattern matching [43][44] and recognizing clinical findings that are "pivot" or specific to certain diseases[44].

A third problem is in identifying exactly which patients will benefit from the new practices. Extrapolating study results to the wrong patient populations (over-generalization)[45][46][47] and not applying study results to the correct population (under-utilization)[48][49] can both increase adverse outcomes.

The problem of over-generalizating study results may be more common among specialist physicians.[50] Two studies found specialists were more likely to adopt cyclooxygenase 2 inhibitor drugs before the drug rofecoxib was withdrawn by its manufacturers after it emerged that its use had unanticipated adverse effects [51][52]. 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".[52]

Similarly, orthopedists provide more expensive care for back pain, but without measurably increased benefit compared to other types of practitioners.[53] Some of the reason that subspecialists may be more likely to adopt inadequately studied innovations is that they read from a spectrum of journals that have less consistent quality.[54] Articles from specialty journals have been noted to persist in supporting claims in the medical literature that have been refuted.[55]

The problem of under-utilizing study results may be more common when physicians are practising outside their expertise. For example, specialist physicians are less likely to under-utilize specialty care[56][57], while primary care physicians are less likely to under-utilize preventive care[58][59].

Metrics used in EBM

Diagnosis

Interventions

Relative measures

  • Relative risk ratio
  • Relative risk reduction

Absolute measures

Health policy

  • Cost per year of life saved[62]
  • Cost of Preventing an Event (COPE)[63]. For example, to prevent a major vascular event n a high-risk adult , the number needed to treat is 19, the number of years of treatment are 5, and the daily cost of the generic drug is 68 cents. The COPE is 19 * 5 * ( 365 * .68) which equals $23,579 in the United States.
  • 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."[64]

Research studies: producing the evidence

Levels of evidence

'Levels of evidence' have been proposed to create a framework for judging the strength of research.[65] An example of levels of evidence is:

Randomized controlled trial

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."[66] The theory behind these trials is that the value of a treatment will be shown in an objective way, and, it is assumed that the results will be applicable to the care of patients who have the condition that was treated.

In practice, randomized controlled trials are available to support only 21%[67] to 53%[68] of principle therapeutic decisions.[69] Due to this, evidence-based medicine has evolved to accept lesser levels of evidence when randomized controlled trials are not available.[70]

Cohort studies

For more information, see: Cohort study.


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."[71]

Incorporating evidence into clinical care

Medical informatics

For more information, see: Medical informatics.

Practicing clinicians cite the lack of time for keeping up with emerging medical evidence that may change clinical practice.[72] 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.[72]

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.[73][74]

Teaching evidence-based medicine

For more information, see: Teaching evidence-based medicine.


Criticisms of EBM

Statue of David Hume. "Man is a reasonable being; and as such, receives from science his proper food and nourishment: But so narrow are the bounds of human understanding, that little satisfaction can be hoped for in this particular..." Hume recognised clearly the difficulties in gaining a general understanding merely by accumulating observations.

There are a number of criticisms of EBM.[75][76] 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" [77]and not recognizing the fallible nature of knowledge in general.[78] The problem of relying 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".[79]

A general problem with EBM is that it seeks to make recommendations for treatment that (on balance) are likely to provide the best treatment for most patients. However what is the best treatment for most patients is not necessarily the best treatment for a particular individual patient. The causes of disease, and the patient responses to treatment all vary considerably, and are affected for example by the individual's genetic make-up, their particular history, and by factors of individual lifestyle. To take these properly into account requires the clinical experience of the treating physician, and over-reliance upon recommendations based upon statistical outcomes of treatments given in a standardised way to large populations may not always lead to the best care for a particular individual.


Ulterior motives

An early criticism of EBM is that it will be a guise for rationing resources or other goals that are not in the interest of the patient.[80][81] 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.[82] As a possible example, Milliman Care Guidelines state they produce "evidence-based clinical guidelines since 1990".[83] In 2000, an academic pediatrician sued Milliman for using his name as an author on a practice guidelines that he stated were "dangerous" [84][85][86] A similar suit disputing the origin of care decisions at Kaiser has been filed.[87] 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.[88][89]

EBM not recognizing the limits of clinical epidemiology

EBM is a set of techniques derived from clinical epidemiology, but a common criticism is that epidemiology can show association but not causation. While clinical epidemiology has its role in inspiring clinical decisions if it is complemented with testable hypotheses on disease,[90] many critics consider that EBM is a form of clinical epidemiology which became so common in health care systems, and imposed such an empiricist bias on medical research, that it has undermined the notion of causal inference in clinical practice.[91] It is argued that it has even become condemnable to use common sense,[92] as was cleverly illustrated in a systematic review of randomized controlled trials studying the effects of parachutes against gravitational challenges (free falls).[93]


Lorenz butterfly showing effect of two attractors over time in a complex, chaotic system. Such systems are deterministic - i.e. they are not random, but indeed are completely determined by a fixed set of differential equations. However these systems are extremely sensitive in an "unpredictable" way to very slight perturbations, in that apparently trivial changes can sometimes (but unpredictably) produce a large effect. In a sense, such perturbations "cause" the ensuing effect, but not in any reproducible manner. Some risk factors for disease may be like such perturbations of a complex chaotic system in that they sometimes have a large effect but generally have no effect. Understanding how particular factors might influence disease processes in an unpredictable way may be important for managing some disease conditions.

Complexity theory
Complexity theory and chaos theory are proposed as further explaining the nature of medical knowledge[94][95] and education[96]. Regarding health services research, although complexity theory has not advanced to the state of being able to mathematically model healthcare delivery, it has been used as a framework for case study[97][98][99][100] and traditional bivariate analysis[101] of healthcare delivery. For example, a systematic review of organizational interventions to improve the quality of care of diabetes mellitus type 2 suggests that interventions based on complexity theory will be more successful.[101] If the goal of modeling healthcare is to comply with specific quality indicators, interventions based on systems theory may be more effective than those based on complexity theory.[102] Regarding basic science research, fractal patterns have been found in cardiac conduction and fluctuations in vital signs over time.[103] Fractals are evidence of a system that follows the non-linear mathematics of a complex adaptive system. That are many other examples of fractal patterns in nature including the prediction of weather patterns.[104]

References

  1. ↑ Sackett DL et al. (1996). "Evidence based medicine: what it is and what it isn't". BMJ 312: 71–2. PMID 8555924. [e]
  2. ↑ Evidence-Based Medicine Working Group (1992). "Evidence-based medicine. A new approach to teaching the practice of medicine. Evidence-Based Medicine Working Group". JAMA 268: 2420–5. PMID 1404801. [e]
  3. ↑ 3.0 3.1 Glasziou, Paul; Strauss, Sharon Y. (2005). Evidence-based medicine: how to practice and teach EBM. Elsevier/Churchill Livingstone. ISBN 0-443-07444-5. 
  4. ↑ Manheimer E et al. (2007). "Meta-analysis: acupuncture for osteoarthritis of the knee". Ann Intern Med 146: 868–77. PMID 17577006. [e]
  5. ↑ Assefi NP et al. (2005). "A randomized clinical trial of acupuncture compared with sham acupuncture in fibromyalgia". Ann Intern Med 143: 10–9. PMID 15998750. [e]
  6. ↑ Clancy CM, Cronin K (2005). "Evidence-based decision making: global evidence, local decisions". Health Affairs (Project Hope) 24: 151–62. DOI:10.1377/hlthaff.24.1.151. PMID 15647226. Research Blogging.
  7. ↑ Shojania KG, Grimshaw JM (2005). "Evidence-based quality improvement: the state of the science". Health Affairs (Project Hope) 24: 138–50. DOI:10.1377/hlthaff.24.1.138. PMID 15647225. Research Blogging.
  8. ↑ Fielding JE, Briss PA (2006). "Promoting evidence-based public health policy: can we have better evidence and more action?". Health Affairs (Project Hope) 25: 969–78. DOI:10.1377/hlthaff.25.4.969. PMID 16835176. Research Blogging.
  9. ↑ Foote SB, Town RJ (2007). "Implementing evidence-based medicine through medicare coverage decisions". Health Affairs (Project Hope) 26 (6): 1634–42. DOI:10.1377/hlthaff.26.6.1634. PMID 17978383. Research Blogging.
  10. ↑ Fox DM (2005). "Evidence of evidence-based health policy: the politics of systematic reviews in coverage decisions". Health Affairs (Project Hope) 24: 114–22. DOI:10.1377/hlthaff.24.1.114. PMID 15647221. Research Blogging.
  11. ↑ 11.0 11.1 Eddy DM (2005). "Evidence-based medicine: a unified approach". Health Affairs (Project Hope) 24: 9-17. DOI:10.1377/hlthaff.24.1.9. PMID 15647211. Research Blogging.
  12. ↑ 12.0 12.1 Haynes RB (2006). "Of studies, syntheses, synopses, summaries, and systems: the "5S" evolution of information services for evidence-based health care decisions". ACP J Club 145: A8. PMID 17080967. [e]
  13. ↑ Banks DE et al. (2007). "Decreased hospital length of stay associated with presentation of cases at morning report with librarian support". JMLA 95: 381–7. DOI:10.3163/1536-5050.95.4.381. PMID 17971885. Research Blogging.
  14. ↑ Lucas BP, Evans AT, Reilly BM, et al (2004). "The impact of evidence on physicians' inpatient treatment decisions". J Gen Intern Med 19 (5 Pt 1): 402–9. DOI:10.1111/j.1525-1497.2004.30306.x. PMID 15109337. Research Blogging.
  15. ↑ McKibbon KA, Fridsma DB (2006). "Effectiveness of clinician-selected electronic information resources for answering primary care physicians' information needs". JAMIA 13: 653–9. DOI:10.1197/jamia.M2087. PMID 16929042. Research Blogging.
  16. ↑ Patel MR et al. (2006). "Randomized trial for answers to clinical questions: evaluating a pre-appraised versus a MEDLINE search protocol". JMLA 94: 382–7. PMID 17082828. [e]
  17. ↑ U.S. Preventive Services Task Force Ratings: [Strength of Recommendations and Quality of Evidence. Guide to Clinical Preventive Services, Third Edition: Periodic Updates, 2000-2003. Hosted by Agency for Healthcare Research and Quality, Rockville, MD.
  18. ↑ Ioannidis JP (2005). "Contradicted and initially stronger effects in highly cited clinical research". JAMA 294: 218–28. DOI:10.1001/jama.294.2.218. PMID 16014596. Research Blogging.
  19. ↑ Ioannidis JP et al. (1998). "Issues in comparisons between meta-analyses and large trials". JAMA 279: 1089–93. PMID 9546568. [e]
  20. ↑ 20.0 20.1 20.2 Dickersin K et al. (1992). "Factors influencing publication of research results. Follow-up of applications submitted to two institutional review boards". JAMA 267: 374–8. PMID 1727960. [e] Cite error: Invalid <ref> tag; name "pmid1727960" defined multiple times with different content Cite error: Invalid <ref> tag; name "pmid1727960" defined multiple times with different content
  21. ↑ Smith R (2005). "Medical journals are an extension of the marketing arm of pharmaceutical companies". PLoS Med 2: e138. DOI:10.1371/journal.pmed.0020138. PMID 15916457. Research Blogging.
  22. ↑ Melander H et al. (2003). "Evidence b(i)ased medicine--selective reporting from studies sponsored by pharmaceutical industry: review of studies in new drug applications". BMJ 326: 1171–3. DOI:10.1136/bmj.326.7400.1171. PMID 12775615. Research Blogging.
  23. ↑ Saint S, Christakis DA, Saha S, et al (2000). "Journal reading habits of internists". J Gen Intern Med 15 (12): 881–4. PMID 11119185. [e]
  24. ↑ Pitkin RM, Branagan MA, Burmeister LF (1999). "Accuracy of data in abstracts of published research articles". JAMA 281 (12): 1110–1. PMID 10188662. [e]
  25. ↑ Canadian Task Force on the Periodic Health Examination (1979) The periodic health examination. Can Med Assoc J ;21:1193-254
  26. ↑ Goldbloom R, Battista RN (1986). "The periodic health examination: 1. Introduction". CMAJ 134: 721–3. PMID 3948088. [e] PubMed Central
  27. ↑ 27.0 27.1 Sackett DL (1989). "Rules of evidence and clinical recommendations on the use of antithrombotic agents". Chest 95: 2S–4S. DOI:10.1378/chest.95.2.2S. PMID 2914516. Research Blogging.
  28. ↑ 28.0 28.1 Sackett DL (1986). "Rules of evidence and clinical recommendations on the use of antithrombotic agents". Chest 89: 2S–3S. PMID 3943408. [e]
  29. ↑ GRADE working group. Retrieved on 2007-11-23.
  30. ↑ Atkins D et al. (2004). "Grading quality of evidence and strength of recommendations". BMJ 328: 1490. DOI:10.1136/bmj.328.7454.1490. PMID 15205295. Research Blogging.
  31. ↑ Walach H et al. (2006). "Circular instead of hierarchical: methodological principles for the evaluation of complex interventions". BMC Med Res Methodol 6: 29. DOI:10.1186/1471-2288-6-29. PMID 16796762. Research Blogging.
  32. ↑ Krzyzanowska MK et al. (2003). "Factors associated with failure to publish large randomized trials presented at an oncology meeting". JAMA 290: 495–501. DOI:10.1001/jama.290.4.495. PMID 12876092. Research Blogging.
  33. ↑ Lexchin J et al. (2003). "Pharmaceutical industry sponsorship and research outcome and quality: systematic review". BMJ 326: 1167–70. DOI:10.1136/bmj.326.7400.1167. PMID 12775614. Research Blogging.
  34. ↑ Pham B et al. (2001). "Is there a "best" way to detect and minimize publication bias? An empirical evaluation". Evaluation & the Health Professions 24: 109–25. PMID 11523382. [e]
  35. ↑ Egger M et al. (1997). "Bias in meta-analysis detected by a simple, graphical test". BMJ 315: 629–34. PMID 9310563. [e]
  36. ↑ Terrin N et al. (2005). "In an empirical evaluation of the funnel plot, researchers could not visually identify publication bias". J Clin Epidemiol 58: 894–901. DOI:10.1016/j.jclinepi.2005.01.006. PMID 16085192. Research Blogging.
  37. ↑ Glasziou P, Doll H (2007). "Was the study big enough? Two "café" rules (Editorial)". ACP J Club 147: A08. PMID 17975858. [e]
  38. ↑ 38.0 38.1 Goodman SN (1999). "Toward evidence-based medical statistics. 1: The P value fallacy". Ann Intern Med 130: 995–1004. PMID 10383371. [e]
  39. ↑ Browner WS, Newman TB (1987). "Are all significant P values created equal? The analogy between diagnostic tests and clinical research". JAMA 257: 2459–63. PMID 3573245. [e]
  40. ↑ Goodman SN (1999). "Toward evidence-based medical statistics. 2: The Bayes factor". Ann Intern Med 130: 1005–13. PMID 10383350. [e]
  41. ↑ Ancker JS, Kaufman D (2007). "Rethinking health numeracy: a multidisciplinary literature review". DOI:10.1197/jamia.M2464. PMID 17712082. Research Blogging.
  42. ↑ Dubeau CE, Voytovich AE, Rippey RM (1986). "Premature conclusions in the diagnosis of iron-deficiency anemia: cause and effect". Med Decis Making 6 (3): 169–73. PMID 3736379. [e]
  43. ↑ Coderre S, Mandin H, Harasym PH, Fick GH (2003). "Diagnostic reasoning strategies and diagnostic success". Med Educ 37 (8): 695–703. PMID 12895249. [e]
  44. ↑ 44.0 44.1 Eddy DM, Clanton CH (1982). "The art of diagnosis: solving the clinicopathological exercise". N. Engl. J. Med. 306 (21): 1263–8. PMID 7070446. [e]
  45. ↑ Gross CP et al. (2000). "Relation between prepublication release of clinical trial results and the practice of carotid endarterectomy". JAMA 284: 2886–93. PMID 11147985. [e]
  46. ↑ Juurlink DN et al. (2004). "Rates of hyperkalemia after publication of the Randomized Aldactone Evaluation Study". N Engl J Med 351: 543–51. DOI:10.1056/NEJMoa040135. PMID 15295047. Research Blogging.
  47. ↑ Beohar N et al. (2007). "Outcomes and complications associated with off-label and untested use of drug-eluting stents". JAMA 297: 1992–2000. DOI:10.1001/jama.297.18.1992. PMID 17488964. Research Blogging.
  48. ↑ Soumerai SB et al. (1997). "Adverse outcomes of underuse of beta-blockers in elderly survivors of acute myocardial infarction". JAMA 277: 115–21. PMID 8990335. [e]
  49. ↑ Hemingway H et al. (2001). "Underuse of coronary revascularization procedures in patients considered appropriate candidates for revascularization". N Engl J Med 344: 645–54. PMID 11228280. [e]
  50. ↑ Turner BJ, Laine C (2001). "Differences between generalists and specialists: knowledge, realism, or primum non nocere?". J Gen Intern Med 16: 422-4. DOI:10.1046/j.1525-1497.2001.016006422.x. PMID 11422641. Research Blogging. PubMed Central
  51. ↑ Rawson N et al. (2005). "Factors associated with celecoxib and rofecoxib utilization". Ann Pharmacother 39: 597-602. PMID 15755796.
  52. ↑ 52.0 52.1 De Smet BD et al. (2006). "Over and under-utilization of cyclooxygenase-2 selective inhibitors by primary care physicians and specialists: the tortoise and the hare revisited". J Gen Intern Med 21: 694-7. DOI:10.1111/j.1525-1497.2006.00463.x. PMID 16808768. Research Blogging.
  53. ↑ Carey T et al. (1995). "The outcomes and costs of care for acute low back pain among patients seen by primary care practitioners, chiropractors, and orthopedic surgeons. The North Carolina Back Pain Project". N Engl J Med 333: 913-7. PMID 7666878.
  54. ↑ McKibbon KA et al. (2007). "Which journals do primary care physicians and specialists access from an online service?". JMLA 95: 246-54. DOI:10.3163/1536-5050.95.3.246. PMID 17641754. Research Blogging.
  55. ↑ Athina Tatsioni, Nikolaos G. Bonitsis, and John P. A. Ioannidis, “Persistence of Contradicted Claims in the Literature,” JAMA 298, no. 21 (December 5, 2007), http://jama.ama-assn.org/cgi/content/abstract/298/21/2517 (accessed December 6, 2007).
  56. ↑ Majumdar S et al. (2001). "Influence of physician specialty on adoption and relinquishment of calcium channel blockers and other treatments for myocardial infarction". J Gen Intern Med 16: 351-9. PMID 11422631.
  57. ↑ Fendrick A et al. (1996). "Differences between generalist and specialist physicians regarding Helicobacter pylori and peptic ulcer disease". Am J Gastroenterol 91: 1544-8. PMID 8759658.
  58. ↑ Lewis C et al. (1991). "The counseling practices of internists". Ann Intern Med 114: 54-8. PMID 1983933.
  59. ↑ Turner B et al.. "Breast cancer screening: effect of physician specialty, practice setting, year of medical school graduation, and sex". Am J Prev Med 8: 78-85. PMID 1599724.
  60. ↑ Laupacis A, Sackett DL, Roberts RS (1988). "An assessment of clinically useful measures of the consequences of treatment". N. Engl. J. Med. 318 (26): 1728–33. PMID 3374545. [e]
  61. ↑ Rembold CM (1998). "Number needed to screen: development of a statistic for disease screening". BMJ 317 (7154): 307–12. PMID 9685274. [e]
  62. ↑ Tengs TO et al (1995). "Five-hundred life-saving interventions and their cost-effectiveness". Risk Anal 15: 369–90. PMID 7604170. [e]
  63. ↑ Maharaj R (2008). "Adding cost to NNT: the COPE statistic". ACP J. Club 148 (1): A8. PMID 18170986. [e]
  64. ↑ Wright JC, Weinstein MC (1998). "Gains in life expectancy from medical interventions--standardizing data on outcomes". N Engl J Med 339: 380–6. PMID 9691106. [e]
  65. ↑ Levels of Evidence. Retrieved on 2007-12-31.
  66. ↑ Stanley K (2007). "Design of randomized controlled trials". Circulation 115: 1164–9. DOI:10.1161/CIRCULATIONAHA.105.594945. PMID 17339574. Research Blogging.
  67. ↑ Michaud G et al. (1998). "Are therapeutic decisions supported by evidence from health care research?". Arch Intern Med 158: 1665–8. PMID 9701101. [e]
  68. ↑ Ellis J et al. (1995). "Inpatient general medicine is evidence based. A-Team, Nuffield Department of Clinical Medicine". Lancet 346: 407–10. PMID 7623571. [e]
  69. ↑ Booth A. Percentage of practice that is evidence based?. Retrieved on 2007-11-15.
  70. ↑ Haynes RB (2006). "Of studies, syntheses, synopses, summaries, and systems: the "5S" evolution of information services for evidence-based healthcare decisions". Evidence-based Medicine 11: 162–4. DOI:10.1136/ebm.11.6.162-a. PMID 17213159. Research Blogging.
  71. ↑ National Library of Medicine. Clinical practice guidelines. Retrieved on 2007-10-19.
  72. ↑ 72.0 72.1 Mendelson D, Carino TV (2005). "Evidence-based medicine in the United States--de rigueur or dream deferred?". Health Affairs (Project Hope) 24: 133–6. DOI:10.1377/hlthaff.24.1.133. PMID 15647224. Research Blogging.
  73. ↑ Hersh W (2002). "Medical informatics education: an alternative pathway for training informationists". JMLA 90: 76–9. PMID 11838463. [e]
  74. ↑ Shearer BS et al. (2002). "Bringing the best of medical librarianship to the patient team". JMLA 90: 22–31. PMID 11838456. [e]
  75. ↑ Straus S et al. (2007). "Misunderstandings, misperceptions, and mistakes". Evidence-based medicine 12 (1): 2–3. DOI:10.1136/ebm.12.1.2-a. PMID 17264255. Research Blogging.
  76. ↑ Straus SE, McAlister FA (2000). "Evidence-based medicine: a commentary on common criticisms". CMAJ 163: 837–41. PMID 11033714. [e]
  77. ↑ Goodman SN (2002). "The mammography dilemma: a crisis for evidence-based medicine?". Ann Intern Med 137: 363–5. PMID 12204023. [e]
  78. ↑ Upshur RE (2000). "Seven characteristics of medical evidence". J Eval Clin Pract 6: 93–7. PMID 10970003. [e]
  79. ↑ Vickers, J (2006). The Problem of Induction (Stanford Encyclopedia of Philosophy). Stanford Encyclopedia of Philosophy. Retrieved on 2007-11-16.
  80. ↑ Grahame-Smith D (1995). "Evidence based medicine: Socratic dissent". BMJ 310: 1126–7. PMID 7742683. [e]
  81. ↑ Formoso G et al. (2001). "Practice guidelines: useful and "participative" method? Survey of Italian physicians by professional setting". Arch Intern Med 161: 2037–42. PMID 11525707. [e]
  82. ↑ Pear, R. A.M.A. and Insurers Clash Over Restrictions on Doctors - New York Times. Retrieved on 2007-11-14.
  83. ↑ Evidence-Based Clinical Guidelines by Milliman Care Guidelines. Retrieved on 2007-11-14.
  84. ↑ Nissimov, R (2000). Cost-cutting guide used by HMOs called `dangerous' / Doctor on UT-Houston Medical School staff sues publisher. Houston Chronicle. Retrieved on 2007-11-14.
  85. ↑ Nissimov, R (2000). Judge tells firm to explain how pediatric rules derived. Houston Chronicle. Retrieved on 2007-11-14.
  86. ↑ Martinez, B (2000). Insurance Health-Care Guidelines Are Assailed for Putting Patients Last. Wall Street Journal.
  87. ↑ Colliver, V (1/07/2002). Lawsuit disputes truth of Kaiser Permanente ads. San Francisco Chronicle. Retrieved on 2007-11-14.
  88. ↑ Warner, S (2/7/2007). The Scientist : State official subpoenas infectious disease group. Retrieved on 2007-11-14.
  89. ↑ Gesensway, D (2007). ACP Observer, January-February 2007 - Experts spar over treatment for 'chronic' Lyme disease. Retrieved on 2007-11-14.
  90. ↑ Djulbegovic B et al. (2000). "Evidentiary challenges to evidence-based medicine". Journal of evaluation in clinical practice 6: 99–109. PMID 10970004. [e]
  91. ↑ Charlton BG. [Book Review: Evidence-based medicine: how to practice and teach EBM by Sackett DL, Richardson WS, Rosenberg W, Haynes RB. http://www.hedweb.com/bgcharlton/journalism/ebm.html] Journal of Evaluation in Clinical Practice. 1997; 3:169-172
  92. ↑ Michelson J (2004). "Critique of (im)pure reason: evidence-based medicine and common sense". J Evaluation Clin Pract 10: 157–61. DOI:10.1111/j.1365-2753.2003.00478.x. PMID 15189382. Research Blogging.
  93. ↑ Smith GC, Pell JP (2003). "Parachute use to prevent death and major trauma related to gravitational challenge: systematic review of randomised controlled trials". BMJ 327: 1459–61. DOI:10.1136/bmj.327.7429.1459. PMID 14684649. Research Blogging.
  94. ↑ Sweeney, Kieran (2006). Complexity in Primary Care: Understanding Its Value. Abingdon: Radcliffe Medical Press. ISBN 1-85775-724-6. Book review
  95. ↑ Holt, Tim A (2004). Complexity for Clinicians. Abingdon: Radcliffe Medical Press. ISBN 1-85775-855-2.  Book review, ACP Journal Club Review
  96. ↑ Fraser SW, Greenhalgh T (2001). "Coping with complexity: educating for capability". BMJ 323 (7316): 799–803. PMID 11588088. [e]
  97. ↑ Anderson RA et al. (2005). "Case study research: the view from complexity science". Qualitative Health Res 15: 669–85. DOI:10.1177/1049732305275208. PMID 15802542. Research Blogging.
  98. ↑ Miller WL et al. (2001). "Practice jazz: understanding variation in family practices using complexity science". J Fam Pract 50: 872–8. PMID 11674890. [e]
  99. ↑ Crabtree BF et al. (2001). "Understanding practice from the ground up". J Fam Pract 50: 881–7. PMID 11674891. [e]
  100. ↑ Sturmberg JP (2007). "Systems and complexity thinking in general practice: part 1 - clinical application". Australian Family Physician 36: 170–3. PMID 17339983. [e]
  101. ↑ 101.0 101.1 Leykum LK et al. (2007). "Organizational interventions employing principles of complexity science have improved outcomes for patients with Type II diabetes". Implementation Science : IS 2: 28. DOI:10.1186/1748-5908-2-28. PMID 17725834. Research Blogging.
  102. ↑ Rhydderch M et al. (2004). "Organisational change theory and the use of indicators in general practice". Quality & Safety in Health Care 13: 213–7. DOI:10.1136/qhc.13.3.213. PMID 15175493. Research Blogging.
  103. ↑ Goldberger AL (1996). "Non-linear dynamics for clinicians: chaos theory, fractals, and complexity at the bedside". Lancet 347: 1312–4. PMID 8622511. [e] Full text at Ebsco
  104. ↑ Lorenz's Model of Convection. Retrieved on 2007-11-21.

See also

Retrieved from "https://citizendium.org/wiki/index.php?title=Evidence-based_medicine&oldid=122880"