References and Glossary
What is EBM?
Covell, DG. Uman, CG. Manning, PR. Information needs in office practice: are they being met? Annals of Internal Medicine 103(4):596-599, Oct 1995.
Crowley SD, Owens TA, Schardt CM, Wardell SI, Peterson J, Garrison S, Keitz SA. A Web-based compendium of clinical questions and medical evidence to educate internal medicine residents. Acad Med 78(3):270-4, 2003 Mar.
Osheroff JA. Forsythe DE. Buchanan BG. Bankowitz RA. Blumenfeld BH. Miller RA. Physicians' information needs: analysis of questions posed during clinical teaching. Annals of Internal Medicine 114(7):576-81, 1991 Apr 1.
Sackett, D. Evidence-based Medicine: How to Practice and Teach EBM. 2nd edition. Churchill Livingtone, 2000.
Sackett, D. Evidence-based Medicine - What it is and what it isn't. http://www.cebm.net/ebm_is_isnt.asp 1996.
Sackett DL, Straus SE. Finding and applying evidence during clinical rounds: the "evidence cart". JAMA 280(15):1336-8, 1998 Oct 21.
Tonelli, M.R. The philosophical Limits of Evidence-based Medicine. Academic Medicine 73(12):1234-1240, Dec 1998.
Richardson WS, Wilson MC, Nishikawa J, Hayward RSA. The well-built clinical question: a key to evidence-based decisions. ACP Journal Club. Nov-Dec 1995;123;A12.
Duke University, Medical Center, Ovid tutorial. http://www.mclibrary.duke.edu/training/ovid
PDQ Evidence-Based Principles and Practice, 1999,by Ann McKibbon, is not only an excellent introduction to EBM but also provides search strategies for doing a literature search using MEDLINE, CINAHL Database of Nursing and Allied Health Literature, PsycINFO, and EMBASE/Excerpta MEDICA. Order information from B.C. Decker, Inc. at http://www.bcdecker.com
UNC-Chapel Hill, HSL, Database Searching learning module: http://www.hsl.unc.edu/services/tutorials/srchdbs/splash.htm
Users' Guides to the Medical Literature from JAMA: Note: The full text of the Users' Guide series is available from the Centre for Health Evidence.
Guyatt GH ; Rennie D. Users' guides to the medical literature [editorial]. JAMA 1993 Nov 3; 270(17):2096-7.
Oxman AD ; Sackett DL ; Guyatt GH. Users' guides to the medical literature. I. How to get started. The Evidence-Based Medicine Working Group. JAMA 1993 Nov 3; 270(17):2093-5.
Guyatt GH ; Sackett DL ; Cook DJ. Users' guides to the medical literature. II. How to use an article about therapy or prevention. A. Are the results of the study valid? Evidence-Based Medicine Working Group. JAMA 1993 Dec 1;270(21):2598-601.
Guytt GH ; Sackett DL ; Cook DJ. Users' guides to the medical literature. II. How to use an article about therapy or prevention. B. What were the results and will they help me in caring for my patients? Evidence-Based Medicine Working Group. JAMA 1994 Jan 5; 271(1):59-63.
Jaeschke R ; Guyatt G ; Sackett DL. Users' guides to the medical literature. III. How to use an article about a diagnostic test. A. Are the results of the study valid? Evidence-Based Medicine Working Group. JAMA 1994 Feb 2;271(5):389-91.
Jaeschke R ; Guyatt GH ; Sackett DL. Users' guides to the medical literature. III. How to use an article about a diagnostic test. B. What are the results and will they help me in caring for my patients? The Evidence-Based Medicine Working Group. JAMA 1994 Mar 2; 271(9):703-7.
Levine M ; Walter S ; Lee H ; Haines T ; Holbrook A ; Moyer V. Users' guides to the medical literature. IV. How to use an article about harm. Evidence-Based Medicine Working Group. JAMA 1994 May 25; 271(20):1615-9.
Laupacis A ; Wells G ; Richardson WS ; Tugwell P. Users' guides to the medical literature. V. How to use an article about prognosis. Evidence-Based Medicine Working Group. JAMA 1994 Jul 20; 272(3):234-7.
Absolute Risk Difference is the arithmetic difference between the rates of events in the intervention and control group.
Absolute Risk Reduction refers to the decrease of a bad event as a result of the intervention.
Absolute Benefit Increase refers to the increase of a good event as the result of the intervention.
Confidence Intervals are calculated on the results of the data to show the strength or weakness of the evidence. A 95%CI[range] means that if you were to repeat the same clinical trial a hundred times you can be 95% sure that the data would fall within the calculated range.
Intention to treat analysis of patients with the treatment group to which they were originally assigned, regardless of whether or not they actually received the treatment or not.
Likelihood Ratio indicates the likelihood that a given test result would be expected in a patient with the target disorder compared to the likelihood that the same result would be expected in a patient without that disorder.
Numbers Needed to Treat (NNT) the number of patients who need to be treated to prevent one bad outcome. The NNT is a useful number when you want to compare the costs and adverse effects of a treatment with its benefits.
Odds Ratio describes the odds of an experimental patient suffering an adverse event relative to a control patient.
P Value refers to the probability that any particular outcome would have arisen by chance. (The smaller the P value the less likely the data was by chance.) Standard scientific practice, usually deems a P value of less than 1 in 20 (expressed as P=.05) as "statistically significant". The smaller the P value the higher the significance. A P value of P=.01 ( less than 1 in 100) is considered "statistically highly significant".
Predictive Value of tests: In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the positive Predictive Value; whereas, the Negative Predictive Value is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.
Relative Risk is the risk of developing a disease in the exposed group divided by the risk of developing the disease in the unexposed group.
Relative Risk Reduction is the proportional difference between the rates of events in the control group and the intervention group. Relative Risk Reduction is usually a larger number than the Absolute Risk Difference and therefore tends to exaggerate the difference.
Sensitivity measures the proportion of patients with the disease who also test positive for the disease.
Specificity measures the proportion of patients without the disease who also test negative for the disease.
A good test is both highly sensitive and highly specific.
|See also the Glossary of Terms from Evidence Based Emergency Medicine and the New York Academy of Medicine|
This is the end of the tutorial. Thank you and good luck!