Alternative definitions

“When the facts change, I change my mind. What do you do?” asked Professor Michael Oliver at a presentation held in Stockholm on 6 June 1996. This is what readers of the New England Journal of Medicine were told in an advertisement for the cholesterol lowering drug simvastatin during the winter of 1996-7. Oliver's statement is accompanied in the advertisement by the following facts: “In post MI and angina patients with cholesterol levels in the range of 5.5 to 8.0 mmol/l (212-309 mg/dl). Proven to reduce the risk of total mortality by 30% (P=0.0003),1 coronary mortality by 42% (P=0.00001).2 “These facts are followed by another statement from Oliver et al: “Lower patients' cholesterol now.”3 This second statement represents Oliver's change of mind since he, in 1992, stated his “Doubts about preventing coronary heart disease: multiple interventions in middle aged men may do more harm than good,”4 which contributed to the controversy over the importance of lowering serum cholesterol concentrations.5 In a similar advertisement, readers of the Lancet have been informed of the same facts, but unaccompanied by Professor Oliver's statements. Instead, these readers are provided with more facts: “Projected 6-year benefits in 1000 patients with coronary heart disease (CHD). 35 lives saved, 67 MIs prevented, 59 procedures avoided.” At first sight, a negative response to Oliver's rhetorical question may seem perverse or prejudiced. On second thoughts, given its rhetorical nature and considering that it is being used in a commercial presentation, you might suspect that there is something more to it. Indeed there is, and the aim of this article is to shed some light on the presentation of facts from clinical trials like the Scandinavian simvastatin survival study (4S) and the West of Scotland coronary prevention study (WOSCOPS).6 Facts from WOSCOPS were presented …

[1]  C. Aydin,et al.  Evaluating Health Care Information Systems: Methods and Applications , 1993 .

[2]  D. Sackett,et al.  The number needed to treat: a clinically useful measure of treatment effect , 1995, BMJ.

[3]  J C Wyatt,et al.  Hospital information management: the need for clinical leadership , 1995, BMJ.

[4]  J. Stengård,et al.  Antibodies to glutamic acid decarboxylase as predictors of insulin-dependent diabetes mellitus before clinical onset of disease , 1994, The Lancet.

[5]  J. Wyatt,et al.  Clinical data systems, part 1: data and medical records , 1994, The Lancet.

[6]  J. Fox,et al.  Evaluation of computer support for prescribing (CAPSULE) using simulated cases , 1997, BMJ.

[7]  P. Macfarlane,et al.  Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia , 1995 .

[8]  T. Fahey,et al.  Evidence based purchasing: understanding results of clinical trials and systematic reviews , 1995, BMJ.

[9]  C D Naylor,et al.  Measured Enthusiasm: Does the Method of Reporting Trial Results Alter Perceptions of Therapeutic Effectiveness? , 1992, Annals of Internal Medicine.

[10]  Chris McManus Engineering quality in health care , 1996 .

[11]  J. Kjekshus,et al.  Reducing the risk of coronary events: evidence from the Scandinavian Simvastatin Survival Study (4S). , 1995, The American journal of cardiology.

[12]  E. M. S. J. Van Gennip,et al.  Assessment and evaluation of information technogies in medicine , 1995 .

[13]  E. B. Steen,et al.  The Computer-Based Patient Record: An Essential Technology for Health Care , 1992, Annals of Internal Medicine.

[14]  A. Maseri Inflammation, atherosclerosis, and ischemic events -- exploring the hidden side of the moon. , 1997, The New England journal of medicine.

[15]  K. Calman,et al.  Cancer: science and society and the communication of risk , 1996, BMJ.

[16]  T. Walley,et al.  Same information, different decisions: the influence of evidence on the management of hypertension in the elderly. , 1996, The British journal of general practice : the journal of the Royal College of General Practitioners.

[17]  T. Lancet,et al.  West of Scotland Coronary Prevention Study: identification of high-risk groups and comparison with other cardiovascular intervention trials , 1996, The Lancet.

[18]  Juhani Iivari,et al.  Why do individuals use computer technology? A Finnish case study , 1995, Inf. Manag..

[19]  P. Poole‐Wilson,et al.  Lower patients' cholesterol now , 1995, BMJ.

[20]  G. Lip,et al.  Can we treat coronary artery disease with antibiotics? , 1997, The Lancet.

[21]  D. Lupton 'The Great Debate About Cholesterol': Medical Controversy and the News Media , 1994 .

[22]  Roberts Wc The underused miracle drugs: the statin drugs are to atherosclerosis what penicillin was to infectious disease. , 1996 .

[23]  J. Danesh,et al.  Chronic infections and coronary heart disease: is there a link? , 1997, The Lancet.

[24]  Jonathan M. Teich,et al.  Research Paper: Implementation of Physician Order Entry: User Satisfaction and Self-Reported usage Patterns , 1996, J. Am. Medical Informatics Assoc..

[25]  Jonathan Mant,et al.  Detecting differences in quality of care: the sensitivity of measures of process and outcome in treating acute myocardial infarction , 1995, BMJ.

[26]  L J Donaldson,et al.  From black bag to black box: will computers improve the NHS? , 1996, BMJ.

[27]  Charles Young,et al.  A randomized controlled trial of a computer-based physician workstation in an outpatient setting: implementation barriers to outcome evaluation. , 1996, Journal of the American Medical Informatics Association : JAMIA.

[28]  P. Macfarlane,et al.  West of Scotland Coronary Prevention Study: Identification of high-risk groups and comparison with other cardiovascular intervention trials , 1996 .

[29]  C Lock,et al.  What value do computers provide to NHS hospitals? , 1996, British medical journal.

[30]  Paul Mongerson Viewpoint: A Patient's Perspective of Medical Informatics , 1995, J. Am. Medical Informatics Assoc..

[31]  M S Leaning,et al.  The new information management and technology strategy of the NHS. , 1993, BMJ.

[32]  R. Haynes,et al.  Effects of Computer-based Clinical Decision Support Systems on Clinician Performance and Patient Outcome: A Critical Appraisal of Research , 1994, Annals of Internal Medicine.

[33]  Baruch Fischhoff,et al.  Judgment under uncertainty: Facts versus fears: Understanding perceived risk , 1982 .

[34]  J. Wise Computer prescribing scheme gets green light , 1996 .

[35]  R M Arnold,et al.  Absolutely relative: how research results are summarized can affect treatment decisions. , 1992, The American journal of medicine.

[36]  P Mongerson,et al.  A patient's perspective of medical informatics. , 1995, Journal of the American Medical Informatics Association : JAMIA.

[37]  D. Spiegelhalter,et al.  Evaluating medical expert systems: what to test and how? , 1990, Medical informatics = Medecine et informatique.

[38]  M. Oliver Doubts about preventing coronary heart disease. , 1992, BMJ.

[39]  P. Ridker,et al.  Inflammation, aspirin, and the risk of cardiovascular disease in apparently healthy men. , 1997, The New England journal of medicine.

[40]  Charles P. Friedman,et al.  Evaluation Methods in Medical Informatics , 1997, Computers and Medicine.

[41]  K. Gyr,et al.  Influence of method of reporting study results on decision of physicians to prescribe drugs to lower cholesterol concentration , 1994, BMJ.

[42]  D. K. Donker Assessment and evaluation of information technologies in medicine , 1996 .

[43]  J. Wyatt Decision support systems. , 2000, Journal of the Royal Society of Medicine.

[44]  H A Heathfield,et al.  Philosophies for the Design and Development of Clinical Decision-Support Systems , 1993, Methods of Information in Medicine.

[45]  Bonnie Kaplan,et al.  Information technology and three studies of clinical work , 1995, SIGB.