Evidence-Based Diagnosis
1
MEDIA REVIEWS EVIDENCE-BASED DIAGNOSIS. By Thomas B. Newman, Michael A. Kohn. New York: Cambridge University Press, 2009; 295 pp; $49.99 (softcover). Evidence-Based Diagnosis is a tool provided to physi- cians to aid in understanding diagnostic, screening, and prognostic tests in clinical medicine. This is a new member of the group of publications focusing on evi- dence-based medicine in clinical practice. The authors state that they restrained from packing this resource full of mathematics and focused instead on practical applicability. This book is organized into category of tests. The first group of chapters introduces definitions. The next collection of chapters introduces various diagnostic tests: interobserver agreement, measurement errors, dichotomous tests, continuous tests, screening tests, prognostic tests, and decision rules. The last section of chapters explains treatment effects as a result of randomized and nonrandomized trials, p-values, and confidence intervals. Each chapter starts with a general introduction, followed by sections explaining each test. To enhance the text, large tables and diagrams are inserted to define terms, give examples of concepts, and provide summaries. Each chapter concludes with exercises for the reader to practice the concepts introduced. The pretest and posttest concept is used in each chapter. The amazing part is that the authors explain complex concepts with minimal math, to avoid frustrat- ing the novice clinician. For example, the first chapter talks about interobserver agreement using kappa measurement. In the next sections, the authors define the term, describe how the formula is calculated and derived, and then provide examples of its use and explain its meaning. To meet their objectives, the chap- ter has tables and figures highlighting the text. For those with a basic level of knowledge, this is an excellent resource to enhance and expand your under- standing of diagnostic testing and its applications in tri- als. The book’s greatest weakness is that it strives to keep the math aspect to a minimum; thus, more advanced readers may find this too basic. In summary, Newman and Kohn’s edition of Evidence- Based Diagnosis fills a nice niche for understanding and applying evidence in clinical medicine for the novice. Abhinav Chandra ([email protected]) Division of Emergency Medicine, Duke University Medical Center, Durham, NC ª 2010 by the Society for Academic Emergency Medicine ISSN 1069–6563 doi:10.1111/j.1553-2712.2010.00770.x PII ISSN 1069–6563583 e51
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Transcript of Evidence-Based Diagnosis
MEDIA REVIEWS
EVIDENCE-BASED DIAGNOSIS.By Thomas B. Newman, Michael A. Kohn.New York: Cambridge University Press, 2009; 295 pp;$49.99 (softcover).
Evidence-Based Diagnosis is a tool provided to physi-cians to aid in understanding diagnostic, screening, andprognostic tests in clinical medicine. This is a newmember of the group of publications focusing on evi-dence-based medicine in clinical practice. The authorsstate that they restrained from packing this resourcefull of mathematics and focused instead on practicalapplicability.
This book is organized into category of tests. The firstgroup of chapters introduces definitions. The nextcollection of chapters introduces various diagnostictests: interobserver agreement, measurement errors,dichotomous tests, continuous tests, screening tests,prognostic tests, and decision rules. The last section ofchapters explains treatment effects as a result ofrandomized and nonrandomized trials, p-values, andconfidence intervals. Each chapter starts with a generalintroduction, followed by sections explaining each test.To enhance the text, large tables and diagrams areinserted to define terms, give examples of concepts,and provide summaries. Each chapter concludes
with exercises for the reader to practice the conceptsintroduced.
The pretest and posttest concept is used in eachchapter. The amazing part is that the authors explaincomplex concepts with minimal math, to avoid frustrat-ing the novice clinician. For example, the first chaptertalks about interobserver agreement using kappameasurement. In the next sections, the authors definethe term, describe how the formula is calculated andderived, and then provide examples of its use andexplain its meaning. To meet their objectives, the chap-ter has tables and figures highlighting the text.
For those with a basic level of knowledge, this is anexcellent resource to enhance and expand your under-standing of diagnostic testing and its applications in tri-als. The book’s greatest weakness is that it strives tokeep the math aspect to a minimum; thus, moreadvanced readers may find this too basic.
In summary, Newman and Kohn’s edition of Evidence-Based Diagnosis fills a nice niche for understanding andapplying evidence in clinical medicine for the novice.
Abhinav Chandra([email protected])Division of Emergency Medicine, Duke UniversityMedical Center, Durham, NC
ª 2010 by the Society for Academic Emergency Medicine ISSN 1069–6563doi:10.1111/j.1553-2712.2010.00770.x PII ISSN 1069–6563583 e51
