For data managers, laboratory data can prove to be a frustrating, if not bewildering, subject with unrivalled subtleties and pitfalls. This book sets out to document many of these problems and give the reader a better understanding of his/her data. This book is about laboratory data as data. It seeks to give an explanation for what is going on and why the laboratories supply the information in the way they do. It also tries to highlight the questions that data managers should look for and to point out what is not as erroneous as might be expected. It is intended for the non-expert in laboratory data. The hope is that she/he will find within the book answers to the questions that arise during handling of the data such as “Is this unit possible?”, “could this result be right?” or “Should there be a normal range for this test?”. Such a book as this can not hope to make its reader into a clinical expert. There is little coverage of the clinical significance of the tests. As far as possible laboratory terminology is explained. There are also· definitions to units and to a number of calculated values but no attempt to supply a list of normal range values. These vary greatly between labs and any single list will at best only be a guide. The book is set out in a number of sections to try and give a pattern to the issues involved. There is an extensive index to enable the user to identify specific problems or specific tests. Hopefully this will add greatly to the book’s usefulness as a source of reference. There is not a section on data cleaning as such. There are many different ways of checking laboratory data and the method selected will depend upon the systems used and the flow of data. This booklet will provide useful reference for data managers trying to interpret the checks that they have done. Likewise reporting receives only scant mention. The design of reports depends very much on the message you want to convey. There are thousands of tests that can be performed. Many are very esoteric and useful only in highly specialised situations. There is no intention this for booklet to mention them all. We will focus on the tests that are used most commonly but in many cases the points discussed will be of general relevance to all tests.
For data managers, laboratory data can prove to be a frustrating, if not bewildering, subject with unrivalled subtleties and pitfalls. This book sets out to document many of these problems and give the reader a better understanding of his/her data.
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