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The Hands-on Guide to Data Interpretation (PDF eBook)


The Hands-on Guide to Data Interpretation (PDF eBook)

eBook by Abraham, Sasha/Kulkarni, Kunal/Madhu, Rashmi

The Hands-on Guide to Data Interpretation (PDF eBook)

£33.95

ISBN:
9781444320381
Publication Date:
03 Aug 2010
Publisher:
Wiley
Imprint:
Wiley-Blackwell
Pages:
264 pages
Format:
eBook
For delivery:
Download available
The Hands-on Guide to Data Interpretation (PDF eBook)

Description

Not sure how to interpret the wealth of data in front of you? Do you lack confidence in applying the results of investigations to your clinical decision making? Then this pocket-sized, quick reference guide to data interpretation may be just right for you. The Hands-on Guide to Data Interpretation is the perfect companion for students, doctors, nurses and other health care professionals who need a reference guide on the ward or when preparing for exams. It focuses on the most common investigations and tests encountered in clinical practice, providing concise summaries of how to confidently interpret investigative findings and, most importantly, how to apply this to clinical decision making. The benefits of this book include: An overview of the normal ranges of test results, followed by a consideration of the differential diagnoses suggested by variance from these values Arranged by system to allow quick access to the key investigations encountered in different specialties A summary 'patient data' chapter to bring the different specialties together, providing an overview to completing investigation documentation and charts Summary table and bullet point format, with a full index, to aid rapid retrieval of information Each chapter reviewed by a specialist to ensure an accurate, practical approach to data interpretation Take the stress out of data interpretation with The Hands-on Guide!

Contents

Preface. Acknowledgements. Abbreviations. 1. Normal Ranges. 2. Cardiovascular. 3. Respiratory. 4. Gastrointestinal. 5. Endocrinology. 6. Renal. 7. Neurology. 8. Haematology. 9. Rheumatology. 10. Obstetrics & Gynaecology. 11. Ophthalmology. 12. Oncology. 13. Microbiology. 14. Genetics. 15. Imaging. 16. Patient Data.

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