Screen LibraryManaging your patients' data in the neonatal and pediatric ICU an introduction to databases and statistical analysis /
With accompanying software! Clinicians manage a lot of data - on assorted bits of paper and in their heads. This book is about better ways to manage and understand large amounts of clinical data. Following on from his ground breaking book, Evaluating the Processes of Neonatal Intensive Care, Joseph...
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| Literature type: | Electronic eBook |
| Language: | English |
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| Online Access: |
http://onlinelibrary.wiley.com/book/10.1002/9780470757451 |
| Summary: |
With accompanying software! Clinicians manage a lot of data - on assorted bits of paper and in their heads. This book is about better ways to manage and understand large amounts of clinical data. Following on from his ground breaking book, Evaluating the Processes of Neonatal Intensive Care, Joseph Schulman has produced this eminently readable guide to patient data analysis. He demystifies the technical methodology to make this crucial aspect of good clinical practice understandable and usable for all health care workers. Computer technology has been relatively slow to transform the daily work of health care, the way it has transformed other professions that work with large amounts of data. Each day, we do our work as we did it the day before, even though current technology offers much better ways. Here are much better ways to document and learn from the daily work of clinical care. Here are the principles of data management and analysis and detailed examples of how to implement them using computer technology. To show you that the knowledge is scalable and useful, and to get you off to a running start, the book includes a complete point of care database software application tailored to the neonatal intensive care unit (NICU). With examples from the NICU and the pediatric ward, this book is aimed specifically at the neonatal and pediatric teams. The accompanying software can be downloaded on to your system or PDA, so that continual record assessment becomes second nature 8211; a skill that will immeasurably improve practice and outcomes for all your patients. |
| Item Description: | "Includes eNICU software for the neonatal intensive care unit, which may be modified for local use or other clinical settings." |
| Carrier Form: | 1 online resource (x, 365 pages) : illustrations |
| Bibliography: | Includes bibliographical references (pages 355-360) and index. |
| ISBN: |
9780470757413 0470757418 9780470757451 0470757450 |
| Index Number: | RJ253 |
| CLC: | R722-05 |
| Contents: | Paper-based patient records -- Computer-based patient records -- Aims of a patient data management process -- Data, information, and knowledge -- Single tables and their limitations -- Multiple tables: where to put the data, relationships among tables, and creating a database -- Relational database management systems: normalization (Codd's rules) -- From data model to database software -- Integrity: anticipating and preventing data accuracy problems -- Queries, forms, and reports -- Programming for greater software control -- Turning ideas into a useful tool: eNICU, point of care database software for the NICU -- Making eNICU serve your own needs -- Single versus multiple users -- Backup and recovery: assuring your data persists -- Security: controlling access and protecting patient confidentiality -- Asking questions of a data set: crafting a conceptual framework and testable hypothesis -- Stata: a software tool to analyze data and produce graphical displays -- Preparing to analyze data -- Variable types -- Measurement values vary: describing their distribution and summarizing them quantitatively -- Data from all versus some: populations and samples -- Estimating population parameters: confidence intervals -- Comparing two sample means and testing a hypothesis -- Type I and type II error in a hypothesis test, power, and sample size -- Comparing proportions: introduction to rates and odds -- Stratifying the analysis of dichotomous outcomes: confounders and effect modifiers; the Mantel-Haenszel method -- Ways to measure and compare the frequency of outcomes, and standardization to compare rates -- Comparing the means of more than two samples -- Assuming little about the data: nonparametric methods of hypothesis testing -- Correlation: measuring the relationship between two continuous variables -- Predicting continuous outcomes: univariate and multivariate linear regression -- Predicting dichotomous outcomes: logistic regression, and receiver operating characteristic -- Predicting outcomes over time: survival analysis -- Choosing variables and hypotheses: practical considerations. |