An edition of Managing your patients' data in the neonatal and pediatric ICU
(2006)
Managing your patients' data in the neonatal and pediatric ICU
an introduction to databases and statistical analysis
by Joseph Schulman
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Managing your patients' data in the neonatal and pediatric ICU: an introduction to databases and statistical analysis
2006, Blackwell Pub., Blackwell Publishing
in English
0727918702 9780727918703
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Book Details
Table of 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; creating a database
Relational database management systems: normalization; Codd's rules
From data model to database software
Integrity: anticipating and preventing problems with data accuracy
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 vs. multiple user
Backup: assuring your data persists
Security: controlling access and protecting patient confidentiality
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 or some: populations and samples
Estimating population parameters; confidence intervals
Comparing two sample means; statistical significance and clinical significance
Type I and type II error in a hypothesis test; power; sample size
Comparing proportions; introduction to rates and odds
Stratifying the analysis of dichotomous outcomes; confounders and effect modifiers; multiple 2 x 2 tables: the Mantel-Haenszel method
Ways to measure and compare the frequency of outcomes; standardization
Comparing the means of more than two samples
Assuming little about the data: non-parametric 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; receiver operating characteristic (ROC)
Predicting outcomes over time: survival analysis
Choosing variables and hypotheses: practical considerations.
Edition Notes
Includes bibliographical references.
"Includes eNICU software for the neonatal intensive care unit, which may be modified for local use or other clinical settings."
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- Created April 1, 2008
- 12 revisions
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| May 4, 2023 | Edited by ImportBot | import existing book |
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