Managing your patients' data in the neonatal and pediatric ICU
Subtitle: an introduction to databases and statistical analysis
By: Joseph Schulman.
Publisher: Blackwell Pub.; Blackwell  Publishing
Published: 2006
Place of publication: Malden, Mass
Language: eng
ISBN-13: 9780727918703
Subjects: Neonatology -- Databases; Neonatology -- Statistical methods; Medical records -- Data processing; Database Management Systems -- Infant, Newborn; Medical Records -- Infant, Newborn; Models, Statistical; Neonatology -- methods
Notes: Includes bibliographical references.
"Includes eNICU software for the neonatal intensive care unit, which may be modified for local use or other clinical settings."
Table of contents: title: Paper-based patient records; title: Computer-based patient records; title: Aims of a patient data management process; title: Data, information, and knowledge; title: Single tables and their limitations; title: Multiple tables: where to put the data; relationships among tables; creating a database; title: Relational database management systems: normalization; Codd's rules; title: From data model to database software; title: Integrity: anticipating and preventing problems with data accuracy; title: Queries, forms, and reports; title: Programming for greater software control; title: Turning ideas into a useful tool: eNICU point of care database software for the NICU; title: Making eNICU serve your own needs; title: Single vs. multiple user; title: Backup: assuring your data persists; title: Security: controlling access and protecting patient confidentiality; title: Crafting a conceptual framework and testable hypothesis; title: Stata: a software tool to analyze data and produce graphical displays; title: Preparing to analyze data; title: Variable types; title: Measurement values vary: describing their distribution and summarizing them quantitatively; title: Data from all or some: populations and samples; title: Estimating population parameters; confidence intervals; title: Comparing two sample means; statistical significance and clinical significance; title: Type I and type II error in a hypothesis test; power; sample size; title: Comparing proportions; introduction to rates and odds; title: Stratifying the analysis of dichotomous outcomes; confounders and effect modifiers; multiple 2 x 2 tables: the Mantel-Haenszel method; title: Ways to measure and compare the frequency of outcomes; standardization; title: Comparing the means of more than two samples; title: Assuming little about the data: non-parametric methods of hypothesis testing; title: Correlation: measuring the relationship between two continuous variables; title: Predicting continuous outcomes: univariate and multivariate linear regression; title: Predicting dichotomous outcomes: logistic regression; receiver operating characteristic (ROC); title: Predicting outcomes over time: survival analysis; title: Choosing variables and hypotheses: practical considerations.