Relational database design.

D Wesley

Home/Archive/PubMed

PubMed · 15912904

Relational database design.

D Wesley

View original source ↗Export metadata ↓

Abstract

Relational databases are the predominant method for storing repetitive data in computers because they allow efficient and flexible storage of that data. While medical directors and underwriters are more likely to use a spreadsheet than a database program to analyze their business, the data they wish to study are often stored in corporate databases. Or the data may be complex enough to require being keyed into or downloaded into a personal computer (PC) database program for storage, even if the data are then output to a spread-sheet for numerical analysis. In many circumstances, one can benefit from an understanding of efficient database design. After a brief overview, the reader is led step-by-step through a practical explanation of database design, from a flat file to a relational model.

Explore related subjects

Database Management Systems Humans Information Storage and Retrieval Software Design Journal Article Review

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

D Wesley. 2000. Relational database design.. https://pubmed.ncbi.nlm.nih.gov/15912904/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2006

Development and validation of queries using structured query language (SQL) to determine the utilization of comparison imaging in radiology reports stored on PACS.

The purpose of this research was to develop queries that quantify the utilization of comparison imaging in free-text radiology reports. The queries searched for common phrases that indicate whether comparison imaging was utilized, not available, or not mentioned. The queries were iteratively refined and tested on random samples of 100 reports with human review as a reference standard until the precision and recall of the queries did not improve significantly between iterations. Then, query accuracy was assessed on a new random sample of 200 reports. Overall accuracy of the queries was 95.6%. The queries were then applied to a database of 1.8 million reports. Comparisons were made to prior images in 38.69% of the reports (693,955/1,793,754), were unavailable in 18.79% (337,028/1,793,754), and were not mentioned in 42.52% (762,771/1,793,754). The results show that queries of text reports can achieve greater than 95% accuracy in determining the utilization of prior images.

Database Management Systems↗

PubMed2006

Developing optimal search strategies for retrieving clinically relevant qualitative studies in EMBASE.

Qualitative researchers address many issues relevant to patient health care. Their studies appear in an array of journals, making literature searching difficult. Large databases such as EMBASE provide a means of retrieving qualitative research, but these studies represent only a minuscule fraction of published articles, making electronic retrieval problematic. Little work has been done on developing search strategies for the detection of qualitative studies. The objective of this study was to develop optimal search strategies to retrieve qualitative studies in EMBASE for the 2000 publishing year. The authors conducted an analytic survey, comparing hand searches of journals with retrievals from EMBASE for candidate search terms and combinations. Search strategies reached peak sensitivities at 94.2% and peak specificities of 99.7%. Combining search terms to optimize the combination of sensitivity and specificity resulted in values over 89% for both. The authors identified search strategies with high performance for retrieving qualitative studies in EMBASE.

Database Management Systems↗

PubMed2005

Database management systems for process safety.

Several elements of the process safety management regulation (PSM) require tracking and documentation of actions; process hazard analyses, management of change, process safety information, operating procedures, training, contractor safety programs, pre-startup safety reviews, incident investigations, emergency planning, and compliance audits. These elements can result in hundreds of actions annually that require actions. This tracking and documentation commonly is a failing identified in compliance audits, and is difficult to manage through action lists, spreadsheets, or other tools that are comfortably manipulated by plant personnel. This paper discusses the recent implementation of a database management system at a chemical plant and chronicles the improvements accomplished through the introduction of a customized system. The system as implemented modeled the normal plant workflows, and provided simple, recognizable user interfaces for ease of use.

Database Management Systems↗