Build a data warehouse to make IT investments pay off.
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Managed care organizations have a wealth of administrative, claims and clinical data available to them--data that could pinpoint patients who could benefit from cost-effective disease management programs. Health plans that have such efforts offer advice on how to home in on the best data.
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As part of preliminary studies for the development of a digital library, we have studied the possibility of using the co-occurrence of MeSH terms in MEDLINE citations associated with the search strategies optimal for evidence-based medicine to automate construction of a knowledge base. We use the UMLS semantic types in order to analyze search results to determine which semantic types are most relevant for different types of questions (etiology, diagnosis, therapy, and prognosis). The automated process generated a large amount of information. Seven to eight percent of the semantic pairs generated in each clinical task group co-occur significantly more often than can be accounted for by chance. A pilot study showed good specificity and sensitivity for the intended purposes of this project in all groups.
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BACKGROUND: Clinical information system (CIS) use is likely to evoke information needs, yet information resources use during CIS use has not been studied. METHODS: We used CIS log files and a survey to characterize clinicians' use of resources and infobuttons (context-sensitive links from a CIS to specific resources) while using a CIS. RESULTS: We examined 38,763 uses of resources and infobuttons by 2,607 users to identify specific sources and contexts (CIS functions) in which they used them. Laboratory results review was the most frequent context and Micromedex was the most popular resource. Differences in resource use were related to context and user type. The survey confirmed that resources and infobuttons were perceived as useful for patient-specific questions while using a CIS. CONCLUSIONS: Understanding context- and user-type-specific information needs can guide the development of infobuttons for use in a CIS.
Central Utah Multi-Specialty Clinic, a 59-physician group with practices in nine locations treating 200,000 active patients, documented the economic impact of implementing an electronic medical record. During the one-year period of the study, the clinic experienced direct reductions in spending and increases in revenue of more than $952,000 compared with the prior year, and anticipates cumulative savings of more than $8.2 million over the next five years.
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Blood banks have a need for efficient, long-term storage of records and quick access to the stored information. Database management systems make it easy to retrieve and review large amounts of data. They provide such functions as data entry, sorting capability, search and find capacity, report production, calculation and graphic capacities, programming, and the relating of fields in one file to those in another file. Privately developed programs can be shared by blood banks. A program for managing an inventory of frozen blood units is offered in this paper.
Computed radiology is a radiographic imaging technology that generates a conventional radiographic image in digital form. The image can be recorded on a laser sensitive film or archived to a digital storage device and displayed on a video monitor. This study was performed to evaluate the adequacy of reporting digitised images directly from the workstation. The test set consisted of portable chest images of 55 patients from the cardiothoracic intensive care unit. Normal structures and nine abnormalities were pre-selected for analysis. The radiographs and images on the video display were reviewed on two separate occasions, six months apart by two independent readers. No clinical details were supplied and the intraobserver and interobserver agreement were assessed using Kappa statistics. The overall results indicated that direct reporting from the workstation was as reliable as reporting from the laser printed copies.
BACKGROUND: Array comparative genomic hybridization (CGH) is a technique which detects copy number differences in DNA segments. Complete sequencing of the human genome and the development of an array representing a tiling set of tens of thousands of DNA segments spanning the entire human genome has made high resolution copy number analysis throughout the genome possible. Since array CGH provides signal ratio for each DNA segment, visualization would require the reassembly of individual data points into chromosome profiles. RESULTS: We have developed a visualization tool for displaying whole genome array CGH data in the context of chromosomal location. SeeGH is an application that translates spot signal ratio data from array CGH experiments to displays of high resolution chromosome profiles. Data is imported from a simple tab delimited text file obtained from standard microarray image analysis software. SeeGH processes the signal ratio data and graphically displays it in a conventional CGH karyotype diagram with the added features of magnification and DNA segment annotation. In this process, SeeGH imports the data into a database, calculates the average ratio and standard deviation for each replicate spot, and links them to chromosome regions for graphical display. Once the data is displayed, users have the option of hiding or flagging DNA segments based on user defined criteria, and retrieve annotation information such as clone name, NCBI sequence accession number, ratio, base pair position on the chromosome, and standard deviation. CONCLUSIONS: SeeGH represents a novel software tool used to view and analyze array CGH data. The software gives users the ability to view the data in an overall genomic view as well as magnify specific chromosomal regions facilitating the precise localization of genetic alterations. SeeGH is easily installed and runs on Microsoft Windows 2000 or later environments.
Data storage and data coordination are important aspects of project design and execution. Pyrosequencing technology allows thousands of data-points to be collected per day. Consequently, a consistent and reliable method of data input and storage is vital. This chapter discusses the strengths and weaknesses of data storage systems.