PubMed · 5909705
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P A Clark. 1966. Simple data analyser for laboratory statistics.. https://doi.org/10.1136/jcp.19.2.202
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We describe a way to display three-dimensional images by integral imaging using an ordinary projector. We first explain a method that uses a large-aperture converging lens, then we explain the proposed method that uses two sets of lens array. Based on the principle of this new approach, front projection as well as rear projection is possible. Only a proper viewing area can be formed on the optical screen by this method, which improves the brightness of images on the screen. The projector itself does not need an additional optical system. We report on the results of an experiment carried out to confirm the validity of the proposed method.
After many years of study, development and experimentation of open PACS and Image workstation solutions including management of medical data and signals (DPACS project), the research and development at the University of Trieste have recently been directed towards Java-based, IHE compliant and multi-purpose servers and clients. In this paper an original Image-Data Manager/Archiver (O3-DPACS) and a universal Image-Data Display (HDW2) are described. O3-DPACS is also part of a new project called Open Three (O3) Consortium, promoting Open Source adoption in e-health at European and world-wide levels. This project aims to give a contribution to the development of e-health through the study of Healthcare Information Systems and the contemporary proposal of new concepts, designs and solutions for the management of health data in an integrated environment: hospitals, Regional Health Information Organizations and citizens (home-care, mobile-care and ambient assisted living).
BACKGROUND: Clinical governance requires health care professionals to improve standards of care and has resulted in comparison of clinical performance data. The Myocardial Infarction National Audit Project (a UK cardiology dataset) tabulates its performance. However funnel plots are the display method of choice for institutional comparison. We aimed to demonstrate that funnel plots may be derived from MINAP data and allow more meaningful interpretation of data. METHODS: We examined the attainment of National Service Framework standards for all hospitals (n = 230) and all patients (n = 99,133) in the MINAP database between 1st April 2003 and 31st March 2004. We generated funnel plots (with control limits at 3 sigma) of Door to Needle and Call to Needle thrombolysis times, and the use of aspirin, beta-blockers and statins post myocardial infarction. RESULTS: Only 87,427 patients fulfilled criteria for analysis of the use of secondary prevention drugs and 15,111 patients for analysis by Door to Needle and Call to Needle times (163 hospitals achieved the standards for Door to Needle times and 215 were within or above their control limits). One hundred and sixteen hospitals fell outside the 'within 25%' and 'more than 25%' standards for Call to Needle times, but 28 were below the lower control limits. Sixteen hospitals failed to reach the standards for aspirin usage post AMI and 24 remained below the lower control limits. Thirty hospitals were below the lower CL for beta-blocker usage and 49 outside the standard. Statin use was comparable. CONCLUSION: Funnel plots may be applied to a complex dataset and allow visual comparison of data derived from multiple health-care units. Variation is readily identified permitting units to appraise their practices so that effective quality improvement may take place.