SYMPOSIUM: DATA ANALYSIS AND TREND IDENTIFICATION IN THE INTENSIVE CARE UNIT
Year : 2017 | Volume
: 3 | Issue : 3 | Page : 123--128
Republication: Application of financial analysis techniques to clinical laboratory data – A novel method of trend interpretation in the Intensive Care Unit
Stanislaw P Stawicki
OPUS 12 Foundation, Bethlehem, PA, USA
Modern critical care medicine depends on constant flow of massive amounts of information. This information has limited usefulness unless it is appropriately gathered, stored, displayed, and interpreted. Despite such wealth of data in the modern Intensive Care Units (ICUs), intensivists often rely on very fragmentary “snapshot” information to make important clinical decisions. In an attempt to improve the understanding of clinical data trends, application of financial analysis (FA) methods to clinical laboratory data samples were performed. Three randomly chosen, anonymized laboratory datasets of patients who spent at least 30 days in the ICU were retrospectively examined. Regularly obtained laboratory values were retrieved and recorded for each patient. Variables examined included white blood cell count, hemoglobin level, platelet count, and blood glucose levels. These variables were then entered into specialized FA software and subjected to computer-based processing. Trends in the recorded data were examined using (1) the stochastic oscillator, (2) the Relative Strength Index tool, (3) price envelope analysis, and (4) moving average analysis. All clinical laboratory parameter analyses demonstrated that laboratory data could be successfully “trended” using FA techniques. Not only were the laboratory data clearly readable and transparent when displayed in FA fashion but also some trends that were not apparent on “gross” inspection of the numeric data became very apparent after FA. Much like with financial patterns and vital sign data, trends noted within laboratory parameters appeared to be more significant when more than one indicator identified or “confirmed” them, utilizing the concept of a confirmatory variable. Laboratory data, much like financial and vital sign data, were subject to trend reversals. Such reversals in laboratory parameters appeared to follow patterns similar to those followed by financial vehicles and markets. This report demonstrates that laboratory data can be subjected to the same manipulations as financial market data. Furthermore, FA tools appear to provide the interpreter with means to define, confirm, and possibly predict trends and trend reversals. Assumptions for the use of FA methods in biologic parameter analysis are also presented.
The following core competencies are addressed in this article: Medical knowledge, Practice-based learning and improvement, Systems-based practice.
Republished with permission from: Stawicki SP. Application of financial analysis techniques to clinical laboratory data: A novel method of trend interpretation in the Intensive Care Unit. OPUS 12 Scientist. 2007;1:1-4.
Stanislaw P Stawicki
Department of Research and Innovation, St. Luke's University Health Network, EW2 Research Administration, 801 Ostrum Street, Bethlehem, PA 18015
|How to cite this article:|
Stawicki SP. Republication: Application of financial analysis techniques to clinical laboratory data – A novel method of trend interpretation in the Intensive Care Unit.Int J Acad Med 2017;3:123-128
|How to cite this URL:|
Stawicki SP. Republication: Application of financial analysis techniques to clinical laboratory data – A novel method of trend interpretation in the Intensive Care Unit. Int J Acad Med [serial online] 2017 [cited 2020 Nov 28 ];3:123-128
Available from: https://www.ijam-web.org/article.asp?issn=2455-5568;year=2017;volume=3;issue=3;spage=123;epage=128;aulast=Stawicki;type=0