Improved methods of clinical data collection, storage, and processing are changing the way critical care practitioners examine and utilize the wealth of patient-related information available in the modern intensive care unit (ICU). The author of this report previously outlined general methods and principles of a proposed new biomedical parameter analysis system based on well-established financial analysis (FA) methods. The new system helps to define, confirm, and potentially predict trends and trend reversals in a number of traditional biomedical variables (vital signs, laboratory parameters, various catheter-derived pressure measurements, oximetry, temperature, and input/output variables). In order to examine the behavior of FA parameters and indicators across different temporal scales (i.e., minutes, hours, days, and weeks) the author analyzed trends in various biomedical parameters using different time scales and a standardized set of FA techniques, including: (1) the Stochastic Oscillator (SO), (2) the Relative Strength Index (RSI) tool, (3) Moving Average (MA), (4) Moving Average Convergence- Divergence (MACD); and (5) Price Envelope (PE) analysis. Randomly chosen and anonymized laboratory, urinary output, hemodynamic and intracranial pressure datasets of patients who spent at least 21 days in the ICU were retrospectively examined. Variables were entered into specialized FA software (MetaStock, Equis International, Salt Lake City, Utah, USA) and subjected to computerized processing methods. Analyses of the above clinical parameters demonstrate that laboratory, input/output, oximetry, and transduced pressure-based data can be successfully ‘trended’ using simple FA techniques. The data were easy to examine when displayed in FA fashion. In addition, some trends that were not easily apparent on examination of raw numeric data or basic non-FA graphs became more apparent after the application of FA methods. These findings suggest that biomedical parameters can be subjected to the same manipulations as financial market data. In addition, FA tools appear to provide the interpreting physician with means to examine biomedical parameters across different temporal scales and resolutions (from minutes to weeks per each measurement epoch). In fact, biomedical parameters tend to display similar trends regardless of whether the data is collected on the scale of minutes, hours, days, weeks, or months.

Citation: Stawicki SP. Financial analysis techniques in clinical practice: From 'micro' to 'macro'. OPUS 12 Scientist 2008;2(3):3-9.

Keywords: Wall Street, Technical indicators, Trending methods for stocks and bonds, Biomedical parameters, Vital signs, Laboratory findings, Pressure-derived parameters, Financial analysis software, Intensive care unit, Directions for future research.

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