Computers in the ICU: why? What? And so what?
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Electronic Data Processing↗
Biomedical subjects
S M Huff
Publications and source records attributed to S M Huff.
Pick from thousands: a collaborative processing model for coded data entry.
Methods for optimizing coded data entry in clinical systems are a frequent topic of system design. We have developed a new mechanism for this type of data entry that we call "Pick From Thousands" (PFT). It combines several known methods, including menu selection, keyword entry, and initial character matching, but adds a new string matching algorithm. The PFT method is more selective than initial character matching for a given number of keystrokes if entries in the coded list have more than one word. Collaborative processing between a PC workstation and the central HELP system computer is used to optimize ease of maintenance and increase the flexibility and performance of the system.
Algorithms↗
Integration of a stand-alone expert system with a hospital information system.
A stand-alone PC expert system for evaluating the appropriateness of inpatient admissions has been integrated with an existing hospital information system. The expert system supports preadmission screening for appropriateness of inpatient admissions. The HIS provides extensive clinical data in a coded electronic form, permitting high-level decision support. The integrated system was developed for a 20 week randomized clinical trial to evaluate the effects of preadmission screening on inappropriate inpatient admissions. Three factors of the integration are considered: programmatic integration of the expert system, seamless presentation of mixed platform applications, and integration of coded data from the stand-alone application into the HIS data structure.
Evaluation Studies as Topic↗
The development of a virtual database to provide on-line access to a large archive of clinical data.
The archival database of the HELP Hospital Information System at LDS Hospital is too large to be stored on line. The archival data are important for clinical and research applications. Demountable disk packs have been used to store the archival database. This method of storage has four significant disadvantages. A virtual database was developed to overcome the limitations of this data-management scheme. This virtual database enables the transparent use of appropriate low-cost network-based storage technology to provide on-line availability of the entire archive of clinical data. The virtual database successfully resolves the problems associated with disk packs, and opens the door to enhanced use of the data for clinical and research applications.
Computer Storage Devices↗
Evaluation of an SQL model of the HELP patient database.
We tested a new model of the HELP patient database that makes use of relational tables to store patient data and provides access to data using SQL (Structured Query Language). The SQL database required more storage space and had many more physical records than the HELP database, but it was faster and more efficient in storing data than the standard HELP utilities. The HELP utilities used disk space more efficiently and were faster than the SQL tools when retrieving data for typical clinical reports. However, the SQL model provides networking capabilities, general report writing tools, detailed user documentation, and an ability for creating secondary indexes that offset its poorer performance.
Database Management Systems↗
Pyrolysis mass spectrometry of bacteria from infected human urine. I. Influence of culturing and antibiotics.
Curie-point pyrolysis mass spectrometry was performed on three bacterial isolates obtained from infected human urine using a novel, direct isolation method. Bacterial samples were analysed directly after isolation, as well as after free growth in broth and after exposure to solutions containing penicillin and gentamicin. The spectra of bacteria directly from urine showed no detectable contamination from urinary constituents. Discriminant analysis indicated genetic strain differences to be greater than the combined variances due to sample preparation or the growth phase. Characteristic biochemical changes related to growth or non-growth were detectable after only 2 h of incubation. The potential usefulness of pyrolysis mass spectrometry techniques for rapid susceptibility testing is discussed.
Anti-Bacterial Agents↗