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Historically, in the process of diagnostic decision making, emphasis was on the skills of effective history taking and physical examination. When deemed necessary, simple laboratory tests (eg, blood count, urinalysis) were also performed by the examiner. This flow of information was a powerful way of making the diagnosis. Admittedly, the ambiguous information content of these data frequently had to be interpreted by nonscientific methods; on the other hand, even these vague data when enriched by the good diagnostician's experience and intuition could lead to remarkably accurate diagnoses. For thousands of years this simple system of information flow was the "art of medicine," justifiably the pride of distinguished line of great clinicians, and it should be remembered with considerable nostalgia. Recent progress in various fields of medical sciences caused a palpable shift in emphasis. Following World War II, the scope of laboratory medicine enlarged at a spectacular rate. The practitioner could

The author presents the complex scientific and technical foundation of the recently completed biomedical nomenclature. This nomenclature places all the terms into a single hierarchical order. Computer-compatibility is achieved by the numeric representation of the location (“address”) of the term on the hierarchical tree. These unique numeric representations serve as codes, making the system language-independent, with potential for usage in various languages, and rendering medical terminology computer-compatible.

A cytopathic strain of hepatitis A virus (HAV) has been used to evaluate the absorption-elution of several membranes. Filters were obtained from four different manufactures: Sartorius, Millipore, Gelman and Cuno. Only the electronegative HAWP (Millipore) and the electropositive (Cuno-Div.) filters appear to absorb HAV with a high efficiency.

A feasibility study for computer-based quality screening was carried on 497 clinical cases. Rule-directed audit criteria were used. Discharge summaries were analyzed in an effort to detect possible quality problems. The charts of the same cases were also screened by nurses, and the suspected cases of both process es were further reviewed by physicians. The computer-based text analysis compared favorably with the screening by nurses, and showed a rather low false negative rate. The objectives of substantiating the discharge summary as a valid source document for generic quality screening was demonstrated. In addition the economy and feasibility of computer based text analysis and interpretation was proven. Finally the applicability of algorithmic rules in detecting clinical quality indicators showed great promise and presents an area of further research. Thus the feasibility study was highly successful. The potential of computer-based care quality assessment is discussed.

When computers were initially installed into the medical environment, it was accepted that the medical input data must be disciplined extensively to make them computer-compatible. Numerous classifying and coding decisions had to be made before a keypunch operator could transfer medical ideas on to the 80-column punch card. During the next two decades, it became increasingly apparent that there is a barrier between human communication conducted in natural language, and the machine's unnatural language [1]. This barrier persists as a major stumbling block to the exploitation of the vast potential of the computer in medicine. As the field of clinical computing matures, the construction of a medical man-machine interface has become a difficult but not impossible challenge. The interface must eliminate the barrier between two languages so that information can flow freely between the physician and his machine. This paper describes the approach we have taken for the development of a medical interface which makes...

Automated fact extraction from discharge summaries of the hospital chart yielded a useful set of facts for characterizing the clinical history and care of a hospitalized patient. The extracted facts depict the clinical events of a single patient, whereas the aggregate of the facts reflects the hospital's pattern of health care. Automated analysis of the discharge summaries provides good data for monitoring quality of care: Appropriateness and timeliness of hospitalization, effectiveness of diagnostic hypothesis generation, judicious use of resources, iatrogenic problems (surgical complications, other therapeutic mishaps), and inconsistencies (such as an abnormal finding without follow-up) are some of the issues recognizable when studying the care rendered. Fiscal studies are facilitated by the 50 to 100 facts on each patient considered pertinent and significant by the physician. These facts on each patient provide a much better definition of the illness and the resources used than the currently used discharge abstract data for DRG grouping. Medical audit: Ongoing clinical self-audit and cost study should stimulate a hospital's medical staff to constantly improve the quality of patient care management, and to be aware of the cost of the various resources. Alternative treatment patterns can be compared in the institutional audit reports, based on outcome, patient satisfaction, and/or cost. Clinical medicine could use a multi-institutional fact data-base as a retrievable source of yesterday's clinical experience, to guide clinical decisions of today.

This radioautographic study was undertaken to ascertain the fate of radiosulfur in the brains of rats receiving S 35 -labeled L-methionine under a variety of experimental conditions. As reported elsewhere, 9,10 it was of great interest to find in the initial experiments that under normal conditions the cerebral radioautograms showed depths of contrast that gave them a striking resemblance to Nissl-stained sections. While this work was in progress, Cohn et al. published an abstract summarizing cerebral radioautographic studies in which they used the same labeled amino acid. 3 By biochemical methods they found that the radioactivity was "mainly due to protein-bound S 35 ." They observed that "the incorporation of S 35 into the proteins was considerably greater in the regions containing cell bodies than in the white matter" and pointed out that "it was particularly prominent in the pyramidalis layer of Ammon's horn [hippocampus] and in the `neurosecretory cells' of