No abstract available.
Pathology, Clinical*

BACKGROUND: Quantitative experiment and analysis of the result with statistical techniques are an essential part of the medical article for acquiring objective confidence. But errors on application, calculation, and interpretation of statistics and insufficient explanation of the used statistical technique deprive the reader of reliance on the article. We identified the statistical errors that were commonly encountered and which researchers and readers should recognize in the Korean Journal of Clinical Pathology (KJCP) in order to improve the quality of the statistics in the article. METHODS: We identified the frequency of the statistical errors from the 193 articles in the 1995 - 1996 editions of the KJCP. There were seven kinds of statistical errors that were most frequently observed. Each different kind of error in the same article were counted separately, but two or more of the same kind of error in an article were counted as one. RESULTS: Seventy-five statistical errors were identified. Seven kind of the most common errors and the observed numbers of the every kind of error were as follow : 1. Using P value without the statistical name (12), 2. Performing t test instead of the analysis of variance (ANOVA) test in comparing the means of three or more groups (11), 3. Omitting the F test on the unpaired t test in small different sized samples (10), 4. Mentioning the statistical technique without using it (9), 5. Mentioning the predictive value without prevalence (7), 6. Not performing multiple comparison after the significant ANOVA test (5), 7. Not using the P value with the correlation coefficient (r) (5). CONCLUSIONS: There were 75 statistical errors in the 1995-1996 editions of the KJCP. Not mentioning the name of the statistical technique used was the most frequently observed error. The authors' careful application of the basic statistics would be the real solution of the problem.
Pathology, Clinical* ; Prevalence

For effective construction of OCS(Order Communication System), the most core part of medical information system on medium and small hospital, this thesis understands the interface types of current medical treatment examination equipments and operational problems and shows the solution through the integrated interface management system. Showing the development cases of real time interface system for integration of clinical pathology inspection equipment, LIS(Laboratory Information System) and medical treatment system, this thesis suggests the basic construction element and the functions.
Clinical Laboratory Information Systems ; Information Systems ; Pathology, Clinical

Difficulties in calculation that hindered the practice of the delta check in the past is now no longer a problem thanks to the development of computers. But, high false positive rates, which creates heavy burden of checking-work load, are still a problem in the practice of the delta check. We propose a new approach to the reduction of false positive rates, naming our method "the multi-item univariate delta check (MIUDC) method". By the multi-item univariate delta check method, we mean a method in which univariate delta checks are performed on multiple items and specimens with the positive univariate delta check in at least k items receive a detailed investigation. Using data collected in the Department of Clinical Pathology at Korea University Guro Hospital via the Korea University Laboratory Information System, our research found that if we put specimens with positive univariate delta check in at least four test items (k=4) under a detailed investigation, check-out volumes will be light and efficiency will be high. As for test items deserving of more interest, total cholesterol, albumin, and total protein are appropriate because the false positive rate associated with them in the MIUDC was zero in a simulation study.
Chemistry, Clinical* ; Cholesterol ; Clinical Laboratory Information Systems ; Korea ; Pathology, Clinical ; Quality Control*

The authors devdeloped a computer program for automatic coding of ACR (American College of Radiology) code. The automatic coding of the ACR code is essential for computerization of the data in the department of radiology. This program was written in FoxBASE language and has been used for automatic coding of diagnosis in the Deparment of Radiology, Wallace Memorial Baptist Hospital since May 1992. The ACR dictionary files consisted of 11 files, one for the organ code and the others for the pathology code. The organ code was obtained by typing organ name or code number itself among the upper and lower level codes of the selected one that were simultaneously displayed on the screen. According to the first number of the selected organ code. the corresponding pathology code file was chosen augomatically. By the similar fashion of organ code selection, the proper pathologic dode was obtained. An example of obtained ACR code is "131.3661". This procedure was reproducible regardless of the number of fields of data. Bacause this program was written in "User's Defined Function" from, decoding of the stored ACR code was achieved by this same program and incoporation of this program into another data processing program was possible. This program had merits of simple operation, accurate and detail coding, and easy adjustment for another program. Therefore, this program can be used for automation of routine work in the department of radiology.
Automation ; Clinical Coding* ; Diagnosis ; Methods* ; Pathology ; Protestantism

The authors developed a comfortable program for routine work of surgical pathology. We used IBM PC (80386) and Foxbase plus program. The main function of this program was automatic coding and concurrent surgical report printing. During gross printing, previous biopsy number and its diagnosis were automatically searched and printed below gross description. The reported data were stored during surgical report printing simultaneously, and thus the typist's workload became considerably reduced. Search for specific cases could be performed by patient's name, surgical number, hospital number, diagnostic code numbers (SNOMED code micro glossary), and certain disease entities on very short duration.
Biopsy ; Clinical Coding ; Diagnosis ; Pathology, Surgical*

Beijing ; Humans ; Internship and Residency ; Pathology, Clinical ; education

China ; Humans ; Pathology, Clinical ; methods ; trends

Humans ; Liver Cirrhosis ; classification ; pathology ; Pathology, Clinical ; Terminology as Topic

Diagnosis, Differential ; Humans ; Lung Diseases, Interstitial ; diagnosis ; pathology ; Pathology, Clinical