Objective To summarize primary clinical data from Xiao Tang Shan Hospital (XTSH) Information System, to provide evidence for clinical data of emerging diseases. Method The primary data were extracted from XTSH information system, which related to demographic and background information, case history, prescriptions, laboratory tests, physical examination, vital sign, surgery, diagnostics and expenditures. The software for data verification was developed by Delphi language program. The information of SARS management was developed by Oracle Developer. Results XTSH information system for SARS management collected 1.09 million pieces of information covering 680 SARS cases. The database was functionally divided into inquiry window, conditional case list window and case details spread window, which provided information of SARS management and shaped a platform for further investigation. Quality control of clinical data was done by the software of SARS Information Real Control.Conclusions XTSH information system collected complete data of SARS management, which made healthcare, research and policy-making on SARS accessible, and made it possible to share resources and train the professionals.
Objective To explore and establish a more precise and reasonable classification method which is suitable for clinical treatment and scientific research of SARS patients. Methods ① Establishing a computerized classification method: Analyzing the relationship between variable items on the front page of medical records and severity of disease; Identifying the variable items related to patient’s condition by stepwise identification analysis; Creating a function equation and computerized classification system. ② Comparing and analyzing the difference between computerized and clinical classifications regarding to the general condition of patients, clinical manifestations, laboratorial test results, prognosis, period of hospitalization and medical expenditure, etc. Results ① Clinical classification: general cases 642 (94.41%), critical cases 38 (5.59%); Computerized classification: type A 436 (64.12%), type C 237 (34.85%), type D 7 (1.03%), no type B. ② There were statistical significance among groups between two classifications regarding the items of general condition (age, cure rate, mortality and average length of hospitalization), total protein , Alb, BUN and medical expenditure. ③ Comparative analysis of the two classifications: 99.77% of type A cases (general type) by computerized classification were general cases by clinical classification; 97.36% of critical cases by clinical classification were type Camp;D by computerized classification. Conclusions The results are conformity between two classifications and the differences are analogical among thegroups. The statistical difference is significant between general and critical cases with the number of critical cases by computerized classification 6.42 times more than that by clinical classification; Compared with clinical classification, computerized classification has advantages that there is significant difference between the groups while no difference within the groups. With more critical cases and more objective and logic results, the compauterized classification is suitable for study and application in the fields of health service quality management, health economy management and pharmaceutical economics, etc.