Access to Information ; China ; Humans ; Information Centers ; organization & administration ; Information Management ; organization & administration ; Management Information Systems ; standards ; Severe Acute Respiratory Syndrome ; diagnosis ; therapy

Information Services ; Information Systems ; standards ; Public Health ; statistics & numerical data ; Public Health Informatics

OBJECTIVETo improve data unified descriptions, identification, query and management in public health service by means of establishing public health information classification framework and coding system.

METHODSData sets created from all fields in public health, scientific research, health management were classified into four layers of frameworks primary class, sub-class, main class and subject areas by means of integration of vertical with horizontal classifications. All these classes were further abstracted, merged and coded by individual characteristics in public health systems.

RESULTS(1) 4 subject areas in diseases control and prevention, public health service, public health management and sanitation surveillance were established including a total of 18 main classes, 49 sub-classes and 205 primary classes. (2) 7 digits and 4 segments (area code, code, disease classification code) were designed including a total of 30 digits multi-classification codes. The purpose of data effectively classifying and coding by application of 50 basic data sets in 9 areas fo public health has been realized.

CONCLUSIONWe believe that this method is of efficiency in data classification and code for public health information communication.

Healthcare Common Procedure Coding System ; Public Health Informatics ; classification ; statistics & numerical data

OBJECTIVETo identify and generalize classes of public health laboratory detection activities and to discuss the method of identification and generalization of classes of Public Health Conceptual Information Model.

METHODSAt first, materials should be collected from consulting literatures and experts, referring to the existing system. Then, identification and generalization of classes are got for business process analysis, writing description documents, summing up important conceptions and activities, By use-case analysis, use-case diagram and tabulation of important conception and activities and reference to PHCDM, a structural diagram of classes is constructed.

RESULTSA structure diagram of classes of public health laboratory detection activity is given.

CONCLUSIONSThis is a feasible method in identification and generalization of classes of public health laboratory detection activities.

Laboratories ; classification ; Models, Organizational ; Public Health

0.37).Meanwhile a good correlation (Y=0.99X-0.18,r=0.987) was obtained. Though Westergren method correlated preferably with MICROTEST 1 (Y=0.86X+1.27,r=0.906),there was a markedly different (t=3.174,P=0.001).At last different references values were collected, according to sex and age.Male,32.5 mm/1 h(60 years old);Female, 34.03 mm/1 h(50 years old).Conclusions MICROTEST 1 correlated preferably with Westergren method.The examination by MICROTEST 1 needs small quantity of sample and fewer time.Furthermore,it has good repeatability and stability.The factors such as temperature and Hct have little influence on the results.The result suggested that it is suitable to apply MICROTEST 1 to large- scale clinical laboratory or other labs.But the reference value of ESR was influenced by age,which should be considered in clinical usage.

Since May 8th, Beijing's severe acute respiratory syndrome (SARS) epidemic is on a continuous decline. Indicating and verifying measures taken since the end of April to be effective. Three stages of SARS have been distinguished in Beijing since late April, they are described in this article as rapid growth stage beginning late April until early May, decline and stable stage throughout the first week of May, and rapid decline stage since May 9th until present. These three stages depict the effectiveness of interventive measures against SARS in Beijing since late April. Information transparency towards the public is an import part among all measures taken, enhancing public awareness and understanding of the current situation and government action as well as introduce public action. Public awareness is an important factor, forming active support for government interventions.
China ; epidemiology ; Female ; Humans ; Incidence ; Information Dissemination ; Male ; Severe Acute Respiratory Syndrome ; epidemiology ; prevention & control

OBJECTIVETo overview the contribution of diabetes in the burden of diseases.

METHODSBased on the data published by MOH, prevalence rate, mortality rate, cause eliminated life year were used to calculate the health burden of disease. Meanwhile, direct economic burden of diseases was presented.

RESULTSAccording the calculation, about 23 million of people suffered from diabetes and 90,000 died from diabetes. The cause eliminated life year attributed to diabetes is different between urban and rural, 0.21 years for urban and 0.08 years for rural. Moreover, the direct economic burden reached 1.071 billion RMB, about 1.88% of national health expenditure at the same period.

CONCLUSIONThe burden of diabetes, based on calculation of both health and economic burden, and will give a heavy pressure to the government and society.

China ; epidemiology ; Cost of Illness ; Diabetes Mellitus ; economics ; mortality ; Humans ; Prevalence ; Rural Population ; statistics & numerical data ; Survival Rate ; Urban Population ; statistics & numerical data ; Vital Statistics

OBJECTIVESTo study methodologies and relevant data-element specifications for basic dataset development in China public health information system construction

METHODSThe goals and scopes were determined through data-viewing analysis, while the function model was developed through information viewing analysis. The components and the structure of the data sets were also identified to distill data elements.

RESULTS50 basic datasets were developed and 1513 data elements were determined in 8 main domains and one public domain in China's public health information system. The 8 domains included Expanded Immunization Program (including 7 Basic Datasets and 326 data elements), Occupational Health and Poisoning (5 Basic Datasets and 158 data elements developed), Laboratory Management (9 Basic Datasets and 118 data elements included), Public Health Emergencies (including 3 Basic Datasets and 47 data elements), Infectious Disease Surveillance (4 Basic Datasets and 177 data elements developed), Non-Chronic Disease Surveillance (3 Basic Datasets and 64 data elements developed), Maternal and Child Health (totally 8 Basic Datasets and 368 data elements developed) and Environment Health (including 4 Basic Datasets and 72 data elements). One common domain consisted of 7 basic datasets and 183 data elements.

CONCLUSIONStandardizing basic datasets in public health information systems is an essential foundation in facilitating information system planning and the effective utilization of resources.

Database Management Systems ; Public Health Informatics ; statistics & numerical data

OBJECTIVETo develop a conceptual framework for decision-making data elements (indicator) in public health through determining its dimensions, sub-dimensions and their interrelationships.

METHODSOn the basis of literatures review, conceptual analysis and health determinant models, a conceptual framework was set up. This framework construction followed five principles: evidence-based, applicable, public health relevant, systemic and extensible. While, with the principles of conceptualization, objective-orientation, independence, and number-restriction, the domain and subdomains were also developed.

RESULTSA conceptual framework consisting of five domains and 20 sub-domains was developed. The 5 domains were health status, non-medical health determinants, public health system performance, the resources of public health system, and characteristics of community and assurance system. The health outcome included three subdomains of health status, functional status, and death; Non-medicine health determinants domain consisted of health behavior, working and living conditions, personal resources and environmental factors; performance domain was made up of effectiveness, accessibility, efficiency, responsibility and safety; resources domain had institution resources, human resources, financial resources, equipment resources and information resources; The characteristics of community and assurance system domain was the last domain which comprises characteristics of community, public health related policy and assurance system. The complicated relationship between these domains was also described.

CONCLUSIONAs the abstraction of public health system, this conceptual framework comprehensively depicts the components of public health system and complicated process of public health system. This framework conforms to the medical care quality model which is made up of structure, process, intermediate results and outcomes.

Decision Support Systems, Management ; Public Health Informatics ; statistics & numerical data ; Quality Assurance, Health Care

OBJECTIVETo indicate the deficiency of the classical method for analyzing data on individual matching case-control study in consideration of the interaction between the study factor (exposure) and the matching factor, and to find out a proper method for handling this deficiency.

METHODFirst, experimental data with 50 pairs of cases and controls were used for strata analysis according to the values of a matching factor to illustrate the possible interaction between a risk factor (exposure) and the matching factor. Second, a detailed procedure was proposed for analyzing such data.

RESULTSInteraction between the study factor and matching factor was demonstrated by using strata analysis and unconditional logistic regression analysis. Therefore the results from the classical analysis for such data might be incorrect.

CONCLUSIONData from individual matching case-control study design should be dealt with strata analysis or multivariate analysis to explore and evaluate the possible interaction between the study factor and matching factor. The conclusion would be valid only after such analysis is conducted.

Case-Control Studies ; Confounding Factors (Epidemiology) ; Matched-Pair Analysis ; Outcome Assessment (Health Care) ; Regression Analysis ; Risk Factors