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Index - Major Sections
Site Map
Product and Services _______________ Index - Same Level Subject
Index - Child Subjects |
IntroductionIn order for health programs to create efficiency and effective levels of health, large volumes of data must be availability not only on health conditions but also social conditions and economical conditions. The complexity of data makes it impossible to use systems that are in place today. A new solution must be offered. Although it has been stated that the quality of data can only be improved by improving the accuracy of diagnosis and improving the accuracy of the codification of causes of death, this is not enough. It is well and good that we know what a person died from, but it is even better if we had the data to tell us why someone died and what we can do to minimize the risk in the future
SurveillanceThe CDC defines surveillance as the following:
In general, surveillance systems today presupposes certain events or conditions. In general, Surveillances that are undertaken today by many governmental and non-governmental organizations presupposes certain events or conditions. Although the primary focus of national surveillances have been on episodic diseases such as HIV, cholera, dengue fever, TB and others, surveillances also can monitor and should monitor all treats to population health. These may include malnutrition, obesity, smoking, substance abuse and others. Surveillance is one of the most important uses of the Clinical Computer Information System. Since all data is forwarded in real time to a Data Warehouse, analysis by Data Mining can be performed and patterns recognized immediately. The key words in the definitions of surveillance relates to "on-going", or "continuous." Without the ability to analyze data continuous and immediately, patterns can not be detected and surveillance cannot be carry out. The traditional methods of existing surveillance systems: data collection, data analysis, data interpretation, and presentation, is too lengthy to effect timely solutions. It is not enough to "address specific program needs." There should be one system in place that gathers data for all programs and every possible problem. Example: One example is the delay of the detection of arsenic poisoning in India and Bangladesh. Although many cases were being reported throughout the area of patients with syndromes that would indicate arsenic poisoning, no method was used whereby these cases were correlated. The primary methods for data collection in many countries such as registries and sentinel surveillance do not give enough detail to be able to detect discernable patterns, especially previously unknown diseases. Since emerging diseases represent themselves in a variety of difference forms, as much data as possible needs to be collected. A few "key" indicators are not enough. In order to analysis data properly, trained professionals with sophisticated tools must be employed at the highest level. The ability for lower level staff to be able to use statistical tools is not required and is not desired. It is a waste of their time to be trained in such detail procedures and it is too expensive to provide them tools. The only means to do this is with very large databases located in Data Warehouses that are fed continuous with detail clinical data.
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