Selected article for: "processing data and time number"

Author: Lazarus, Ross; Yih, Katherine; Platt, Richard
Title: Distributed data processing for public health surveillance
  • Document date: 2006_9_19
  • ID: 1fu1blu0_13
    Snippet: Data flows for the NDP are illustrated in Figure 1 . Data pre-processing, detection of repeated visits by the same patient for the same syndrome, and data aggregation is performed using a custom software package, written, maintained, and distributed by the NDP datacenter. Data providers maintain complete control of the security of their own PHI and also maintain control over the operation of the data processing software, which runs on one of thei.....
    Document: Data flows for the NDP are illustrated in Figure 1 . Data pre-processing, detection of repeated visits by the same patient for the same syndrome, and data aggregation is performed using a custom software package, written, maintained, and distributed by the NDP datacenter. Data providers maintain complete control of the security of their own PHI and also maintain control over the operation of the data processing software, which runs on one of their secured workstations. Since the pre-processing takes place within a secured environment under the control of the data provider, there is no need for the individual patient identifiers to be divulged to the datacenter. In the case of the NDP [5] , the only data that is centrally collated consists of counts of the number of new episodes of specific syndromes over a defined time period (currently set at each 24 hour period ending at midnight), by geographic area (currently, 5-digit zip code area). More detailed definitions of "syndromes" and "new episodes" are provided below. Table 1 illustrates the data transferred from each data provider each day to the datacenter for statistical processing, reporting and alerting. Note that the although this data does not contain any obvious identifiers such as date of birth or gender, there is always a risk that a specific individual might be identifiable using additional data, and that this risk is greatest in zip codes with very small populations.

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