The primary reason and the need to aggregate data in health care is the normalization of the data and unification of it; subsequently, the queries, alerts, and reports are made possible. The main condition of this possibility is that the data is unified in a single format. For instance, the area in which data aggregation can be implemented is patient home monitoring. For that sake, the sources the data is gathered from are incompatible.
Should a provider want to order a glycated hemoglobin laboratory test for a client, the type of data is automatically identified as a laboratory result. The result is, thus, retrieved from the Laboratory Information System (LIS) and filled into the client’s record. A common code such as LOINC can be used, at that. Within a short period of time, the provider can retrieve decoded information and insert it into an electronic health record for the second time in a row. The data is thus duplicated, creating an unnecessary system strain. To avoid it, data aggregation and normalization are used. The results are presented in a unified form and no duplicates are created.
Among other factors in favor of data aggregation in healthcare are system interaction and the enhancement of the reliability of the outcome, i.e., client records. Considering the multitude of tools that exist, the challenges are numerous as well. Data aggregation and normalization facilitate exactitude and comprehensibility in the first place. The software is of critical importance at that, but so are the people. With qualified human resources, software, and techniques combined, the organization is provided with exact data on the constant update.