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While OpenMRS serves as a platform for building a medical record system within a specific healthcare network, it also can provide very valuable data which, when analyzed, creates insight into the disease burden of a region and its population health. A large instance of OpenMRS contains an immense set of data that can significantly benefit individuals that are interested in analyzing it. Privacy is an important consideration with data aggregation as healthcare data contains a large amount of patients' personal information.
The results from the analysis of this anonymous data balances the needs of both the implementers of OpenMRS and the research community. A closer look at information involving disease burden and population health gives the implementers of OpenMRS a better perspective as to what new features may be needed or old features that need to be updated/improved by the developers. Likewise, the analysis will provide researchers with better knowledge of diseases in specific areas and the burden they place on different parts of that region.
The objective of the Data Aggregation Module is to aggregate anonymous data across multiple instances of OpenMRS through a REST-Like interface. The module utilizes Hibernate to execute the SQL statement needed to access the requested, anonymous data from the database. Currently, the module supports 2 queries: Tests Ordered and Disease Counts.
The disease counts can be used to compile data on the disease burden of patients in the OpenMRS instance(s), customized based on specific diseases, cities, time period of diagnosis, and minimum/maximum number of cases.
The Tests Ordered query gathers data from an OpenMRS instance that represents a total count of all tests ordered and can be customized based on specific tests, a set of certain locations, occurrence of tests during a time period, minimum/maximum number of cases, and output format.
The data can be returned in 3 different file formats: JSON, XML, and CSV. These file formats help organize the data, allowing it to be graphed easily utilizing different data visualization tools like D3, R, or even a simple spreadsheet application like Excel.
When used with multiple instances of OpenMRS, this module can produce robust data to be graphed and help answer really interesting questions about population health.
The results themselves can be used to analyze different aspects of population health and disease burden, such as:
The Data Aggregation Module is being developed as a result of a collaboration between Moravian College and Merck Pharmaceuticals. Students at Moravian College have been working on the development of the module throughout various courses and as independent research. Merck has provided the students with mentoring and support throughout the development.