Consider the following scenario: You are in a hospital setting that uses an enterprise EHR system with multiple interfaces to other health information platforms. What types of data would be kept in each system and what steps would be needed to allow for analytics to be performed across multiple disparate platforms?
An enterprise EHR system usually consists of several interfaces that are created for each department. Therefore, every system will contain specific types of data that are relevant to the department. For instance, the laboratory will keep information about the patients’ test results and registration will have the information about the patients’ address, phone number, health insurance status, their scheduled appointments, and billing preferences. Doctors will have access to patients’ history, their vaccination status, and chronic and acute conditions.
A cross-platform analysis is a challenging effort, as it requires not only a road view into enterprise-wide data but also data standardization and governance (Walji et al., 2014). Three steps can facilitate the analytics being performed across multiple disparate platforms:
- Careful selection of enterprise data warehouse. A mindfully chosen data warehouse enables the health system to mine data for improvement opportunities, while vastly speeding up major data initiatives. Usually, this is an expensive matter; however, according to recent research, it is money well-spent.
- Data governance and standardization. This step includes defining the standards of data that is entered and stored in the database. Moreover, these standards should be taught to the end-users to ensure the effective time distribution of the hospital personnel.
- Matching patients to care. The final step aims at tracking patient encounters across multiple care locations and information systems. In other words, all the relationships between entities should be identified and unified.
Reference
Walji, M., Kalenderian, E., Piotrowski, M., Tran, D., Kookal, K., Takeda, O., … Patel V. (2014). Are three methods better than one? A comparative assessment of usability evaluation methods in an EHR. International Journal of Medical Informatics, 83(5), 361-367. Web.