Instructions: Read the case scenario then answer the discussion questions below.
Beware of the data silo
A regional healthcare system has three hospitals and seven clinics that are dispersed throughout the region. The three hospitals use one EHR system, while the clinics use a best-of-breed system that supports the needs of the clinics. Because continuity of care is important between the hospitals and clinics, the healthcare system wanted to create a virtual patient record view that would contain all data for a patient from both systems.
However, differences in data structures and definitions between the systems posed a significant problem to developing a virtual view of all of a patient’s information. Therefore, a major data mapping program was launched that mapped data between the two systems. This is a labor intensive process that required a review of each data element in each system, determining the equivalency rating for each and identifying any required transformation. HIM professionals carried out this task. When data between systems needs to be harmonized, they are mapped to standard medical terminologies such as RxNorm and SNOMED-CT.
Data mapping was performed and documented in spreadsheets early on in the program. Separate pages in the spreadsheet were created for analogous files in both systems. For instance, a separate page was created for the patient file, provider file, and so on. On each page, an analyst documented the metadata for each data field in the source and target files. Then, the analyst conducted a manual review to determine the equivalency between source and target fields. It was not long, however, before the HIM and technical staff recognized this was not an optimal solution for documentation of the data maps.
The spreadsheets created silos of data maps. The silos hampered data map reusability and did not offer visualization of the data maps. The team researched a more efficient method for documenting the data maps. They chose a graphical data mapping tool that consolidated data maps into a library, provided a way to visualize the data as maps rather than as spreadsheet rows, delivered a tool for managing the data dictionary and metadata on an enterprise-wide basis, and helped them save time in developing and maintaining the data maps.
This case pinpoints the practical need for data standards. Although data mapping is used as a foundation for data interoperability, it is a time-consuming and ongoing process. The program team found out firsthand how difficult data mapping was even though it involved mapping between only two systems. Operating from a systems perspective, the team realized that creating silos of data maps using spreadsheets was a short-sighted solution and that an integrated solution was required not only for the data itself, but for the data maps as well.
- What is a data map silo?
- What specific problems do you think may arise due to data map silos?
- What type of solution might help in this scenario? What recommendations would help the team in this scenario?