In Module Two, you examined the models and technologies that support
HIE communication and implementation. In Module Three, you will focus on
two database tools that are very important to the success of HIE—the data
dictionary and the master patient index (MPI).
Data dictionaries provide a full description of data including its format,
structure, and usage. It should be designed to capture all the metadata
about elements in the system. Additionally, when creating the data
dictionary, federal standards around HIE and meaningful use should be
considered. Essentially, the data dictionary supplies the rules the system
should abide, achieving semantic interoperability when all systems adhere
to the same rules. Ultimately, the data dictionary facilitates uniformity in
use and interpretation of data, decreases redundancy, improves reliability,
and enhances the ability to analyze data for making informed decisions.
The enterprise MPI contains patient demographic information as well as
information about the patient’s medical history. It has the potential to link
and aggregate MPIs from every facility involved in the HIE into one overall
database. Like data dictionaries, MPIs store data in the same format and
structure, allowing for the proper communication and transmission of
information between systems in the HIE. The MPI is a key factor in ensuring
disparate data from multiple healthcare organizations may be analyzed and
reported consistently and accurately.
In this module, you will answer questions relating to the purpose, standards,
quality elements, benefits, data elements, methods, and data mining related
to MPIs or EMPIs. Also, Milestone One, the introduction of your final
project, is due in this module. You will review the case study to identify the
issues the hospital is having and determine the content, model, and
extraction techniques you want to include in your plan. As you move
through this module, think about the ways that these tools may ultimately
be used to improve patient outcomes.
