Data Marts as a Sustainability Strategy
Grocery chains all across this great land stumbled upon a quirk about human nature that has led to massive profits over time. We all have a need to be presented with organization; call it a human frailty if you will. Sections of supermarkets have been redesigned to resemble marts, if you will. Traditionally, the mart was a place where sellers and buyers of specialized goods convened to do business.
The local supermarket offers virtually everything you might need in terms of food and household goods. Since the 1950’s, a level of compartmentalization has transpired. Now you walk in and head to your desired section; dairy, meats, bakery, and deli, to name a few. It is almost like having a specialty store within a store; where you can dart in, get just what you need, and dart back out.
A data warehouse is not much different from that supermarket. Assuming proper data extraction and cleansing; it has virtually every kind of healthcare data you would ever want. (Please note that the previous sentence presumes you retrieved clinical, claims, operational, and financial data.) A more sophisticated data warehouse owner is going to create marts of specialty data that appeal to the individual shopper. It is a way of giving your user that store within a store.
A data mart is the access layer of the data warehouse environment that is used to get data out to the users. The data mart is a subset of the data warehouse that is usually oriented to a specific business line or team. In some deployments, each department or business unit is considered the owner of its data mart including all the hardware, software and data. This enables each department to use, manipulate and develop their data any way they see fit; without altering information inside other data marts or the data warehouse. In other deployments where conformed dimensions are used, this business unit ownership will not hold true for shared dimensions like customer, product, etc.
The primary use for a data mart is business intelligence (BI) applications. BI is used to gather, store, access and analyze data. The data mart can be used by smaller business units to utilize the data they have accumulated. A data mart can be less expensive than implementing a data warehouse, thus making it more cost effective for the small user. A data mart can also be set up in much less time than a data warehouse. These facts make data analytics more attractive to the smaller organization. An example of how this scenario would work is to assume that a larger organization (such as an HIE) builds and operates the data warehouse (our supermarket). They then create a series of data marts for smaller organizations (IDN, Payer, PCMH, etc.) with specialized offerings of information pertinent to each of those organizations (dairy, bakery, meats, etc.).
There is value to healthcare analytics, much the same as there is value to that gallon of milk. Unless you wish to become best friends with the store security staff; you are going to have to pay for that container of 2% moo juice! The very same concept holds true for the owner of the data analytics infrastructure. There is value in the data and analytics shared with constituents; so it is perfectly fair to charge for furnishing that information.
Therein lies a sustainability model for the HIE or central data aggregator. Faced with diminishing funding options from grants and government programs; sustainability has to be addressed through recurring revenue; in this case from the sale of complete, cleansed, measured, and actionable information back to data contributors. So, have you set up your deli section yet?