Master data management also referred to as MDM, can be defined or explained as a comprehensive method in which an enterprise is enabled to link its critical data to one file called a master file. This master file provides a point of reference and facilitates the streamlining of data sharing among personnel and departments in an organization. The importance of Healthcare MDM is that it enables healthcare personnel and organizations to streamline the plethora of patient data and clinical big data for easier analysis, interpretation, and access
Healthcare MDM solutions comprise a broad range of data cleansing, interpretation, transformation and integration practices and levels. As more and more data sources are added to the system from different levels and in different forms, master data management initiates a process that makes it easier to identify, collect, transform, and repair data. When a healthcare organization uses Healthcare MDM they have confidence that all their data is accurate, up-to-date, and consistent. Once the data meets the quality thresholds, schemas and taxonomies are created to help maintain a high-quality master reference.
What are the benefits of Healthcare MDM?
Healthcare MDM provides a reference point for critical information in the healthcare industry and eliminates costly redundancies that occur within organizations when they rely on multiple sources of information which are conflicting. Having multiple sources of information is a widespread problem, especially in large healthcare organizations, and the associated costs can be very high.
Approaches to Healthcare MDM
There are three main approaches to healthcare master data management and they are:
- IT system consolidation
- Upstream MDM implementation
- Downstream master data reconciliation in an enterprise data warehouse (EDW)
IT System Consolidation: One of the popular and common ways to handle healthcare data management within a healthcare organization is by abandoning the popular solutions and use instead, monolithic EMR and ERP solutions.
These solutions are the Epics and Corners of what can be referred to as the clinical realm and the Lawsons and Peoplesoft’s of the business processes realm. Implementing these consolidated solutions involves reconciling all of an organization’s master data and then the monolithic solutions become “masters” of the data in their respective realms.
- The advantages of the IT system consolidation of MDM is that in addition to its relative comprehensiveness, you get another benefit of this approach: when MDM is handled at the level of these transactional systems, master data is reconciled at the time of the transaction. For example, a patient is matched at the moment that she or he is registered in the system rather than upstream or downstream.
- The major disadvantages of this method is its complexity and its cost. These systems are not cheap, and the changeover consumes significant resources. It is also important to realize that, while these initiatives solve master data challenges within an organization, when there is a desire to integrate outside data with mastered organizational data, there may be a need for more MDM between the data sources.
Upstream MDM Implementation
In an upstream MDM implementation, organizations keep their disparate IT systems but map their master data through a third-party tool such as an enterprise master patient index (EMPI).
- The advantages of a system like this is that although master data problems aren’t reconciled in the source (as is possible with IT consolidation), they are reconciled very near the source. In addition, these systems allow for extensive manual adjudication.
- The disadvantage of the Upstream MDM implementation is one that’s all too common in the healthcare industry- it is expensive. This approach might seem more attractive on paper than a massive IT consolidation initiative, but most organizations favor IT consolidation over upstream MDM implementation. This is because upstream implementations tend to be complicated, large, expensive, and slow-moving IT projects. We find that this approach has a high failure rate.
Downstream master data reconciliation in an enterprise data warehouse (EDW)
When the two approaches mentioned above don’t appeal to an organization, then EDW becomes the right alternative for an MDM strategy. Healthcare organizations can be able to implement EDW platforms, analytics applications, and process that enable healthcare organizations to use their data to drive high quality and lower cost care. As such, MDM isn’t the principal focus. But that doesn’t mean an EDW can’t help with MDM challenges. If an organization has already mastered its data, an EDW can work with whatever MDM approach has been adopted. And if the organization hasn’t solved its MDM problems, resolving issues with common linkable identifiers and common linkable vocabulary in an EDW platform is an option. The main benefit of using an EDW to master data is that it is a very achievable solution to the problem. The main drawback of this approach, however, is that the mastered data is only available for analytics.