Abstract: The recent emphasis on regulatory compliance, mergers and acquisitions and health information exchanges has made the creating and maintaining of accurate and complete master data a business imperative in healthcare industry. In this post I will briefly discuss the importance of Master Data Management and three approaches for MDM.
To answer the question about why master data management(MDM) is important it is better to start by definition of MDM; is a comprehensive method of enabling an enterprise to link all of its critical data to one file, called a master file, that provides a common point of reference. When properly done, MDM streamlines data sharing among personnel and departments.
Three main drivers are making MDM more important than ever in the healthcare industry:
- Mergers and Acquisitions (M&A): The IT systems of organizations involved in M&A are rarely the same, and each organization has its own master data.
- Health information exchanges (HIEs): To successfully exchange information across locations and organizations, HIEs have to be able to reconcile master data.
- ACOs: To understand and manage their patient populations, ACOs bring together health system data and payer data.
When we found out about the importance of MDM the next question is how to tackle it. Currently, three main approaches are available:
- IT system consolidation: abandon best-of-breed solutions in favor of monolithic EMR and ERP solutions.
- 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).
- Downstream master data reconciliation in an enterprise data warehouse (EDW): for organization who 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.
How to find best approach: The drawback of IT consolidation is its complexity and its expense. Also upstream implementations tend to be complicated, large, expensive, and slow-moving IT projects. We find that this approach has a high failure rate. finally while EDW platforms enable healthcare organizations to use their data to drive higher-quality, lower-cost care but it will not solve master data challenges at the level of transactional systems.
Conclusion: In real-world situations, there can be quite a bit of overlap among these M&A, HIEs and ACOs which makes selecting the best approach for MDM difficult. The solutions we have in place now for managing master data may not be comprehensive enough to encompass all the data a healthcare organization will need to leverage. An EDW can step in and bridge any gaps in an organization’s MDM strategy.
References:
http://searchdatamanagement.techtarget.com/definition/master-data-management
https://msdn.microsoft.com/en-us/library/bb190163.aspx
http://www.gartner.com/it-glossary/master-data-management-mdm/
https://www.healthcatalyst.com/master-data-management-in-healthcare-3-approaches
http://dataconomy.com/2016/03/modern-face-master-data/