5 Critical Components of MDM in EHR

Master data management (MDM) is a clear necessity in the healthcare industry—accuracy is paramount where health is concerned—but that does not mean that just any MDM system will do. There are two types of data management in healthcare: identity data, which looks at patient and provider information, and reference data, which focuses on order sets like procedure codes. There are a myriad of different systems to manage this data, but any MDM system you introduce for managing your electronic health records (EHRs) needs to have certain master data management components. At Black Oak Analytics, we recommend decoupling the various processes of MDM, allowing better control over data quality and support of the full information life cycle of your data. Healthcare organizations with an enterprise master patient index (MPI) or trying to develop an MPI, need to focus on data quality and above all metrics, which hold people and processes accountable for data quality.

1. Data Integration

Master data management programs integrate data so that it is available from anywhere within the system. In order to keep accurate EHRs, your MDM needs to be able to accept data from multiple resources and integrate them into a final format that is easy to read without duplicating data. It needs to be able to match and link information so that complete data sets are created and that EHRs are flagged when data cannot be integrated properly. Linked records should carry a persistent identifier to give the organization a fully functional enterprise MPI system. In addition, the right MDM system for health records will update entries automatically as new information is added.

2. Entity Resolution and Data Quality

Any time data is automatically imported, there will be some issues requiring specialized matching, called entity resolution. Someone may enter the same information in a different format, using different terms, or inconsistent abbreviations. There might also be data duplication, process disharmony, or issues integrating similar but separate information. Data remediation helps to solve this by providing a system for identifying entity conflicts through algorithms as well as examining data quality. Before altering internal processes or systems, the quality of in production data needs to be examined and analyzed in order to determine critical needs in the existing systems. Analyzing data quality can identify weaknesses in current processes, but can also trace some issues back to original sources. Once data quality issues have been identified, the best MDM systems also allow manual intervention to solve such issues.

3. Data Governance

Master data management programs need to address data governance as well. Data security is a vital part of data management in healthcare. It needs to be accessible by the right people and safe from those who are not authorized to view that information. Moreover, there need to be people who are responsible for that data and those people need to enforce standards about how the data is handled across the enterprise. To do this properly, these data stewards need to understand the flow of information throughout the EHR system, how provider requirements differ from member needs and the legal requirements relating to data security in healthcare.

4. Insights from Data

MDM systems should also be capable of driving insights across your different lines of business. In this manner, your healthcare organization can see which demographics it serves most frequently and the sorts of conditions encountered most. Whether you use the data to inform your business strategies, drive marketing initiatives or determine which treatments in which to invest, a master data management system can consolidate demographic information and payment records into a final format.

5. Evolution of Healthcare Systems

Finally, master data management systems can work towards identifying which locations or portions of your business are least profitable. In turn, you may be able to retire obsolete components and improve efficiency throughout your operations. You might also be able to introduce certain measures to save on time, such as self-service portals, or develop systems that streamline billing.

Are you ready to adopt a new master data management system to manage your electronic health records, decouple your matching from your existing MDM platform, or develop a new MPI system? Contact us! We can help you establish a system that makes data management in healthcare seem easy.


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