What is Master Data Management and Where Should I Start?

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Oct 23, 2017

What is Master Data Management and Where Should I Start?

Written by Impact Advisors

Category: Data & Analytics

Master Data Management (MDM) has been an established IT concept for several decades. However, it just became a buzzword in the healthcare industry over the last few years. While there are many similar yet different definitions out there, in our opinion,

Master data management is the effort that utilizes governance, process, talent and technical tools to develop and maintain the single source of truth for enterprise data assets. These assets, managed correctly, can effectively support business operations decision making and planning activities.

So, what really is MDM? Imagine you need a list of providers that serve in your organization. You could pull a list from your EHR (if not multiple EHRs), another list from your HR system, and perhaps another one from your physician credentialing system. Theoretically, all the lists should sync up, but the reality is rarely that perfect – you will find discrepancies. So how do you know which list is correct? The processes, procedures and associated technologies of establishing and maintaining a master list (aka, “source of truth”) in this scenario is essentially MDM. It is important to note that MDM should not be just an IT concept, it is an organization-wide strategy.

Everyone seems to understand the importance of MDM. However, most health organizations traditionally relegate MDM as a focus of the Health Information Management (HIM) team. Current HIM teams are generally capable of handling patient identity management by using a Master Patient Index (MPI), with defined processes in place for cleanup and consolidation. The scope of MDM is much bigger than identity related data – patient, provider, employee, vendor – it also covers referential data like CDM, order sets, formulary, market share, financial data, etc.

Compared to subjects like predictive analytics, machine learning or telemedicine, MDM might not sound like the most fun topic to work on. But it is critical to an organization seeking to derive value from their data and truly leverage timely accurate data as an asset for informed decision making. Understandably, the U.S healthcare faces many challenges with MDM given the recent industry evolution (e.g. approximately 90% of the healthcare organizations just deployed EHR in the last decade), the active M&A transactions in the last a few years, and, in some cases, organizations’ internal political resistance. However, the speed of data acquisition is growing exponentially – organizations are now flooded by the data attained through their IT systems. The need for MDM in healthcare is urgent.

It should be understood that the larger the organization, the greater the need for MDM – and the larger the impact of enterprise MDM. So, where to start? Here is a short list to get the ball rolling:

1. Survey the organization’s existing data assets, products and competency.

  • An initial inventory provides great insight to the variety of similar data used throughout the organization.
  • Start from the pain points if that’s easier. Don’t let perfect be the enemy of good.

2. Establish an MDM governance body.

  • Ensure executive buy-in. Create executive roles to serve as the responsible data champions for the organization, e.g. Chief Data Office, Chief Analytics Officer.
  • Since MDM is essentially a part of overarching data governance, utilize your existing data governance structure (if you don’t have data governance, well, that’s another blog!). This body will be imperative in many decision points during the initial data “de-weaving” as well as ongoing maintenance. It will also serve as the advocate for the needed organizational change management.
  • The MDM governance body must address both business and technical considerations. It is vital to recognize ongoing MDM is not only a technical “massage” of data, it also involves business processes and organizational culture. Successful education around this philosophy will perpetuate a fruitful MDM program.

3. Foster an organizational culture of MDM.

  • Promote the benefits of data consistency enhances MDM efforts in the long run.
  • Plan for the expected changes to minimize political obstacles.

4. Evaluate internal technical capability on supporting an MDM initiative (hint: don’t rush out and get a shiny MDM tool).

  • Assess your current tools and staff to fully understand their capabilities. While technology can enable a desired process, the first priority is to understand what you and your team can already do with what they have to work with today.
  • In the same way as if you don’t know how to drive, you shouldn’t be shopping for a car; you must understand what you need before you can go to market for a solution.

We hope these recommendations inspire you to develop a successful MDM program that supports solid data-driven decisions for your organization. Decisions you can trust, based on a well-managed source of truth.