How to DIY Master Data Management for Healthcare and Life Sciences

by | Jan 12, 2022 | Healthcare, Life Sciences, Master Data Management

Master Data Management for Healthcare Organizations

Healthcare organizations require coordinating mass amounts of data across multiple providers with unique levels of sophistication, which is often a challenging task when the data is outdated or fragmented. These data sets help healthcare and life science businesses improve patient care, lower costs, and inform future decisions.

In this post, you’ll discover the steps healthcare organizations can take to develop and implement a master data management (MDM) system from scratch. However, based on over 15 years of experience in the healthcare industry, developing and implementing a master data management (MDM) platform is complicated and expensive, often requiring the expertise of a solution provider.

Ready to learn more? Let’s discover how you can implement MDM in-house and create a single source of truth for your healthcare organization.

Key Takeaways:

  • MDM provides consistent, accurate, and reliable master data sets.
  • A DIY MDM approach will be more expensive and time-consuming than working with a provider.
  • Your MDM strategy needs to include a proper data origination, management, and consumption strategy to be effective.

What is MDM?

An MDM program consists of the tools, processes, and technology that configures the data lists across the entire organization consistently and reliably. Typically, this will include the integration of master data and real-time healthcare data. Master data often consists of a defined data list such as patient name, location, panel status, workflows, and more.

In many cases with healthcare organizations, fundamental changes to the technology and business process will need to change to maintain clean master data. You should also expect to invest effort, time, and money into creating accurate data that will be updated and expanded over time.

A successful MDM platform helps improve patient outcomes and reduce administrative resources at a lower cost and risk. A few key benefits of a successful healthcare MDM program include:

  • Track the patient journey for all types and sizes of life science organizations
  • Support organized and accurate directories for thousands of providers
  • Meet compliance requirements with timely reporting for regulatory establishments and consent workflows
  • Connect to industry CRM systems and API integrations to consume, publish, and connect data in real time


Data Provides Strategic Advantages Chart
Source: Experian

7 Steps to Get Started with MDM for Healthcare In-House

Creating an MDM program can seem like a daunting task for many companies, especially if you have complex or unorganized data streams. If your organization wants to follow a DIY approach, you can get started using these steps:

1. Identify Your Master Data Sources

Start with a few consolidated sources of master data to learn from and then scale in the future. In this stage, you may discover completely new data sets that you didn’t know existed initially. However, you’ll want to make sure that the data you choose represents your organization, so you avoid making technology decisions around data that you’ll have to change in the future.

Data Managed Internally Will Increase 20% by 2022 Graph
Source: Data Services Inc.

2. Analyze the Metadata for Your Master Data

Once you have your key sources identified, you’ll want to select the attributes and entities for the data, including:

  • Data type
  • Attribute name
  • Constraints
  • Default values
  • Dependencies
  • The owner (who owns and maintains the data)

The owner is often challenging to identify and could take significant effort unless you have an existing data repository.

3. Determine Data Point of Contacts

With the metadata attributes selected, you need to appoint the “data stewards” who can transform the source data into the MDM format. As a best practice, the initial owners select the stewards based on their data knowledge and will be responsible for the MDM program.

4. Develop a Data Governance Council and Program

A crucial part of your MDM program is creating rules around how the organization maintains, audits, and includes the master data. When you embark on this project, especially in a DIY capacity, you will need to make countless decisions. Having a defined decision-making process will ensure long-term success for your organization.

5. Create a Master Data Model

As the most time-consuming step, you need to decide what you want your master records to look like, including the attributes, values, and data types. You should start this process by mapping your current data sources to the master data model. It’s essential to avoid creating a model that is too complex or large and won’t benefit your organization long-term.

6. Select Your Tools

Next, you need to build tools that enable your master lists to clean, transform, maintain, and use the data in real time. Depending on your goals, organizations can use a single tool that serves all these functions or choose multiple toolsets that are better at one task.

In general, you’ll want to choose technology that provides the following features for your master data:

  • Versioning
  • Modeling
  • Data matching
  • Stewardship
  • Hierarchy management
  • Integrations

And, of course, as your healthcare platform grows, the tools should have the ability to scale and perform in parallel with your overall growth.

7. Create the Infrastructure and Maintenance Processes

Once you get past the hard part of obtaining clean data, you need to push it into your internal applications and develop the right processes to maintain it. When you implement the infrastructure into your systems, your business will expect it to be consistent and available, so it’s crucial to develop the right processes in place to ensure it reaches your intended goals.

This step should include:

  • Ensure the MDM program fits within your existing infrastructure and applications
  • Build tools for the data steward to quickly recognize errors and reduce complex corrections
  • Provide a history of data changes made to isolate the mistakes better
  • Use your tools to merge your sources and master list to test the data
  • Update the systems as required and implement continuous improvement efforts

Bottom Line: Should You DIY MDM for Your Healthcare Business?

When developing your MDM strategy, it’s crucial to implement three core data management pillars: origination, management, and consumption. These components are critical to developing a robust program that benefits your business and patients.

If you plan on taking the DIY approach, it’s very easy to miss these essential steps, spend too much time making complex decisions, or run up your budget more quickly than intended. Instead, consider working with an experienced MDM solution provider dedicated to helping your organization interpret and use complex data sets.

Ready to get started? Contact Gaine today to learn more about our Coperor Platform.


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