In 2004, President Bush set a goal for every American to have an electronic health record (EHR) by 2014. The goal was that better and safer care could be delivered through more complete knowledge of a patient that was accessible in a secure repository.
The 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act spurred a wave of both new and replacement EHR purchases in the industry. Studies have shown that investing in better patient data has yielded tangible impact.
While digitizing patient data has understandably been a major priority, digitizing provider data has largely been ignored. Yet, provider data is critical to keeping hospitals and health systems running efficiently because every department and mission-critical operation relies on some aspect of provider data to function effectively:
- Consumers rely on accurate provider data each time a patient searches for providers, specialists, and schedules appointments online
- Scheduling and compliance teams work to ensure providers’ privileges are in order
- Credentialing teams need to know which providers’ licenses are active
- Referring teams must know subspecialties and which providers are in payer networks
- Billing teams need referring providers’ information to bill for ancillary services
- Lines of service marketing teams need to know the full list of referring providers in their catchment area in order to market their services
The list goes on and on.
Uniting provider data is critical
Provider data inaccuracy is frequently cited by leaders at health systems as a source of inefficiency. Because members rely on health plan directories to schedule appointments and make referral decisions, inadequate provider data can lead to dissatisfaction and increased healthcare costs. Health systems can lose millions of dollars through patient leakage – unknowingly caused by out-of-network referrals.
When it comes to managing provider data, health systems have a few options. Historically, organizations have either built a homegrown database or relied on a master data management (MDM) system.
More recently, a class of purpose-built provider data management (PDM) systems designed specifically for healthcare have entered the market and made a splash. We’ll explore the benefits of PDMs and MDMs and why, if you have an MDM, you should consider uniting your MDM with a PDM system.
Differences between MDM and PDM systems
Both MDM and PDM systems provide centralized storage of large amounts of high-quality data and enable integration with other systems. However, there are many differences that distinguish the two systems.
PDMs are, by definition, provider specific. They are built on a data model that includes data points covering all aspects of clinicians and are curated either manually or by feeds from trusted data sources, such as credentialing platforms. Critical provider information includes locations, specialties, subspecialties, health plans, network participation, and more.
In contrast, an MDM is an application-agnostic data repository. It requires that IT teams and subject matter experts develop a data model, business workflows, end user applications, reporting, and integration. MDMs also require substantial ongoing IT resources to develop and maintain, as well as a highly technical team to configure the database and retrieve data for it to be put to use. In general, PDMs are more user-friendly and require minimal technical support after implementation.
Another difference between PDMs and MDMs is their data management and sharing. An effective provider directory should consolidate, cleanse, and normalize all provider data using your integrated delivery network (IDN)’s provider information. Software should also continuously update all healthcare systems via Application Programming Interfaces (APIs) behind the scenes. Unlike PDMs, with MDMs, provider data must be manually consolidated, de-duped, loaded, and cleansed by data teams across the healthcare organization. Without a dedicated set of data curation resources, this process will either be onerous or not feasible.
A good way to think of MDMs is like Fort Knox: they’re highly secure, but difficult and time-consuming to both design and retrieve data from when ready to use. In contrast, PDMs are midweight and real time. They provide a predefined container of all the provider data a health system needs for functions from registration and scheduling to referrals and billing. They’re designed so that it’s easier to enter and retrieve data than MDMs.
Who benefits from an MDM vs PDM system?
Mid-to-large-sized organizations that want to do large-scale clinical research and data analysis with patient data could benefit from using an MDM. For example, if an organization wants to do a study on diabetic patients across six hospitals utilizing 10 years of data, an MDM can provide a rich data set. MDMs can also be useful for research around claims and processing. However, a drawback of using MDMs for these purposes is that they require a robust data analytics team. If the resources and tech talent are available, MDMs can give healthcare organizations a complete understanding of patient data, which is essential for organizations to understand how care is delivered, analyze clinical care and operations, and ultimately, determine how to better treat patients.
PDMs, on the other hand, are most useful for provider and payer organizations that want a central, continuously updated source of truth for provider data curated and available to departments across the organization. Overall, PDMs streamline data management processes and more directly impact the patient experience, leading to increased patient acquisition and decreased patient leakage. PDMs also provide some functions and operational efficiencies that an MDM cannot, including provider search and outreach, the management of locations, plans, and networks, and the ability for patient access and other teams to enroll providers in real time directly from a provider directory.
While MDMs and PDMs have different benefits, both provide high data accuracy and security. Many healthcare organizations can benefit from implementing both types of data management systems.