MongoDB, the Healthcare Database

Healthcare has become a data challenge. With the advent of FHIR and the drive toward interoperability, we are closer to a future where episodic, intermittent care is replaced by a holistic, “longitudinal” view of the patient to promote life-long health. Choosing the right healthcare database platform can help get you there.

Healthcare providers and payers work in closed electronic health record (EHR) systems. Medical data is held in outdated legacy databases, and health records and health data are stored in multiple incompatible data standards. These are just some of the issues preventing the free and secure flow of medical records and other medical data to improve patient care.

Healthcare databases are a foundational component of delivering health care.

The two most common types of databases used in healthcare are relational (SQL) and non-relational (NoSQL).

The technology underlying the relational databases in use at many healthcare organizations was first developed in the 1970s. Conceived long before the cloud computing era, they were never intended to support evolving standards, like FHIR. Neither were they developed for connected devices, nor the volume, variety, and velocity of data generated on those devices today.

As a result, healthcare providers and payers have struggled to offer the frictionless and personalized digital experiences of startups and new entrants delivering health care services.

For years, the healthcare sector and healthcare industry has wrestled with the questions of whether, and how, to modernize their legacy database systems and other healthcare databases. With the emergence of digital engagement strategies that require connected care, real-time transactions, analytics, and database systems that support agile product development, legacy modernization has become a healthcare imperative.

The key to legacy modernization is creating a bridge between legacy systems and the new architecture, the Operational Data Layer (ODL).

This approach enables healthcare organizations to offload traffic away from costly legacy systems and, eventually, to re-architect monolithic applications into a suite of microservices. At the same time, they can apply FHIR data standards and use FHIR compliance projects — not just for check-box compliance, but as a strategic starting point for a more modern data infrastructure.

Crucially, by deploying the ODL in phases, healthcare organizations can embark on their digital transformation journey iteratively, without the risk of an all-or-nothing, rip-and-replace approach.

Read more about modernizing healthcare databases in our guide, “Bring the FHIR Inside: Digital Transformation without the Rip and Replace.”

Improving clinical workflows and patient experiences hinges on the easy exchange of and real-time access to relevant healthcare data. And that means the database you choose is vital.

Consider your own healthcare organization and its database systems.

How easy is it to:

• Access all of the data required to transform a business process?
• Extract data from legacy technology, particularly legacy relational databases?
• Combine different data formats to create meaningful and actionable insights and streamline new business processes?

The ability to execute on a digital transformation plan succeeds or fails depending on how you answer these questions. If the answer to all three is “not very easy,” then your organization, like many others, faces steep hurdles to digitally transform.

You’re stuck, battling against a pervasive opposing force or “digital friction.”

To innovate and give patients the modern healthcare experiences they expect, healthcare organizations must first free themselves from the rigid healthcare databases and architectures associated with legacy hardware, as well as monolithic health data and care applications.

Even modern healthcare databases still rely on traditional data architectures, like relational database management systems (RDBMS). This makes change harder than it needs to be. These databases slow the rate of innovation and entrench a fear of failure. They also complicate business requirements, such as data privacy, which didn’t exist when RDBMS were invented.

MongoDB offers an alternative approach to working with healthcare data and modernizing legacy healthcare systems. The flexibility of the (NoSQL) document model at the heart of MongoDB is uniquely qualified to adapt to future data demands.

With MongoDB, healthcare institutions can enrich their view of the patient with data from new sources, such as connected health devices.