Identity in healthcare begins with knowing who’s who, but there are different degrees of “knowing.”
Think of everyone you know: family, friends, colleagues and acquaintances. Some you know extremely well and some you know only superficially. And that’s fine. You need to know a lot about your partner to have a happy marriage; you don’t need to know as much about your dentist to get your teeth cleaned.
Similarly, there are five levels at which healthcare organizations can know their patients, providers and others. The higher the level, the more complete the picture of people and customers, the richer the insights into their behavior and circumstances, and the more ways the healthcare organization is able to use the data for its own benefit as well as that of others.
Each level builds upon the one below it, as the user adds data and functionality and achieves interoperability with other systems. The highest level offers a 360-degree view of patients and customers across complex ecosystems with valuable insight into their identity, behavior, social determinants, preferences and more.
What level is right for you?
Each ascending level of identity intelligence provides an increasingly detailed answer to the fundamental question of who’s who. Currently, healthcare is rich in identity data but poor in insights based on that data. Identity intelligence allows organizations to collect, organize, share and analyze data to deliver exceptional experiences and power strategic initiatives.
Some healthcare organizations know only a little about patients and customers while others want a more complete picture. The important thing is that organizations possess enough knowledge to function effectively. Every organization must assess which level suits the needs of its stakeholders best – there is no right or wrong level.
Here is a closer looks at the five levels:
- Identity resolution – This is the simplest level of identity intelligence. It involves matching patients to the correct records in the EHR; knowing that John Smith is not Jon Smith; and resolving duplicate identities when they are created. This is a foundational step toward preventing medical errors and advancing patient safety. It also makes coding and billing faster and more efficient. Spending less time manually resolving patient identity errors reduces the workload on staff, which can lead to higher retention and greater job satisfaction.
- Identity interoperability – The next level takes identity intelligence outside of a single EHR. This is necessary when organizations exchange data, such as between a hospital and a lab, or a hospital and health information exchange. A merger between healthcare systems with separate EHRs is another example. It’s important that accurate patient data be preserved during data exchanges or database mergers. It might require creating a unique enterprise master person index ID across all applications. This level also contains enough data to allow users to perform basic outcome-based analytics.
- Identity enrichment – This is the level at which identity intelligence goes beyond just ensuring the correct identity and becomes richer with additional information from other sources. Typically, this will include data about a patient’s household and social determinants. That makes it easier for organizations to engage with patients all along their healthcare journey, reminding them of appointments, encouraging medication adherence, soliciting input, etc. This information also can be used by an organization to market itself to patients and organizations.
- Identity data management – This level includes multiple nonclinical facets of a patient’s life, including employment, household situation, consumer habits, hobbies, etc., with much of the information coming from outside sources. Every subject is more than just a subject, and the more a healthcare organization knows about their lives, the more it can do to ensure they receive the best possible care and services. Organizations can use this enriched data to segment patients for a variety of purposes and to map their journeys so that they know every point at which the patient interacts with the system.
- Identity intelligence – This highest level can be defined as fully understanding every patient, member, consumer, clinician, and employee, unifying their data and using it for the purposes of connection, identification, enrichment, management and activation. It combines identity resolution and enrichment with identity verification, AI-powered data governance, and advanced insights. It is reliable enough to provide data for AI training and usage, as well as hospital operations.
The power of identity intelligence
Of course, it’s not necessary for every healthcare organization to operate at Level 5 to successfully manage identity. As mentioned earlier, different organizations have varying needs and, for some, the more basic levels might suffice. For those that want a higher level of identity intelligence, it’s a good idea to begin at a lower tier and progress, rather than trying to jump immediately to 4 or 5 without having the necessary systems in place to manage it.
The important thing is for healthcare organizations to achieve a level of identity intelligence that allows them to operate with confidence and best serve themselves and others.
More organizations are recognizing identity intelligence for the valuable and versatile asset it is. They use it to guide operations, deliver exceptional experiences, maximize engagement, and support enterprise acquisition and retention strategies for growth.
A healthcare data management system that serves as the single source of truth for identity intelligence can transform how healthcare organizations operate and set them up for success in an industry that relies on knowing its patients and customers.
About Nick Orser
Nick Orser is GM, Healthcare Providers and HIEs, at Verato, offering the industry’s first hMDM, the next-generation MDM for healthcare.
