Healthcare organizations have many sources of patient or customer identity records, and those sources can vary widely in the completeness and quality of the data.
For example, data sources that record patient identities from clinical encounters (such as EMR/EHR applications) typically have complete and good-quality information. But data sources that have marketing or digital engagement information typically have much less complete, less trusted information.
It’s helpful to think of these data sources as tiers of sources, where the highest tier contains the source systems with the most complete and trusted data, and the lowest tier contains the source systems with the thinnest data.
It is not possible to use a single set of matching logic to unify all these different sources and tiers of data without introducing either a large number of missed matches (also known as false negatives) or a large number of over-matched identities (also known as false positives). As a result, most healthcare organizations only attempt to link together their more complete & higher-quality data, from clinical encounters. This allows organizations to address a subset of their identity-related use cases, but not all use cases.
Verato Match Tiers™ is a proprietary Verato capability that allows you to match together records from different tiers using different matching configurations for each tier. A critical feature of Match Tiers is that the data from lower (thinner and less trusted identity records) tiers can be incorporated into your overall single view of a patient/consumer, but that data is not allowed to influence the matching decisions made between higher-tier records. With Match Tiers, organizations can create a truly complete and trusted single view of each patient/customer identity, which can be used to address ALL identity-related use cases in your business and technology organization.
How Verato Match Tiers work
Match Tiers are determined by your organization identifying which of your data sources should be assigned to which match tier, and then informing Verato’s Customer Success Team. The Verato Customer Success Team will then use this information to configure your Verato software instance to correctly map sources to tiers as well as the appropriate matching behavior for each tier.
This ensures that identities with data from your highest tier sources are matched at the appropriate clinical-grade level of accuracy, without allowing data from lower-tier sources to compromise the match decision. In addition, lower-tier data cannot create a ‘transitive’ link decision among higher-tier identity records.
Imagine you have two different patient identity records from your EMR system, which are in your highest tier of data sources, i.e. the most complete and accurate data.
You also have an identity record from a web form that was filled out by a person using your website.
You will only match the two EMR identity records together at a very strict level of confidence. If the attribute data about the two EMR identity records is not similar enough, you will not match them together, and you would consider them to be two separate identities.
But you also want to use the web form identity information -- which only contains a name, address, and email -- for marketing and analytics use cases, not patient care decisions.
To get the best possible benefit from all your data, you want to match the web form identity record to the EMR identity records with a slightly different level of confidence that is suitable for marketing decisions.
The Match Tiers feature allows you to make these matches, so that the web form record is matched and linked together with one of the EMR identity records. However, the web form data is not used to create a ‘transitive’ link between two EMR records, meaning you can group your web form identity with your EMR records without sacrificing the accuracy of match decisions made within the EMR records.