It’s been more than seven years since the 21st Century Cures Act was first passed, but it’s only recently that the legislation has gotten its teeth, with the newly effective ability for the Department of Health and Human Services (HHS) to enforce penalties for organizations that violate its information blocking provisions.
Health identity tracking and management company Verato recently commissioned a survey to find out how prepared healthcare organizations are to comply with the Cures Act’s requirements. The results showed that there is still a long way to go for many healthcare organizations. 61% of respondents reported investing time and money into meeting Cures Act requirements but only 41% say that they are currently able to fully comply with info-blocking rules.
The survey highlighted several specific areas in which fewer than half of the surveyed organizations were fully prepared, including sending electronic patient activity notifications, sharing and receiving patient-level data, obtaining consent, and maintaining infrastructure. Regarding data exchanges, the survey also revealed that 98% and 97% and of respondents expect an increase in data requests and data arriving from external sources, respectively.
Given that this data deluge seems unavoidable, let’s look at a few of the tactics being used to ensure smooth data transfers:
Interfaces
For data sources with existing interfaces to a healthcare organization, growth of incoming data represents an opportunity rather than a hurdle. Interfaced information sent through modern protocols like FHIR arrives instantly and as discrete data directly into a patient’s health record.
The drawback is that an interface isn’t something that’s simply turned on, it needs to be both built and maintained. This means ensuring that every field that’s transferred is mapped with the correct name, units, reference range, etc. and that the interface can draw from existing data to properly match patients or their orders and encounters.
Setting up and maintaining an interface isn’t something that’s just done once though, as each source of incoming documents needs a separate interface. This makes interfaces particularly valuable for organizations that receive documents from a handful of highly concentrated sources, but they show diminishing returns with more sporadic senders.
Patient Identifiers
One of the biggest issues with organizations sending information back and forth to one another is making sure that the data is associated with the correct patient. Research gathered by AHIMA already indicates that this is a big problem, with a duplicate rate of 20 percent or more in larger hospitals. The Verato survey indicated that 57% of respondents, “believe that patient data-matching errors will result in a healthcare crisis within the next five to 10 years.”
As a company that specializes in correctly matching patient information, it’s no surprise that Verato would highlight this concern, but patient identification has been a particularly contentious issue since a turn of the millennium provision in House of Representatives spending bills that bars government funds from being used on a national patient identifier. That provision is still present in funding bills today despite concerns from industry trade groups that barring the identifier causes financial burdens and threats to patient safety.
Data Consistency
Even with data that transfers easily and matches with patients, both individual patient and amalgamated research data are only useful if they’re entered correctly and consistently. Not only do different organizations use different measurements, they often use different nomenclature as well, so despite being equivalents, computer systems may not be able to distinguish between 50 U/mL, 50 units, .05 units/liter, etc.
While the agency can’t create a universal identifier, the ONC can work on other aspects of interoperability and are doing so with standardization. Publishing a common framework of naming and measurement conventions reduces the trivial-seeming matching errors (a human can clearly tell that ‘1st’ and ‘first’ are equivalent) that become massive headaches at scale.
Automation Software
Hospitals are turning to software like Extract’s HealthyData Platform to act as a universal interface for incoming documents. The software classifies, indexes, and abstracts unstructured documents per your specific set of requirements. These documents tend to be an organization’s most time consuming for staff to enter, or most time consuming among clinicians when they are filed as images with no discrete data. The best part is that it scales to volume fluctuations as well, expected or not.
If you could use a universal interface to catch and process all the documents that don’t quite fit, please reach out and we’ll be happy to show you how you can have more complete and accurate data with lower costs.
About the Author: Chris Mack
Chris is a Marketing Manager at Extract with experience in product development, data analysis, and both traditional and digital marketing. Chris received his bachelor’s degree in English from Bucknell University and has an MBA from the University of Notre Dame. A passionate marketer, Chris strives to make complex ideas more accessible to those around him in a compelling way.