Differences in Terminology Challenge Healthcare, Part I
Terminology is core to everything in healthcare—from procedures to results to diagnoses. As healthcare organizations increasingly rely on information systems, agreeing on terminology usage and standards is critical to improving care, conducting analytics and other important initiatives.
Unfortunately, no single healthcare vocabulary or terminology can meet all the needs of those who use healthcare information. The variety in terminologies and the variability in how they are used has created an environment of data being trapped in silos. To improve healthcare delivery and research, terminology barriers need to be addressed.
This was the topic addressed in a recent roundtable discussion hosted by Health Data Management and sponsored by Health Language. Here is the first in a weeklong series addressing terminology challenges and possible solutions.
Moderated by HDM editor Fred Bazzoli, the panel included:
- Ekta Agrawal, MD, healthcare informatics lead at Houston Methodist Hospital System
- Sheila Britney, manager of information systems, Spectrum Health, Grand Rapids, Mich.
- Jason Buckner, vice president of informatics for Healthbridge, Health Collaborative
- Steven Christoff, Executive director, Physician Health Partners, Ocala, Fla.
- Diane Christopherson, director of analytics, OptumCare, Eden Prairie, Minn.
- Amy Knopp, manager of enterprise information management, Mayo Clinic, Rochester, Minn.
- Brian Levy, MD, senior vice president and chief medical officer, Health Language, Wolters Kluwer Health
- Jean Narcisi, director of dental informatics, American Dental Association, Chicago, and chair of WEDI
- Paul Tuten, vice president of product development and management, RxAnte, Arlington, Va.
- Jason Wolfson, Vice President, Marketing and Product Management at Wolters Kluwer Health.
In this excerpt, the panel details some of the challenges their organizations face in wrestling with terminology differences.
FRED BAZZOLI: What challenges do healthcare organizations face because of the variety of terminologies that exist, and how does it affect what you do at your organization?
EKTA AGRAWAL: We deal with a lot of unstructured data. Even though we have implemented the terminologies in context with billing and coding, there are still issues with clinical notes and lab results. It's a very common issue with healthcare organizations, especially if you're trying to make meaningful information out of the data that you collect.
BAZZOLI: Sounds like you're early in the process?
AGRAWAL: Yes, I'm just beginning to tackle that challenge. We are moving toward integrated EHR systems that would resolve some of our challenges in having the data coming from multiple sources, but with unstructured data, there’s a long way to go. For example, our gastroenterology department wanted to understand whether we are utilizing endoscopic procedures for the right indications. When we tried to analyze the data, we found out that there are 84 different indications, which were not actually 84 different indications, but just indications written different ways in unstructured formats. Many were synonyms for similar indications.
BRIAN LEVY: The nice thing about standards in healthcare is there are plenty of them. The number of standards we have to work with continues to increase, even though we have meaningful use regulations saying we should use SNOMED and LOINC. The problems begin when you start to add in all of the other standards and then all of the other subsets of these standards. We've also been surprised that this problem is being pushed down to the hospital.
AGRAWAL: Physicians are trying to understand how they can capture that information so that they can create their own registries within their practices, and they can monitor and enhance their processes. That's how we got them to the point where they are ready to utilize some structure in clinical documentation. They have started thinking about collecting the data versus just treating the patients.
JASON WOLFSON: Not only do you have unstructured data that you have to convert into standards, then you have standards that you have to convert between standards, like the outpatient code versus the inpatient code.