While many healthcare organizations are beginning to understand the importance of consistent terminology, achieving consistency take a lot of work and investment.

The Mayo Clinic has a long history of using records to achieve benefits across the organization, and this has continued, and intensified, as it has moved to electronic health records. Other organizations are at different stages of the process, but see the same needs that initiated Mayo’s journey.

A recent roundtable discussion hosted by Health Data Management and sponsored by Health Language discussed terminology and standards challenges that now face all segments of the industry.

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.

AMY KNOPP: Mayo Clinic recognizes data as a vital asset, and our efforts around data governance are physician-led. And we've had strong physician support through the life of our data governance terminology management. If it's driven just from a technology perspective, it's harder to get buy-in. Standardization of our practice, which includes our policies and our best practices, drives all the way down into the need to standardize and collect and manage data consistently. So we have great participation from across the organization. When we ask who wants to be the data steward, people raise their hand, and they say, “That would be my job because of what I do.”
EKTA AGRAWAL: So far, our focus primarily has been on quality and regulatory measures. And those are easy to tackle. But it’s harder when it comes to forming internal registries and utilizing the data for evidence-based practice. That shift is occurring – the conversation in terms of data stewardship – but it’s a slow process.

BAZZOLI: Amy, talk about how Mayo achieved this cultural shift in your organization. How did you get to that point where people want to own their data and standardize it?

KNOPP: It’s foundational to our culture. Our paper medical record was architected to index diagnoses and procedures, recognizing the importance of data and sharing that. At Mayo Clinic, the paper record was created so each physician would put in their own notes, and then we had a pneumatic tube system so that everybody's notes would be together. Through our data governance committee, there's a lot of work that we've done around knowledge management, how we store, manage, catalog all of our Mayo knowledge, and then how we deliver that in the context of patient care. To do that, you need to be able to collect and vet your knowledge, and then annotate it in a way that you can connect it to patient data. And the patient data needs to be structured, standardized and coded so that you can bring these things together.

PAUL TUTEN: The enterprises that are most successful at these implementations tend to recognize that health information technology is fundamentally like a socio-technical system. The thinking is sometimes, “We'll change the technology, we'll get a new standard, that will make it better and all of the problems that existed before will go away.” No, it doesn't. We just have now more standards, different ways of doing the same thing. We haven't solved the sort of fundamental social issue, which is why do I really want to share this information, what's in it for me or my patients and the things that I care about and sort of deeply value? If we solve that, it oftentimes results in a pretty good outcome. It gets people excited to want to make the investment and view it as an enterprise-based type of solution.

BAZZOLI: Is that where this should start then?

TUTEN: The problems with this lie outside of the technology layer, with the political or religious or governmental layer. So you sort of start solving in those areas to get people to agree on what's really important, whether it's within the organization or across the industry.

BRIAN LEVY: Even if we're all using SNOMED and LOINC, we're not using them in the same ways. We need to focus on the questions that we need to answer. And that's going to involve focusing on subsets or groups or smaller groups of these standards that we use in consistent ways across the groups.

JASON WOLFSON: Certain things are coming up, like a tipping point, if you will. ICD-10 is a good example. A few months back, an executive from a fairly large payer explained to me the process of harmonizing medical policies and benefit policies with preconditions or post conditions. They were using a manual process that was long and very painful, and he had been dealing with it for quite some time. This person had been a champion for years and kept saying that the payer needed to put in governance and use technology to solve the problem. It fell on deaf ears. Finally, this individual got the joy of heading up an ICD-10 mediation project. This was the tipping point to take terminology seriously. Maybe there are other pain points that people are going to eventually hit.

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