How to Consolidate Healthcare Terminology for Better Quality and CMS Reporting
One of the great difficulties in the health care industry is the use of standards. The idea of establishing a standard, of course, is that you have one set requirements to which everyone adheres. Yet there are so many standards for so many different purposes in healthcare that it can become daunting to navigate.
This is particularly true when it comes to healthcare terminology and CMS reporting or other quality reports. As discussed in our Guide to Knowing Which Terminology Standard to Use, there are billing terminologies like ICD-9/ICD-10 for claims data, SNOMED CT for various types of clinical data, LOINC for lab results, as well as internal terminology specific to the organization, and more. So many different standards for so many different things, and sometimes they even overlap.
Implementation of these terminology standards is another challenge. The objective of many standards is to enable greater capabilities, like interoperability, based on common building blocks. However, adoption and implementation of the standards has proven difficult and expensive. The only standards that have become widely adopted are those that have a clear and significant return on investment, like billing codes where adoption is mandatory for reimbursement.
Quality reporting requirements in healthcare attempt to take advantage of terminology standards. CMS, as well as other government entities, reference these standards in their reporting requirements. This is true for Meaningful Use measures, some Accountable Care Organizations (ACOs), and the National Health Safety Network, to name a few. This government encouragement to use the terminology standards aids adoption processes. It also makes explicit definition of measures simpler when referencing a previously defined standard terminology. The desired result of these recommendations and measures is greater interoperability, and higher quality care at a lower cost.
CMS has taken steps to ensure ACOs are focusing on quality as well as cost savings by leveraging previously developed Clinical Quality Metrics in defining ACO reporting requirements. CMS currently has defined 33 performance measures on which ACOs report.
While these measures reference standard clinical terminology, many private ACOs are using claims data for reporting. This is due to its structured nature and availability, but it isn’t the best way to report on quality. Claims data can show certain preventive measures, such as the last time a patient over 50 years of age had a colonoscopy or whether one with diabetes has had a recent Hg A1C test. But it can’t show the outcome of that test to see if improvements have been made. For that type of information you need clinical data which is often unstructured or captured in multiple places. Even ACOs that have good systems in place may find that much of the clinical data isn’t being captured in specifically assigned fields but rather in the unstructured clinical notes section of their electronic health records (EHR) system.
Of course, ACO participation is just one of many areas affected by a lack of real standardization. Most health care organizations have multiple reporting requirements to various entities, such as Meaningful Use and their own internal reports, which demand the ability to access different types of captured data in different ways using different terminology protocols. This is where it gets complicated.
Addressing Healthcare Terminology Disconnects
Healthcare organizations are taking several paths to address these standardization issues. Some of the strategies are discussed below.
One strategy is to develop clinical terminology sets using terms defined according to SNOMED or LOINC codes. In fact, some EHR and point solution vendors are now offering pre-built clinical term sets, like Problem Lists, that are based on or mapped to SNOMED. Another approach is manually mapping the data extracted on populations for use in CMS reporting.
Other organizations are taking matters into their own hands and developing robust mapping solutions between the terminology they use internally and standards such as SNOMED or LOINC. They may even purchase a third-party terminology solution that comes pre-loaded with the standards and assist in mapping efforts.
On a smaller scale, some organizations are creating and storing mapping files on more of an as-needed basis. In other words, they don’t map data from their internal system to a standard until there is a report that requires it. And then they may only map subsets of their internal codes to specific standards just to meet a particular reporting requirement.
Another option has been to hand off problems with reconciling terminology to the vendors to solve. This approach is not ideal due to the highly configurable nature of most healthcare software. Vendors can remove some of the flexibility and incorporate standards to a few aspects of their system, but it’s generally not a complete solution.
Many organizations will find that they have employed more than one of the above strategies for a variety of reasons. This is very common and adds additional challenges when trying to provide a comprehensive view of the organization.
Healthcare Data Warehouse Pulls It All Together
This is where an enterprise data warehouse (EDW) can help. An EDW has the ability to pull all the individual mapping products and workarounds an organization is using into a single solution that facilitates its reporting efforts and clinical quality improvement programs. It not only simplifies generating the reports required today, it sets a solid foundation for future reporting needs as well.
The primary advantage of an EDW is that it brings all of an organization’s clinical, claims/financial, and patient satisfaction data together in one place in a consistent form so it can be used for analytics and reporting. If mapping between terminologies has already been performed, it can pull that mapping in with the clinical data, preserving that previous investment while minimizing the amount of analysis required. If mapping is missing, there are multiple strategies that can be used to incorporate it into the EDW.
Bringing everything into an EDW ensures that the organization has a consistent picture of all the related data for analytics and reporting. It can look at all its data in one place and take advantage of its solutions in a more effective way. Centralizing the data also makes it easier to see the gaps in its current solutions and determine how to address them.
The bottom line is an EDW can support a large variety of terminology solutions – or even a lack thereof – to help facilitate working through terminology issues for quality reporting.
What issues have you encountered with terminology and quality reporting?