How to get ahead with access to primary and secondary terms.
Problem lists are not new to healthcare, yet the industry has historically struggled to accurately capture this critical snapshot of patient problems and visit diagnoses. While EHRs now provide an efficient way to gather problem list data, they don’t address the underlying challenge of clean data capture due to the wide variance in terminologies used across the industry.
When compiled accurately and thoroughly, problem lists have the potential to immediately align multi-disciplinary treatment efforts as patients are triaged from unit to unit or provider to provider. It’s one of the primary reasons these lists were a focal point of Meaningful Use (MU) requirements to improve electronic exchange of critical patient data. Unfortunately, strategies to meet MU problem list requisites are often more about checking off a compliance box than ensuring information is concise and accurate. Thus, many IT and clinical executives face notable challenges to effectively governing this information today.
In truth, healthcare organizations must prioritize quality control of problem lists and visit diagnoses to avoid negative downstream impacts related to analytics, clinical decision support, and reimbursement . Clinicians need streamlined methods that speed selection of problem list and visit diagnoses codes, while also improving accuracy. Otherwise healthcare organizations run the risk of:
- Inability to accurately report quality measures with inaccurate or unspecified data
- Outdated or inaccurate diagnoses because of lack of specificity
- Decrease in productivity with increased number of coder queries
- Clinician EHR dissatisfaction
These impact your hierarchical condition categories (HCC) and risk adjustment factors (RAF).
The Health Language Provider Friendly Terminology solution is uniquely positioned in the marketplace to address this problem. Our content database makes it easy for clinicians to record problems and diagnoses by providing a comprehensive library of commonly-used synonyms with mappings to SNOMED CT®, ICD-9, and ICD-10. For example, clients using the content set within their IT systems can create SNOMED CT problem lists using familiar clinical terms such as ”afib,” ”HTN,” or ”elevated BP.” In addition, the solution leverages coding and clinical attributes to ensure clinicians are aware of additional specificity needed to code at the highest level of reimbursement.
While other solutions exist that address efficient capture of problem list and visit diagnoses information, they often don’t have primary and secondary terms, creating redundancies within problems lists that can lead to confusion. It is in this area that the Health Language solution is differentiated in the marketplace through its standards-based approach wherein only primary terms are placed on problem lists and visit diagnoses. Health Language is the only terminology vendor that provides primary and secondary terms.
By building provider synonyms and vernacular around industry standards, the solution distinguishes between primary terminologies and secondary acronym options, ultimately pointing clinicians to the best code choice. For instance, the industry may use five acronyms to represent chronic obstructive pulmonary disease. Health Language Provider Friendly Terminologies uses secondary terms such as COPD to point clinicians to the primary term, eliminating redundancy and allowing clinicians to use the terminology they use every day.
Health Language is leading the charge to improve terminology conversion and accuracy through our comprehensive enterprise terminology management platform. Provider Friendly Terminology is one component of that effort, providing the tools needed to decrease clinician time spent searching for the right problem list codes. Physicians search for the terms they are accustomed to using in the paper record, thus enhancing productivity and allowing clinician focus to remain on patient care. Behind the scenes, these terminology tools convert the terms to the best SNOMED CT and ICD-9/10 codes, enhancing information sharing and interoperability with other systems.