Reference Terminologies: SNOMED CT and LOINC

Reference Terminologies: SNOMED CT and LOINC

Among the most critical aspects in the healthcare organization are proper storage, retrieval, and transfer of data including clinical reports, laboratory tests, and patient history, among other social and physical aspects of each patient (Lee et al., 2013, 88). Such data require to be stored in a safe format that is easily accessible, and that can be understood by all medical professionals that the patient will meet. Furthermore, such data also needs to be properly coded so that it can be useful to other healthcare professionals outside the institution as well as regulatory authorities. While installing an (EHR) electronic health records system is an essential step for the organization, it is but a small aspect that influences the management of health records. Acquiring the proper coding and reference terminology is essential to the running and implementation of the EHR system and its use in the organization. Through the course of this work, the institution’s EHR system is evaluated with the purpose of incorporating LOINC and SNOMED CT reference languages.

Purpose

For any EHR system, there is a need for consistency in the use of medical terminologies to allow other users to access the records and interpret them using a universal scale. EHR systems are based on medical terminologies, requiring them to acknowledge varied medical conditions, procedures, instructions for patient care and therapies as well as the results of various lab tests that have been done on the patient. Nurses, physicians, and the whole range of care providers that patients interact with are trained in different medical terms to illustrate patients’ physical, social, historical, and other details that are important in patient treatment. Administrators, insurance firms, and quality regulators also have their terminologies that are essential in healthcare administration and reimbursement. Most times, different natural words can be used to describe various conditions. A heart attack, myocardial infarction, or MI can be used by different people to mean the same things on the same document. This makes it essential to have a standardized system for data entry in the EHR system

Within the organization, the proposal to have the EHR system will be efficient in handling clinical records, enhancing retrieval in different locations as well as general management tasks. However, the EHR system has many different components as the company has covered. The plan also has a proper feasibility analysis that has come up with a different coding system to enhance the use of the EHR. While the EHR system can be set up based on code developed for the institution, various quality initiatives determine the health language that should be used. Conventions, including the ICD-10, have established the naming of pathologies and disease states, accounting professionals have several financial codes that will all interact within the system. Bringing together all these functions would require many applications and clog up the system. A single system that brings together these different functions would minimize duplication of tasks and enhance the streamlining of the institution’s operations. In this age of lean operations and cost reduction, such a measure would enhance the company’s financial position and improve profitability, leading to better patient care.

Content and organizational structure

SNOMED-CT refers to the Systematized Nomenclature of Medicine Clinical Terms, a global health language used in more than 50 nations worldwide. The language has developed over more than fifty years and is now regulated by the International Health Terminology Standards Development Organisation (IHTSDO). The nomenclature is based on clinical content that has been scientifically reviewed. Information in the form of phrases written by the healthcare professional is coded in a manner that simplifies their interpretation by automatic systems (Lee et al., 2013, 87). SNOMED CT will, therefore, enable healthcare professionals to easily use codes standing for various answers from patients. Such data may be in the form of words, observation, or tests.

Logical Observation Identifiers, Names, and Codes (LOINC) on the other hand is vital in the EHR system since it provides the codes to represent the various questions, tests, or observations that can be made by the healthcare professions. The software’s standard is developed and freely maintained by Regenstrief Institute and the NIH (AHRQ, n.d., 1). The institution can use LOINC to code to aggregate results from vital tests, clinical care, lab tests, and clinical studies.

Using the two systems together has been promoted as a suitable model for EHR systems in many countries globally. Within the institution, LOINC can be used to code for the needs of the organization, helping to determine the various ‘questions’ that the patient is asked. After coming up with the code for the organization using LOINC, similar code will be developed in SNOMED CT to represent the ‘answers’ from the patient. Using the two systems together will enhance the use of the systems together in the institution.

Throughout the organizational structure, training will be essential in ensuring the smooth adoption of SNOMED/LOINC. Proper training across the whole corporate structure will be a significant step in enhancing the use of the SNOMED CT/LOINC system.  Such training should also be well planned to have real examples from code that has already been developed for the organization. Project managers, physicians, nurses, practitioners, administrators, and all other users will need to be trained on relevant codes as well as security of the information. This will improve user acceptance of the system.

Processes for maintenance and quality

While the two systems are available to be installed at no fee, the activation of this system will take a while since the organization and its workers have to learn how to use the system. Constantly used codes at the institution will have to be analyzed to develop a code-set that can represent close to a hundred per cent of the organization’s cases. Developing the code is a very crucial process as it will determine its ease of implementation. To do this, the organization will have to dedicate resources to a number of coders who will come up with the code. Rather than mapping out the code-set of the entire institution which will take long at a high cost, the institution can seek to translate a highly populated section of its local code into LOINC, allowing faster adoption of LOINC (AHRQ, n.d., 1). The same process can be done for SNOMED-CT to allow concurrent use of the two systems. The current EHR system can be used concurrently with the new SNOMED/LOINC system after which the older one can be phased out.

The SNOMED/LOINC system will require to be maintained regularly, primarily by updating the versions of the software used. However, these updates will have to be planned so that the system does not have a glitch in its use. For the first year, the orders should be updated after six months and once every year after that. For cases where caregivers lack a specific code, a code will be developed by the coding team. This will be a collaboration between language experts, coders, and physicians to enhance the development of code that will be accepted by all users (Lee et al., 2013, 88). All code will be preserved according to federal requirements, and real-time data backups maintained to enhance data integrity.

Relationships with other terminologies and codesets

SNOMED and LOINC are effective in coming up with codesets that cover clinical, financial, and research aspects for most healthcare institutions. For the institution, the transfer from the code used now will depend on the complexity of the new code compared to the older code. McKesson Z codes and CPT systems are compliant with LOINC codes for reporting clinical and laboratory tests (Chen et al., 2010,102). SNOMED and ICD-10 are primarily related, and code written using one language can easily be converted to the other. For the institution, this means that patients reporting with data from organizations that use other languages can be processed quickly into the institution’s database.

In conclusion, employing the use of SNOMED-CT and LOINC within the institution will result in improvements in data input, handling and retrieval. For the EHR system, this will reduce the need for more systems that may overload the organization’s resources. Training will be important in ensuring that all users of the institution’s system learn the code that is to be used and maintain the required level of confidence with patient data. For the project manager, this requires careful planning and execution so that the system is ready to run efficiently. The organization will then reap the full benefits of having an EHR system.

References

AHRQ (n.d.). LOINC. AHRQ Digital Healthcare Research Archive. AHRQ. Available at             https://digital.ahrq.gov/key-topics/loinc

Chen, E. S., Melton, G. B., Engelstad, M. E., & Sarkar, I. N. (2010). Standardizing Clinical          Document Names Using the HL7/LOINC Document Ontology and LOINC Codes.   AMIA. Annual Symposium proceedings. AMIA Symposium, 2010, 101–105.

Lee, D., Cornet, R., Lau, F., & de Keizer, N. (2013). A survey of SNOMED CT    implementations. Journal of Biomedical Informatics, 46(1), 87–96.            doi:10.1016/j.jbi.2012.09.006