Importance of controlled terminology and standards in healthcare
Many healthcare organizations have adopted electronic health records to share data and improve the quality of healthcare provided to patients. Standardization of data involves the use of similar data codes across systems (Halley, Sensmeier & Brokel, 2009). For example, an IT department within a healthcare organization may decide to use “1” to represent males and “2” to represent females across systems. If healthcare data are coded consistently, then healthcare personnel across departments within an organization can understand and use data with ease. For example, although personnel in emergency care clinics use different terminologies from those in the pharmacy department, they understand and use data that are coded and standardized. Also, primary care physicians and specialists share data that are coded using standard vocabulary. In addition, laboratory technologists share clinical test results with physicians because they use standard terminologies across the systems. Coding of data ensures patient-directed care, and it prevents many forms of errors that could arise in the absence of data standardization (Halley et al., 2009).
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The National Health IT Agenda
The following components characterize the National Health IT Agenda:
- American Health Information Community (use cases, business needs and priorities).
- National Health Information Networks (network service providers and architectural designs).
- Standards (interoperability specifications).
- Policies (state laws and regulations, and federal leadership).
- Business deployment (efficient business models, software, state/regional partnerships, and evaluations).
- Certification (criteria development and testing).
The overall goal of the National Health IT Agenda is the coding of healthcare data to enhance interoperability which would go a long way in improving patient care (Kuperman, Blair, Franck, Devaraj & Low, 2010).
Challenges of data sharing across systems
Healthcare organizations encounter some problems when sharing data across systems. One of the challenges is that data can be standardized by specific codes that are no longer usable across systems. Such data cannot be interpreted because there are no standard codes to identify them across systems. Another challenge is that there can be a lack of standard codes that link all the data in current use (Kuperman et al., 2010). This problem is brought about by a lack of adoption of a comprehensive vocabulary. In addition, the challenge of local codes being added at each department is faced by many healthcare organizations. When such local extensions occur, data cannot be identified and used by all users across systems. The last challenge faced by healthcare organizations when sharing data across systems is that a standard code utilized to identify and interoperate data could change over time. This change of data codes is known as code reuse. If the standard code changes, then data could be wrongly interpreted by users across systems (Kuperman et al., 2010).
Solutions (strategies to avoid interoperability challenges)
Healthcare organizations dedicated to using electronic health records for improving sharing of data across systems should manage the challenges associated with interoperability. One of the strategies would involve the use of programs that provide the newest versions of software components used to interoperate data. The use of most current programs would solve the challenge of code reuse. Another strategy is that a healthcare organization should adopt data vocabularies that are developed centrally. The development of centralized data codes ensures that codes are identified and used across many interlinked systems. This strategy solves the problem of local development of codes by different departments within an organization (Truran, Saad, Zhang & Innes, 2010; Kuperman et al., 2010).
Halley, E. C., Sensmeier, J., & Brokel, J. M. (2009). Nurses exchanging information: understanding electronic health record standards and interoperability. Urologic nursing, 29(5), 305.
Kuperman, G. J., Blair, J. S., Franck, R. A., Devaraj, S., & Low, A. F. (2010). Developing data content specifications for the nationwide health information network trial implementations. Journal of the American Medical Informatics Association, 17(1), 6-12.
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Truran, D., Saad, P., Zhang, M., & Innes, K. (2010). SNOMED CT and its place in health information management practice. Health Information Management Journal, 39(2), 37.