Health informatics -final exam Essay Example

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Health Informatics 6

Health Informatics

Health Informatics

Decision support technologies are increasingly available to contemporary medical practitioners. There are numerous software programs designed to assist with, diagnosis, health maintenance, drug dosing and other clinically relevant healthcare decisions. There is a growing tendency of using computers to maintain medical records. This tendency has created a need for automated medical decision-making. The Electronic Health Record (EHR) is the key driver for the increasing use of computerized decision tools (Haug, Rocha & Rocha, 2007). EHR has enabled the development of clinical decision support systems (DSS).

Decision support systems work on the basis of practice guidelines. These refer to systematically developed statements to help players such as practitioners and patients decide on appropriate care and given clinical circumstances (Gordon & Christensen, 1995). Communication technologies, medical terminologies and structural components are essential to provide information to the DSS. Health Level Seven (HL7), ISO, and DICOM technologies help in the establishment of a common organizational structure and presentation of information. For instance, Digital Imaging and Communications in Medicine (DICOM) specifies the preferred network communication rules and physical data formats to allow communication between human and modalities (Blazona & Koncar, 2007). HL7 standards would specify mechanisms and structure to describe and communicate clinical and administrative data (Blazona & Koncar, 2007). This includes communicating the clinical guidelines. Organizing clinical information can help to improve the quality and consistency of information. Such standards facilitate the sharing of information between people at various discrete levels (Lewis, 2002). In this case, individuals such as doctors, social workers, nurses and patients can share and understand the clinical guidelines for the diagnosis and treatment of the disease. Understanding EHR may be difficult for an average the user (Zeng-Treitler et al., 2007). Communication technologies ensure that the system uses a common language, which any user can understand. Use of relevant communication terminologies is essential to ensure that communication technologies work effectively. Clinical terms work by refining the information to structure clinical records and communicate meaningful information. They ensure the use of a structured vocabulary system and data capturing techniques that the system can understand. In this case, the guidelines would include terms related to iron overload, symptoms and possible remedies. Terminologies such as Systemized Nomenclature of Human and Veterinary Medicine (SNOMED) can help to index events (Cote et al., 1993). For example, they can index the events that transpire since the patient started consuming high amounts of iron up to the healing process. Communication terminologies can also resolve language variations. Structural components such as open EHR and archetypes collaborate with other components to provide information to the DSS. EHR architecture can faithfully capture the original meaning of information and provides an appropriate framework for enterprise and professionals to analyze EHRs (Kalra, 2006). It can also incorporate the necessary medico-legal constructs to promote safe and relevant communication. Archetypes help to specify a certain hierarchy of record component sub-classes (Kalra, 2006).

Communication technologies, medical terminologies and structural components play critical roles essential to deliver EHR to DSS. Effective communication is a common role for the three infrastructure components of EHR. EHR is the information basis of and interoperable health information system (Blobel, 2006). They must provide interoperability at the knowledge level and meet ethical, legal and organizational requirements. Consequently, communication technologies play a key role in passing knowledge to medical professionals and patients in a comprehensive manner. However, communication infrastructures differ from others in that they are standards that regulate communications. The use of terminologies is the starting point for representing knowledge in the health information domain (Beale, 2003). Therefore, terminologies serve the purpose of effective communication of clinical guidelines within the system. Lexicons of terms have evolved into semantic networks that encode relationships and internal classification. They use underlying ontologies to derive terms. The primary intention of terminologies is computational use such as guideline processing and decision support. When the clinician wants to record facts such as diagnosis, the terminology interface helps to extract a list of possible terms. In the provided case, some terminologies relating to iron overload include Poryphyria Cutanea Tarda (PCT) and Phlebotomy. These terms would send a message to the clinician to know which treatment to use on the patient. The structural component domain also promotes communication, but its main function is to enhance interoperability. It describes several approaches such as the reference information model and the open EHR. The former approach ensures that the clinician sends and receives information from another provider, thus ensuring interoperability (Garde et al., 2007). The latter is a technique for sharing evolving information in a way that the receiving provider can process (Garde et al., 2007). This enables segmenting interoperability. For example, a skin fragility archetype would represent a description of the information a clinician might want. This would help to express valid data types, values and structure.

Electronic health records provide a backdrop for the development of decision support systems. Therefore, it is critical to ensure that clinical guidelines are in consistent with expected communication technologies, terminologies and infrastructure components. These components aim and presenting knowledge and information in a comprehensive manner to both experts and common users.

List of References

Blazona, B., & Koncar, M. 2007. HL7 and DICOM based integration of radiology departments with healthcare enterprise information systems. International Journal of Medical Informatics, 76(3), S425.

Beale, T. 2003. Archetypes and the EHR. Studies in health technology and informatics, 238-246.

Blobel, B. G. M. E. 2006. Advanced EHR architectures-promises or reality. Methods of Information in Medicine, 45(1), 95.

Cote, R. A., Rothwell, R. S., Palotay, J. L., et al. 1993. The Systematized Nomenclature of Human and Veterinary Medicine–SNOMED International. Northfield, IL: College of American Pathologists.

Garde, S., Knaup, P., Hovenga, E. J., & Heard, S. 2007. Towards Semantic Interoperability for Electronic Health Records—Domain Knowledge Governance for open EHR Archetypes. Methods of information in medicine, 46(3), 332-343.

Gordon, C., & Christensen, J. P.1995. Health telematics for clinical guidelines and protocols (Vol. 16). IOS Press.

Haug, P. J., Rocha, B. H., & Rocha, R. A. 2007. Clinical decision support at Intermountain Healthcare. In Clinical decision support systems (pp. 159-189). Springer New York.

Kalra, D. 2006. Electronic health record standards. Yearb Med Inform, 136-144.

Lewis, A. 2002. Health informatics: information and communication. Advances in Psychiatric Treatment, 8(3), 165-171.

Zeng-Treitler, Q., Goryachev, S., Kim, H., Keselman, A., & Rosendale, D. 2007. Making texts in electronic health records comprehensible to consumers: a prototype translator. In AMIA Annual Symposium Proceedings 2007, p.846.