Nursing constraint models for electronic health records: a vision for domain knowledge governance.
Various forms of electronic health records (EHRs) are currently being introduced in several countries. Nurses are primary stakeholders and need to ensure that their information and knowledge needs are being met by such systems information sharing between health care providers to enable them to improve the quality and efficiency of health care service delivery for all subjects of care. The latest international EHR standards have adopted the openEHR approach of two-level modelling. The first level is a stable information model determining structure, while the second level consists of constraint models or 'archetypes' that reflect the specifications or clinician rules for how clinical information needs to be represented to enable unambiguous data sharing. The current state of play in terms of international health informatics standards development activities is providing the nursing profession with a unique opportunity and challenge. Much work has been undertaken internationally in the area of nursing terminologies and evidence-based practice. This paper argues that to make the most of these emerging technologies and EHRs we must now concentrate on developing a process to identify, document, implement, manage and govern our nursing domain knowledge as well as contribute to the development of relevant international standards. It is argued that one comprehensive nursing terminology, such as the ICNP or SNOMED CT is simply too complex and too difficult to maintain. As the openEHR archetype approach does not rely heavily on big standardised terminologies, it offers more flexibility during standardisation of clinical concepts and it ensures open, future-proof electronic health records. We conclude that it is highly desirable for the nursing profession to adopt this openEHR approach as a means of documenting and governing the nursing profession's domain knowledge. It is essential for the nursing profession to develop its domain knowledge constraint models (archetypes) collaboratively in an international context.
Hovenga
Evelyn
E
School of Information Systems, Health Informatics Research Group, Faculty of Informatics and Communication, Central Queensland University, Rockhampton MC, Qld 4702, Australia.
Garde
Sebastian
S
Heard
Sam
S
D001185:Artificial Intelligence; D003628:Database Management Systems; D016208:Databases, Factual; D020000:Decision Support Systems, Clinical; D007722:Health Knowledge, Attitudes, Practice; D016247:Information Storage and Retrieval / Q000379:methods*; D016347:Medical Records Systems, Computerized; D008962:Models, Theoretical; D048108:Nursing Informatics / Q000379:methods*; D017009:Professional Autonomy; D014584:User-Computer Interface