A basic issue in integrating nursing data standards with general standards for health care data within the HL7 RIM is to define the nursing domain. This article reports early attempts to model the nursing domain in the context of the HL7 RIM. Participants selected two representations of the nursing domain for modeling and mapping to the HL7 RIM. The first was the representation of the nursing process as a dynamic series of phases including the following:
- Data collection or assessment
- Diagnosis
- Identification of goals or desired outcomes
- Planning of interventions
- Implementation of treatment and care
- Evaluation
The second representation of the nursing domain to be mapped to the HL7 RIM was the very generic Nursing Information Reference Model (NIRM). The NIRM focuses on the information needs of nurses at clinical and higher (more abstract) levels, identifying a hierarchy of nursing information. At the base are atomic facts or findings about the patient. The second level consists of meta-observations such as nursing diagnoses, interventions, and outcomes and of the standardized vocabulary needed for naming them. The third level describes the aggregation of nursing diagnoses, interventions, and results into statistical reports at the institutional level for such purposes as management and quality improvement. Finally, the fourth level selects and aggregates nursing data from many institutions into population reports for public health and policy at national and international levels. Thus, the NIRM describes types of domain information in the nursing profession and its purposes. The challenge is to map such domain information, with its peculiarities, to the more comprehensive, non-discipline-specific health care information models.
The concept of nursing as a dynamic process and the hierarchy of information in the NIRM model provide useful perspectives on the nursing domain. Modeling these representations of the nursing domain consistently with the HL7 RIM will lay the groundwork for data exchange and semantic interoperability in electronic health records. For example, using this approach, the Dutch perinatology project combined the information management of general practitioners, midwives, medical specialists, and nurses.