NI2012 Classification of Reasons for Hospital Readmission.

Hospital readmission is a focus of efforts to improve quality and reduce cost in our healthcare system. Use of a standard readmission classification in a clinical information system would facilitate examination and analysis of reasons for hospital readmission and provide direction for targeting interventions. The purpose of this quality improvement project was to examine coverage of reasons for readmission in three existing classification schemes compared with a "gold standard" conceptual framework. Data were obtained from five data sources about reasons for readmission for a select group of patients using a modified Institute for Healthcare Improvement (IHI) tool. Both the structure and the level of granularity of the three classifications had an impact on the classification of reasons. Between 53% and 65% of the reasons for readmission could be coded in the three readmission classifications, leaving 35% to 47% of the reasons uncoded, when compared with the conceptual framework.

A dynamic classification approach for nursing.

Nursing has a long tradition of classification, stretching back at least 150 years. The introduction of computers into health care towards the end of the 20(th) Century helped to focus efforts, culminating in the development of a range of standardized classifications. Many of these classifications are still in use today and, while content is periodically updated, the underlying classification structures remain relatively static. In this paper an approach to classification that is relatively new to nursing is presented; an approach that uses formal Web Ontology Language definitions for classes, and computer-based reasoning on those classes, to determine automatically classification structures that more flexibly meet the needs of users. A new proposed classification structure for the International Classification for Nursing Practice is derived under the new approach to provide a new view on the next release of the classification and to contribute to broader quality improvement processes.

Mapping nursing concepts to ontologies for evidence-based nursing.

In this paper we describe a project to map natural language expressions of nursing-related concepts to standard ontologies in support of an evidence-based nursing initiative. Natural language concept expressions are identified from syntheses of nursing knowledge and mapped to ICNP and SNOMED-CT.