15 research outputs found
Nursing Terminologies as Evolving Large-Scale Information Infrastructures
This paper describes the slowly evolving nature of large-scale terminology-based information infrastructures. The strategic aim of implementing standardized terminologies is to share and compare information within and across domain-specific and organizational boundaries. We are particularly interested in working classification systems focused on specific domains’ and classes, and even more specifically in reference terminologies with the capability to interconnect different existing classification systems. We examine this empirically through a threefold case based on data from three Norwegian university hospitals, where we also track a national recommendation of a reference terminology. The reference terminology, which was initially promoted as a means to achieve integration and harmonization, is increasingly perceived as competing with other terminologies. This “gateway” has been presented as a purely technical and politically neutral system, but may be more complex in reality: such integration processes require considerable adaptations, negotiations, and manual maintenance
Understanding the use of standardized nursing terminology and classification systems in published research : a case study using the International Classification for Nursing Practice®
Background
In the era of evidenced based healthcare, nursing is required to demonstrate that care provided by nurses is associated with optimal patient outcomes, and a high degree of quality and safety. The use of standardized nursing terminologies and classification systems are a way that nursing documentation can be leveraged to generate evidence related to nursing practice. Several widely-reported nursing specific terminologies and classifications systems currently exist including the Clinical Care Classification System, International Classification for Nursing Practice®, Nursing Intervention Classification, Nursing Outcome Classification, Omaha System, Perioperative Nursing Data Set and NANDA International. However, the influence of these systems on demonstrating the value of nursing and the professions’ impact on quality, safety and patient outcomes in published research is relatively unknown.
Purpose
This paper seeks to understand the use of standardized nursing terminology and classification systems in published research, using the International Classification for Nursing Practice® as a case study.
Methods
A systematic review of international published empirical studies on, or using, the International Classification for Nursing Practice® were completed using Medline and the Cumulative Index for Nursing and Allied Health Literature.
Results
Since 2006, 38 studies have been published on the International Classification for Nursing Practice®. The main objectives of the published studies have been to validate the appropriateness of the classification system for particular care areas or populations, further develop the classification system, or utilize it to support the generation of new nursing knowledge. To date, most studies have focused on the classification system itself, and a lesser number of studies have used the system to generate information about the outcomes of nursing practice.
Conclusions
Based on the published literature that features the International Classification for Nursing Practice, standardized nursing terminology and classification systems appear to be well developed for various populations, settings and to harmonize with other health-related terminology systems. However, the use of the systems to generate new nursing knowledge, and to validate nursing practice is still in its infancy. There is an opportunity now to utilize the well-developed systems in their current state to further what is know about nursing practice, and how best to demonstrate improvements in patient outcomes through nursing care
Mining the Medical and Patent Literature to Support Healthcare and Pharmacovigilance
Recent advancements in healthcare practices and the increasing use of information technology in the medical domain has lead to the rapid generation of free-text data in forms of scientific articles, e-health records, patents, and document inventories. This has urged the development of sophisticated information retrieval and information extraction technologies. A fundamental requirement for the automatic processing of biomedical text is the identification of information carrying units such as the concepts or named entities. In this context, this work focuses on the identification of medical disorders (such as diseases and adverse effects) which denote an important category of concepts in the medical text. Two methodologies were investigated in this regard and they are dictionary-based and machine learning-based approaches. Futhermore, the capabilities of the concept recognition techniques were systematically exploited to build a semantic search platform for the retrieval of e-health records and patents. The system facilitates conventional text search as well as semantic and ontological searches. Performance of the adapted retrieval platform for e-health records and patents was evaluated within open assessment challenges (i.e. TRECMED and TRECCHEM respectively) wherein the system was best rated in comparison to several other competing information retrieval platforms. Finally, from the medico-pharma perspective, a strategy for the identification of adverse drug events from medical case reports was developed. Qualitative evaluation as well as an expert validation of the developed system's performance showed robust results. In conclusion, this thesis presents approaches for efficient information retrieval and information extraction from various biomedical literature sources in the support of healthcare and pharmacovigilance. The applied strategies have potential to enhance the literature-searches performed by biomedical, healthcare, and patent professionals. The applied strategies have potential to enhance the literature-searches performed by biomedical, healthcare, and patent professionals. This can promote the literature-based knowledge discovery, improve the safety and effectiveness of medical practices, and drive the research and development in medical and healthcare arena
Towards a system of concepts for Family Medicine. Multilingual indexing in General Practice/ Family Medicine in the era of Semantic Web
UNIVERSITY OF LIÈGE, BELGIUM
Executive Summary
Faculty of Medicine
Département Universitaire de Médecine Générale.
Unité de recherche Soins Primaires et Santé
Doctor in biomedical sciences
Towards a system of concepts for Family Medicine.
Multilingual indexing in General Practice/ Family Medicine in the era
of SemanticWeb
by Dr. Marc JAMOULLE
Introduction
This thesis is about giving visibility to the often overlooked work of family
physicians and consequently, is about grey literature in General Practice
and Family Medicine (GP/FM). It often seems that conference organizers
do not think of GP/FM as a knowledge-producing discipline that deserves
active dissemination. A conference is organized, but not much is done with
the knowledge shared at these meetings. In turn, the knowledge cannot be
reused or reapplied. This these is also about indexing. To find knowledge
back, indexing is mandatory. We must prepare tools that will automatically
index the thousands of abstracts that family doctors produce each year in
various languages. And finally this work is about semantics1. It is an introduction
to health terminologies, ontologies, semantic data, and linked
open data. All are expressions of the next step: Semantic Web for health
care data. Concepts, units of thought expressed by terms, will be our target
and must have the ability to be expressed in multiple languages. In turn,
three areas of knowledge are at stake in this study: (i) Family Medicine as a
pillar of primary health care, (ii) computational linguistics, and (iii) health
information systems.
Aim
• To identify knowledge produced by General practitioners (GPs) by
improving annotation of grey literature in Primary Health Care
• To propose an experimental indexing system, acting as draft for a
standardized table of content of GP/GM
• To improve the searchability of repositories for grey literature in GP/GM.
1For specific terms, see the Glossary page 257
x
Methods
The first step aimed to design the taxonomy by identifying relevant concepts
in a compiled corpus of GP/FM texts. We have studied the concepts
identified in nearly two thousand communications of GPs during
conferences. The relevant concepts belong to the fields that are focusing
on GP/FM activities (e.g. teaching, ethics, management or environmental
hazard issues).
The second step was the development of an on-line, multilingual, terminological
resource for each category of the resulting taxonomy, named
Q-Codes. We have designed this terminology in the form of a lightweight
ontology, accessible on-line for readers and ready for use by computers of
the semantic web. It is also fit for the Linked Open Data universe.
Results
We propose 182 Q-Codes in an on-line multilingual database (10 languages)
(www.hetop.eu/Q) acting each as a filter for Medline. Q-Codes are also available
under the form of Unique Resource Identifiers (URIs) and are exportable
in Web Ontology Language (OWL). The International Classification of Primary
Care (ICPC) is linked to Q-Codes in order to form the Core Content
Classification in General Practice/Family Medicine (3CGP). So far, 3CGP is
in use by humans in pedagogy, in bibliographic studies, in indexing congresses,
master theses and other forms of grey literature in GP/FM. Use by
computers is experimented in automatic classifiers, annotators and natural
language processing.
Discussion
To the best of our knowledge, this is the first attempt to expand the ICPC
coding system with an extension for family physician contextual issues,
thus covering non-clinical content of practice. It remains to be proven that
our proposed terminology will help in dealing with more complex systems,
such as MeSH, to support information storage and retrieval activities.
However, this exercise is proposed as a first step in the creation of an ontology
of GP/FM and as an opening to the complex world of Semantic Web
technologies.
Conclusion
We expect that the creation of this terminological resource for indexing abstracts
and for facilitating Medline searches for general practitioners, researchers
and students in medicine will reduce loss of knowledge in the
domain of GP/FM. In addition, through better indexing of the grey literature
(congress abstracts, master’s and doctoral theses), we hope to enhance
the accessibility of research results and give visibility to the invisible work
of family physicians