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1.  Collaborative development and maintenance of health terminologies 
The quest for a standardized terminology that can meet the varying needs of healthcare practice, and requirements for secondary use, is ongoing. The number of potential users and the number of potential uses for standardized terminologies make collaborative development, rather than the traditional de jure approach, an imperative, and there appears to be significant worldwide interest in this area. In this article we describe an initiative of the International Council of Nurses (ICN), ICNP C-Space (Collaborative Space), which utilized a social media platform to encourage and facilitate global collaborative development of its terminology, the International Classification for Nursing Practice (ICNP®). We report on several years of experience of managing the platform and provide valuable lessons on collaborative terminology development. Our experience suggests that web-based platforms such as ICNP C-Space certainly offer the promise of a broader, wider-reaching, and more inclusive community of contributors to the terminology development process. However, there are also potential limitations for which we provide practical recommendations.
PMCID: PMC3900200  PMID: 24551359
2.  Semantic Mappings and Locality of Nursing Diagnostic Concepts in UMLS 
One solution for enhancing the interoperability between nursing information systems, given the availability of multiple nursing terminologies, is to cross-map existing nursing concepts. The Unified Medical Language System (UMLS) developed and distributed by the National Library of Medicine (NLM) is a knowledge resource containing cross-mappings of various terminologies in a unified framework. While the knowledge resource has been available for the last two decades, little research on the representation of nursing terminologies in UMLS has been conducted. As a first step, UMLS semantic mappings and concept locality were examined for nursing diagnostic concepts or problems selected from three terminologies (i.e., CCC, ICNP, and NANDA-I) along with corresponding SNOMED CT concepts. The evaluation of UMLS semantic mappings was conducted by measuring the proportion of concordance between UMLS and human expert mappings. The semantic locality of nursing diagnostic concepts was assessed by examining the associations of select concepts and the placement of the nursing concepts on the Semantic Network and Group. The study found that the UMLS mappings of CCC and NANDA-I concepts to SNOMED CT were highly concordant to expert mappings. The level of concordance in mappings of ICNP to SNOMED CT, CCC and NANDA-I within UMLS was relatively low, indicating the need for further research and development. Likewise, the semantic locality of ICNP concepts could be further improved. Various stakeholders need to collaborate to enhance the NLM knowledge resource and the interoperability of nursing data within the discipline as well as across health-related disciplines.
PMCID: PMC3272126  PMID: 21951759
Unified Medical Language System; Standardized Nursing Terminology; Semantic Mapping; Nursing Knowledge Representation; Health Informatics
3.  Magnetic Bionanoparticle Enhances Homing of Endothelial Progenitor Cells in Mouse Hindlimb Ischemia 
Korean Circulation Journal  2012;42(6):390-396.
Background and Objectives
Poor homing efficiency is one of the major limitations of current stem cell therapy. Magnetic bionanoparticles (MPs) obtained from Magnetospirillum sp. AMB-1 have a lipid bilayer membrane and ferromagnetic properties. We evaluated a novel priming strategy using MPs to enhance the homing of transplanted progenitor cells to target tissue.
Materials and Methods
Effects of MP on proliferation, viability, and migration of late human endothelial progenitor cells (EPCs) were examined in vitro. Additionally, effects of MP on gene and protein expression related to survival and adhesion were evaluated. Homing and angiogenic efficiency of MP transferred late EPCs was evaluated in nude mouse hindlimb ischemia model.
Below threshold concentration, MP transfer did not influence proliferation or survival of late EPCs, but enhanced migration and trans-endothelial migration of late EPCs toward magnet. Below threshold concentration, MP transfer did not influence gene and protein expression related to survival. In the mouse hindlimb ischemia model, late EPCs treated with high dose MP (5 ug/mL) showed enhanced homing of injected late EPCs in the ischemic limb by magnet, compared to low dose MP (1 ug/mL) treated late EPCs. In addition, high dose MP transferred EPC showed significantly better improvement of perfusion in ischemic limb compared to untreated EPC.
MP transfer with magnet application can be a promising novel strategy to enhance homing efficacy and outcomes of current stem cell therapy.
PMCID: PMC3390424  PMID: 22787469
Nanoparticles; Stem cells; Ischemia
4.  Representation of Nursing Terminologies in UMLS 
There are seven nursing terminologies or classifications that are considered a standard to support nursing practice in the U.S. Harmonizing these terminologies will enhance the interoperability of clinical data documented across nursing practice. As a first step to harmonize the nursing terminologies, the purpose of this study was to examine how nursing problems or diagnostic concepts from select terminologies were cross-mapped in Unified Medical Language System (UMLS). A comparison analysis was conducted by examining whether cross-mappings available in UMLS through concept unique identifiers were consistent with cross-mappings conducted by human experts. Of 423 concepts from three terminologies, 411 (97%) were manually cross-mapped by experts to the International Classification for Nursing Practice. The UMLS semantic mapping among the 411 nursing concepts presented 33.6% accuracy (i.e., 138 of 411 concepts) when compared to expert cross-mappings. Further research and collaboration among experts in this field are needed for future enhancement of UMLS.
PMCID: PMC3243214  PMID: 22195127
5.  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 20th 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.
PMCID: PMC3243282  PMID: 22195109
6.  Clinician Adoption Patterns and Patient Outcome Results in Use of Evidence-Based Nursing Plans of Care 
Delivery of safe, effective and appropriate health care is an imperative facing health care organizations globally. While many initiatives have been launched in a number of countries to address this need from a medical perspective, a similar focus for generating evidence-based nursing knowledge has been missing [1]. This paper reports on a collaborative evidence-based practice (EBP) research initiative that adds nursing knowledge into computerized care protocols. Here, a brief overview of the study’s aims, purpose and methodology is presented as well as results of data analysis and lessons learned. The research team examined nurses’ adoption patterns of EBP recommendations with respect to activity tolerance using four-month patient data collected from a pilot hospital. Study findings indicate a need for more focus on the system design and implementation process with the next rollout phase to promote evidence-based nursing practice.
PMCID: PMC2655848  PMID: 18693871
Nursing knowledge; evidence-based practice; nursing standard terminology; nursing dataset; information technology infrastructure; clinician adoption
7.  Predictive Modeling for the Prevention of Hospital-Acquired Pressure Ulcers 
A one-to-one case control study was conducted on a pre-existing dataset to examine a predictive model with a set of risk factors for pressure ulcer development in acute care settings. Various techniques were used to select the most relevant predictors from ten subsets of a pre-existing dataset. The predictors identified were further examined using ten additional subsets by measuring sensitivities, specificities, positive/negative predictive values, and the areas under the ROC (receiver operating characteristic) curves. The best components for identifying at-risk patients consisted of three Braden subscales and five risk factors routinely collected through electronic health records. Entering these eight predictors into the logistic regression model yielded a sensitivity of 92%, a specificity of 67%, and an area under the ROC curve of 89%. Further evaluation, however, is needed to explore the validity of the model.
PMCID: PMC1839359  PMID: 17238378

Results 1-7 (7)