The Application of a Falls Risk Index

This study examined the prospective use of a falls risk index. The research question was: To what extent do the intrinsic factors identified in the Tinetti et al. falls risk index predict which patients are likely to experience a fall. Hogue\u27s ecological model of falls in late life provided a conceptual framework for the study. Direct observation was used to collect baseline data from a convenience/purposive sample of 26 male patients in a midwest nursing home care unit with a rehabilitation focus. Patients were then assigned to one of three risk groups: yes-fall, 30% chance of fall, no-fall. Reports of patient falls were reviewed during the following four months. Data were analyzed by discriminant analysis and frequency tables. Actual occurrences were demonstrated to be consistent with predicted occurrences in the frequency tabulation, and 23/26 Participants were classified correctly by discriminant analysis. There are several considerations in the interpretation of this data: (1) over half the sample was in the predicted middle—risk group (30% chance of falls) which has limited clinical usefulness, (2) the discriminant analysis equation was developed from study data, and (3) no variable contributed significantly to risk of falling in the stepwise entrance of variables analysis. Nonetheless, predictability of the extremes (yes-fall or no-fall) using reproducible scales to evaluate risk factors was demonstrated, and may be useful clinically as well as in other studies of patient falls

OBCS: The Ontology of Biological and Clinical Statistics

Statistics play a critical role in biological and clinical research. To promote logically consistent representation and classification of statistical entities, we have developed the Ontology of Biological and Clinical Statistics (OBCS). OBCS extends the Ontology of Biomedical Investigations (OBI), an OBO Foundry ontology supported by some 20 communities. Currently, OBCS contains 686 terms, including 381 classes imported from OBI and 147 classes specific to OBCS. The goal of this paper is to present OBCS for community critique and to describe a number of use cases designed to illustrate its potential applications. The OBCS project and source code are available at http://obcs.googlecode.com

The Ontology of Biological and Clinical Statistics (OBCS) for standardized and reproducible statistical analysis

Statistics play a critical role in biological and clinical research. However, most reports of scientific results in the published literature make it difficult for the reader to reproduce the statistical analyses performed in achieving those results because they provide inadequate documentation of the statistical tests and algorithms applied. The Ontology of Biological and Clinical Statistics (OBCS) is put forward here as a step towards solving this problem. Terms in OBCS, including ‘data collection’, ‘data transformation in statistics’, ‘data visualization’, ‘statistical data analysis’, and ‘drawing a conclusion based on data’, cover the major types of statistical processes used in basic biological research and clinical outcome studies. OBCS is aligned with the Basic Formal Ontology (BFO) and extends the Ontology of Biomedical Investigations (OBI), an OBO (Open Biological and Biomedical Ontologies) Foundry ontology supported by over 20 research communities. We discuss two examples illustrating how the ontology is being applied. In the first (biological) use case, we describe how OBCS was applied to represent the high throughput microarray data analysis of immunological transcriptional profiles in human subjects vaccinated with an influenza vaccine. In the second (clinical outcomes) use case, we applied OBCS to represent the processing of electronic health care data to determine the associations between hospital staffing levels and patient mortality. Our case studies were designed to show how OBCS can be used for the consistent representation of statistical analysis pipelines under two different research paradigms. By representing statistics-related terms and their relations in a rigorous fashion, OBCS facilitates standard data analysis and integration, and supports reproducible biological and clinical research

Sagittal abdominal diameter and its socioeconomic correlates: perspective of sex differences

Background: Sagittal abdominal diameter (SAD) is an anthropometric index associated with visceral adiposity. It remains unclear whether SAD and its socio-economic correlates differ in women and men, which limits the epidemiological and clinical applications of the SAD measurement. The aims of this study are to examine the sex differences in SAD and its socio-economic correlates. Methods: A complex stratified multistage clustered sampling design was used to select 6975 men and 7079 women aged 18 years or more from the National Health Nutrition and Examination Survey 2011-2016, representative of the US civilian non-institutionalized population. SAD was measured in accordance to the standard protocols using a two-arm abdominal caliper. The sex differences in SAD and its socio-economic correlates were evaluated by performing weighted independent t tests and weighted multiple regression. Results: SAD was lower in women than in men in the entire sample, as well as in all the subgroups characterized by age, race, birth place, household income, and body mass index except for non-Hispanic blacks and those with household income < $20,000. Adjusted for other characteristics, age, birth place, household income, and body mass index were associated with SAD in both women and men. Black women were associated with higher SAD then white women (p < .0001), and Hispanic and Asian men were associated with lower SAD than white men (both p < .01). Women born in other countries were more likely to have lower SAD than women born in the US (p < .0001), and so were men (p = .0118). Both women and men with a household income of <$75,000 had higher SAD than those with an income of over $75,000. The associations of age, race, and household income with SAD differed in women and men. Conclusion: SAD is lower in women than in men, in the general population as well as in the most socio-economic subgroups. While socio-economic correlates of SAD are similar in women and men, the associations of age, race, and household income with SAD vary across sex

Architecture and usability of OntoKeeper, an ontology evaluation tool

Abstract Background The existing community-wide bodies of biomedical ontologies are known to contain quality and content problems. Past research has revealed various errors related to their semantics and logical structure. Automated tools may help to ease the ontology construction, maintenance, assessment and quality assurance processes. However, there are relatively few tools that exist that can provide this support to knowledge engineers. Method We introduce OntoKeeper as a web-based tool that can automate quality scoring for ontology developers. We enlisted 5 experienced ontologists to test the tool and then administered the System Usability Scale to measure their assessment. Results In this paper, we present usability results from 5 ontologists revealing high system usability of OntoKeeper, and use-cases that demonstrate its capabilities in previous published biomedical ontology research. Conclusion To the best of our knowledge, OntoKeeper is the first of a few ontology evaluation tools that can help provide ontology evaluation functionality for knowledge engineers with good usability.https://deepblue.lib.umich.edu/bitstream/2027.42/152214/1/12911_2019_Article_859.pd

Crossâ Network Directory Service: Infrastructure to enable collaborations across distributed research networks

IntroductionExisting largeâ scale distributed health data networks are disconnected even as they address related questions of healthcare research and public policy. This paper describes the design and implementation of a fully functional prototype openâ source tool, the Crossâ Network Directory Service (CNDS), which addresses much of what keeps distributed networks disconnected from each other.MethodsThe set of services needed to implement a Crossâ Directory Service was identified through engagement with stakeholders and workgroup members. CNDS was implemented using PCORnet and Sentinel network instances and tested by participating data partners.ResultsWeb services that enable the four major functional features of the service (registration, discovery, communication, and governance) were developed and placed into an openâ source repository. The services include a robust metadata model that is extensible to accommodate a virtually unlimited inventory of metadata fields, without requiring any further software development. The user interfaces are programmatically generated based on the contents of the metadata model.ConclusionThe CNDS pilot project gathered functional requirements from stakeholders and collaborating partners to build a software application to enable crossâ network data and resource sharing. The two partnersâ one from Sentinel and one from PCORnetâ tested the software. They successfully entered metadata about their organizations and data sources and then used the Discovery and Communication functionality to find data sources of interest and send a crossâ network query. The CNDS software can help integrate disparate health data networks by providing a mechanism for data partners to participate in multiple networks, share resources, and seamlessly send queries across those networks.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149237/1/lrh210187.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149237/2/lrh210187_am.pd

Coordinated Evolution of Ontologies of Informed Consent

Informed consent, whether for health or behavioral research or clinical treatment, rests on notions of voluntarism, information disclosure and understanding, and the decisionmaking capacity of the person providing consent. Whether consent is for research or treatment, informed consent serves as a safeguard for trust that permissions given by the research participant or patient are upheld across the informed consent (IC) lifecycle. The IC lifecycle involves not only documentation of the consent when originally obtained, but actions that require clear communication of permissions from the initial acquisition of data and specimens through handoffs to, for example, secondary researchers, allowing them access to data or biospecimens referenced in the terms of the original consent

Development of User-Centered Interfaces to Search the Knowledge Resources of the Virginia Henderson International Nursing Library

The primary aim of this collaborative research project was to develop "tell and ask" functional interface where the nurse communicates with the knowledge base by making logical assertions based on his/her domain knowledge