Browsing by Subject "data analysis"

Now showing 1 - 5 of 5
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    Coincidence Analysis: A Novel Approach to Modeling Nurses' Workplace Experience
    (Thieme, 2022-08) Womack, Dana M.; Miech, Edward J.; Fox, Nicholas J.; Silvey, Linus C.; Somerville, Anna M.; Eldredge, Deborah H.; Steege, Linsey M.; School of Nursing
    Objectives  The purpose of this study is to identify combinations of workplace conditions that uniquely differentiate high, medium, and low registered nurse (RN) ratings of appropriateness of patient assignment during daytime intensive care unit (ICU) work shifts. Methods  A collective case study design and coincidence analysis were employed to identify combinations of workplace conditions that link directly to high, medium, and low RN perception of appropriateness of patient assignment at a mid-shift time point. RN members of the study team hypothesized a set of 55 workplace conditions as potential difference makers through the application of theoretical and empirical knowledge. Conditions were derived from data exported from electronic systems commonly used in nursing care. Results  Analysis of 64 cases (25 high, 24 medium, and 15 low) produced three models, one for each level of the outcome. Each model contained multiple pathways to the same outcome. The model for “high” appropriateness was the simplest model with two paths to the outcome and a shared condition across pathways. The first path comprised of the absence of overtime and a before-noon patient discharge or transfer, and the second path comprised of the absence of overtime and RN assignment to a single ICU patient. Conclusion  Specific combinations of workplace conditions uniquely distinguish RN perception of appropriateness of patient assignment at a mid-shift time point, and these difference-making conditions provide a foundation for enhanced observability of nurses' work experience during hospital work shifts. This study illuminates the complexity of assessing nursing work system status by revealing that multiple paths, comprised of multiple conditions, can lead to the same outcome. Operational decision support tools may best reflect the complex adaptive nature of the work systems they intend to support by utilizing methods that accommodate both causal complexity and equifinality.
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    Methods for Medical Student Research Projects
    (2024-05-20) Dolan, Levi; Han, Amy
    Symposium participation by invitation, no abstract submitted.
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    Qualitative Coding and Thematic Analysis of Semi-Structured Interviews: Individuals Expressions Related to Copyright Issues
    (2020-02-23) Piper, Gemmicka; Maixner, Gary
    Thematic analysis of interviews conducted to identify patterns in faculty and student thinking around copyright.
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    SAVI Community Information System
    (Office of the Vice Chancellor for Research, 2011-04-08) Derr, Michelle
    SAVI helps organizations and researchers make data-informed decisions by 1) providing reliable data about Central Indiana communities; 2) creating actionable information; 3) developing tools for data analysis; and 4) building capacity, especially for nonprofit and community-based organizations, to use data effectively. The SAVI Community Information System is the nation’s largest spatially-enabled system of its type, providing detailed, geographically precise information needed to make data-informed decisions. SAVI contains a wealth of free data about the social, physical, and economic conditions of Central Indiana communities from counties to neighborhoods and census tracts, as well as information on thousands of non-profit and community-based organizations and programs. SAVI is a donor-supported, web-based system (www.savi.org) that allows users to create custom maps, graphs, charts, and data profiles of over 2,000 Central Indiana communities. SAVI supports research: selecting appropriate study area; identifying community-based research partners; identifying and managing nurse-led community health activities; understanding health effects of neighborhood poverty; identifying health disparities; environmental health/environmental justice; identifying socio-spatial health knowledge networks; and understanding social and physical neighborhood context and influences on obesity, leukemia treatment adherence, cancer screening rates, asthma, diabetes, and STDs. SAVI also supports community research: identifying community assets, assessing needs, planning and evaluating programs, identifying collaborators, supporting grant applications, strategic planning, and visualizing patterns and trends. This hands-on exhibit will showcase SAVI and the ways in which it can support community and researcher decisionmaking needs. We will present a poster and have live demonstrations of our interactive website that provides a wealth of data and analysis tools.
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    The Evolution of an Electronic Lab Notebook Community
    (2024-05-21) Dolan, Levi; Whipple, Elizabeth C.
    Electronic Lab Notebook (ELN) products are intended to replace physical lab notebooks in basic science and clinical research labs. As part of supporting rigor and reproducibility in biomedical research practices, our library supports ELN implementation at our institution. We investigated how ELNs are currently being implemented by analyzing backend ELN usage data, then used the results to reach out to super users. Based on their feedback, we created a shared electronic lab notebook with reusable components and sponsored a training event led by LabArchives product staff. This sequence of library outreach and programming activities has increased the library’s understanding of our ELN community and diversified our methods for advancing best practices in data management.