Abstract
BACKGROUND AND PURPOSE: Little is known about how nursing assessments of strengths and signs/symptoms inform intervention planning in assisted living communities. The purpose of this study was to discover associations among older adults' characteristics and their planned nursing interventions. METHODS: This study employed a data-driven method, latent class analysis, using existing electronic health record data from a senior living community in the Midwest. A convenience sample comprised de-identified data of well-being assessments and care plans for 243 residents. Latent class analysis, descriptive, and inferential statistics were used to group the sample, summarize strengths and problems attributes, nursing interventions, and Knowledge, Behavior, and Status scores, and detect differences. RESULTS: Three groups presented based on patterns of strengths and signs/symptoms combined with problem concepts: Living Well (n = 95) had more strengths and fewer signs/symptoms; Lower Strengths (n = 99) had fewer strengths and more signs/symptoms; and Resilient Survivors (n = 49) had more strengths and more signs/symptoms. Some associations were found among group characteristics and planned interventions. Living Well had the lowest average number of planned interventions per resident (Mean = 2.7; standard deviation [SD] = 1.7) followed by Lower Strengths (Mean = 3.8; SD = 2.6) and Resilient Survivors (Mean = 4.1; SD = 3.4). IMPLICATIONS FOR PRACTICE: This study offers new knowledge in the use of a strengths-based ontology to facilitate a nursing discourse that leverages use of older adults' strengths to address their problems and support their living a healthier life. It also offers the potential to complement the problem-based infrastructure in clinical practice and documentation.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 58-80 |
| Number of pages | 23 |
| Journal | Research and theory for nursing practice |
| Volume | 33 |
| Issue number | 1 |
| DOIs | |
| State | Published - Feb 1 2019 |
Bibliographical note
Funding Information:The first author is a recipient of the Robert Wood Johnson Foundation Future of Nursing Scholar award for her PhD study in nursing at the University of Minnesota. This research received no other specific grant from any funding agency in the public, commercial, or not-for-profit sectors. The authors also acknowledge Robin Austin for her review of the mapping to the Omaha System, Sasank Maganti for de-identifying the EHR data, and Mary Jo Kreitzer and Katherine Todd for their collaboration in the provision of the EHR data for this research.
Publisher Copyright:
© 2019 Springer Publishing Company.
Keywords
- data-driven research
- older adults
- problems
- strengths
- the Omaha System
PubMed: MeSH publication types
- Journal Article
- Research Support, Non-U.S. Gov't