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. 2019 Feb 1;33(1):58-80.
doi: 10.1891/1541-6577.33.1.58.

Discovering Associations Among Older Adults' Characteristics and Planned Nursing Interventions Using Electronic Health Record Data

Grace Gao  1 , Madeleine J Kerr  1 , Ruth A Lindquist  1 , Chih-Lin Chi  1 , Michelle A Mathiason  1 , Karen A Monsen  1
Affiliations

Discovering Associations Among Older Adults' Characteristics and Planned Nursing Interventions Using Electronic Health Record Data

Grace Gao et al. Res Theory Nurs Pract. .

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.

Keywords: data-driven research; older adults; problems; strengths; the Omaha System.

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Conflict of interest statement

Disclosure. The authors have no relevant financial interest or affiliations with any commercial interests related to the subjects discussed within this article.

Figures

Figure 1.
Figure 1.
Latent class analysis groups by strengths. Note. Interpersonal = Interpersonal relationship; NMS function = Neuromusculoskeletal function; Speech = Speech and language; Community resources = Communication with community resources; Health supervision = Healthcare supervision; Sleep = Sleep and rest patterns; Digestion = Digestion-hydration
Figure 2.
Figure 2.
Latent class analysis groups by signs/symptoms. Note. Community resources = Communication with community resources; NMS function = Neuro-musculo-skeletal function; Health supervision = Health care supervision; Speech = Speech and language; Interpersonal = Interpersonal relationship; Digestion = Digestion-hydration
Figure 3.
Figure 3.
Overall findings by group.
Figure 4.
Figure 4.
Interventions by problem concept for the three groups. Note. NMS function = Neuromusculoskeletal function; Health supervision = Healthcare supervision; Neighborhood = Neighborhood/workplace safety; Interpersonal = Interpersonal relationship; Sleep = Sleep and rest patterns; Community resources = Communication with community resources; Speech = Speech and language. *significant statistical differences p < .05.
Figure 5.
Figure 5.
Planned interventions by categories and by percentage of residents. *significant statistical difference.
See this image and copyright information in PMC

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References

    1. Agency for Healthcare Research and Quality. (2012). Prospects for care coordination measurement using electronic data sources (Publication No. 12–0014-EF). Washington, DC: AHRQ.
    1. American Medical Informatics Association (AMIA). (2017). Redefining our picture of health: Towards a person-centered integrated care, research, wellness, and community ecosystem. A white paper of the 2017 AMIA Policy Invitational; Retrieved from https://www.amia.org/sites/default/files/API-2017-White-Paper-Redefining...
    1. Banning M (2008). A review of clinical decision making: Models and current research. Journal of Clinical Nursing, 17(2), 187–95. - PubMed
    1. Das R (2015, August 11). A silver tsunami invades the health of nations. Forbes. Retrived from https://www.forbes.com/sites/reenitadas/2015/08/11/a-silver-tsunami-inva...
    1. Federal Interagency Forum on Aging-Related Statistics. (2016). Older Americans 2016: Key indicators of well-being. Federal Interagency Forum on Aging-Related Statistics. Washington, DC: U.S. Government Printing Office.

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