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

Research output: Contribution to journalArticle

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 languageEnglish (US)
Pages (from-to)58-80
Number of pages23
JournalResearch and theory for nursing practice
Volume33
Issue number1
DOIs
StatePublished - Feb 1 2019

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Electronic Health Records
Signs and Symptoms
Nursing
Survivors
Nursing Assessment
Documentation

Keywords

  • data-driven research
  • older adults
  • problems
  • strengths
  • the Omaha System

PubMed: MeSH publication types

  • Journal Article

Cite this

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title = "Discovering Associations Among Older Adults' Characteristics and Planned Nursing Interventions Using Electronic Health Record Data",
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.",
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author = "Grace Gao and Kerr, {Madeleine J.} and Lindquist, {Ruth A.} and Chi, {Chih Lin} and Mathiason, {Michelle A.} and Monsen, {Karen A.}",
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AU - Kerr, Madeleine J.

AU - Lindquist, Ruth A.

AU - Chi, Chih Lin

AU - Mathiason, Michelle A.

AU - Monsen, Karen A.

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N2 - 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.

AB - 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.

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