Linking Environments and Resident Function via MDS

Abstract Over the past three decades, research in long-term care settings has demonstrated links between design characteristics and the experiences of residents who live in these environments. Individual studies have shown how different approaches to the design of the built environment can contribute to enhanced resident safety, function, and even care outcomes but these findings have been difficult to generalize due to the lack of a validated and comprehensive assessment tool that provides a consistent metric for the discrete environmental characteristics that may be contributing factors. In addition, existing environmental tools have limited demonstrated connections to other widely used assessment tools for care outcomes such as the Minimum Data Set (MDS) the standard for facilitating care management in nursing homes. The Environmental Audit Scoring Evaluation (EASE) tool has been shown to provide a reliable set of comprehensive scoring criteria that can measure the strengths (or weaknesses) of specific design features. Further, the EASE tool items are comprised of features that specifically support quality outcomes measures that are also of focus of the MDS. In this paper, we describe the study design to link the MDS assessments of 235 residents to the EASE assessments of their (15) distinct living areas across seven skilled care buildings.

Authors

Institutions

Publication Details

Journal
Innovation in Aging
Published
2025-12-01
DOI
https://doi.org/10.1093/geroni/igaf122.622
Primary Topic
Geriatric Care and Nursing Homes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Linking Environments and Resident Function via MDS

Robert Wrublowsky, Migette L. Kaup, Margaret Calkins, Adam Davey
Innovation in Aging
Geriatric Care and Nursing Homes
article

Linking Environments and Resident Function via MDS

Robert Wrublowsky, Migette L. Kaup, Margaret Calkins, Adam Davey
article en

Abstract

Abstract Over the past three decades, research in long-term care settings has demonstrated links between design characteristics and the experiences of residents who live in these environments. Individual studies have shown how different approaches to the design of the built environment can contribute to enhanced resident safety, function, and even care outcomes but these findings have been difficult to generalize due to the lack of a validated and comprehensive assessment tool that provides a consistent metric for the discrete environmental characteristics that may be contributing factors. In addition, existing environmental tools have limited demonstrated connections to other widely used assessment tools for care outcomes such as the Minimum Data Set (MDS) the standard for facilitating care management in nursing homes. The Environmental Audit Scoring Evaluation (EASE) tool has been shown to provide a reliable set of comprehensive scoring criteria that can measure the strengths (or weaknesses) of specific design features. Further, the EASE tool items are comprised of features that specifically support quality outcomes measures that are also of focus of the MDS. In this paper, we describe the study design to link the MDS assessments of 235 residents to the EASE assessments of their (15) distinct living areas across seven skilled care buildings.

Innovation in AgingVol. 9(Supplement_2)
Kansas State University (US), Research Manitoba (CA), Cleveland Heights University Heights Public Library (US), University of Delaware (US)
Sustainable cities and communities
Openalex Percentile: Top 21%
Geriatric Care and Nursing Homes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.