Abstract

Doc number: 244

Abstract

Background: To describe relationship patterns and management practices in nursing homes (NHs) that facilitate or pose barriers to better outcomes for residents and staff.

Methods: We conducted comparative, multiple-case studies in selected NHs (N = 4). Data were collected over six months from managers and staff (N = 406), using direct observations, interviews, and document reviews. Manifest content analysis was used to identify and explore patterns within and between cases.

Results: Participants described interaction strategies that they explained could either degrade or enhance their capacity to achieve better outcomes for residents; people in all job categories used these 'local interaction strategies'. We categorized these two sets of local interaction strategies as the 'common pattern' and the 'positive pattern' and summarize the results in two models of local interaction.

Conclusions: The findings suggest the hypothesis that when staff members in NHs use the set of positive local interaction strategies, they promote inter-connections, information exchange, and diversity of cognitive schema in problem solving that, in turn, create the capacity for delivering better resident care. We propose that these positive local interaction strategies are a critical driver of care quality in NHs. Our hypothesis implies that, while staffing levels and skill mix are important factors for care quality, improvement would be difficult to achieve if staff members are not engaged with each other in these ways.

Details

Title
Local interaction strategies and capacity for better care in nursing homes: a multiple case study
Author
Anderson, Ruth A; Toles, Mark P; Corazzini, Kirsten; McDaniel, Reuben R; Colón-Emeric, Cathleen
Pages
244
Publication year
2014
Publication date
2014
Publisher
BioMed Central
e-ISSN
14726963
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1537537662
Copyright
© 2014 Anderson et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.