LONG-TERM CARE STAFF DECISION-MAKING PROCESSES IN DETERMINING DAILY WELL-BEING OF RESIDENTS. (20th December 2022)

• Record Type: Journal Article
• Authors: Bowen, Mary (Libbey); Shin, Ju Young; Rowe, Meredeth
• Is Part Of: Innovation in aging. Volume 6(2022)Supplement 1
• Page Start: 699
• Page End: 700
• Publication Date: 2022-12-20
• Subjects: Aging -- Periodicals; Gerontology -- Periodicals; 612.67
• DOI: 10.1093/geroni/igac059.2561
• Languages: English
• ISSNs: 2399-5300

Abstract

Abstract: Much of the care provided to residents in long term care (LTC) comes from staff with minimal training, particularly in the area of the assessment of complex clinical presentations. This study utilized semi-structured focus group techniques with 25 clinical staff to understand how they determine whether a resident is functioning within or outside their daily "norm" and how they follow-up on these determinations. The overall finding was that each staff member develops an internally stored phenotype of each resident's norm. Three primary themes emerged: 1) the staff's phenotype becomes the 'gold standard' to determine whether there is a change and/or a cause for concern; 2) staff include sleep routines, fatigue, participation in usual activities, physical and mental status, and social interactions with others in their phenotypes. Staff reflect in what seems like a random manner through these comparisons, and, from this process, 3) a judgement emerges that helps inform clinical decision-making and potential action of the staff member. In most scenarios, staff decided there was no cause for concern. The identified weakness in this strategy was that staff rarely mentioned or used complementary and confirmatory formal assessment or referral mechanisms to ensure their judgment was correct. Thus, staff utilize complex multidimensional thinking and memory in decision-making but lack the skills or institutional structure to augment this with more formal and reliable techniques. This represents an interesting opportunity to build on existing assessment skills with additional types of assessment, technology-based information and formal referral mechanisms.