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Record W4395010587 · doi:10.1007/s41999-024-00973-4

How comprehensive is our comprehensive geriatric assessment in clinical practice? An Irish perspective

2024· article· en· W4395010587 on OpenAlexaboutno aff
Karen Dennehy, Amy Lynch, Catriona Reddin, Bart Daly, Tim Dukelow, Michelle Canavan, Maria Costello, Robert Murphy

Bibliographic record

VenueEuropean Geriatric Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
FundersUniversity College CorkIrish Research eLibrary
KeywordsMedicineBaseline (sea)MoodIrishGerontologyMontreal Cognitive AssessmentGeriatricsPhysical therapyCognitive impairmentFamily medicineCognitionPsychiatry

Abstract

fetched live from OpenAlex

PURPOSE: Comprehensive geriatric assessment (CGA) is the cornerstone of high-quality care for older adults. There is no current gold standard to guide what should be included as the baseline measure for CGAs. We examined what metrics are being captured in CGA baseline assessments completed by community based integrated care teams in Ireland. METHODS: CGA's care pathways in Ireland are usually initiated with a written document that establish patients baseline in various assessment areas. These documents were the focus of this study. We completed a cross-sectional study of the components captured in CGA baseline assessments completed in a community setting. We contacted operational leads in each of the community health organisations in Ireland and requested a copy of their current initial baseline screening document for CGA. RESULTS: We reviewed 16 individual CGA baseline documents for analysis in this study. Common assessment areas in all documents included frailty (with the Rockwood Clinical frailty scale used in 94%, n = 15), cognition (4AT-56% of CGAs, MMSE-25%, MOCA-25%, AMTS-19%, AD8-19%, Addenbrookes-13%, 6CIT-13%, mini cog-6%), mobility (100%, n = 16), falls (100%, n = 16), continence (100% n = 16), nutrition (100% n = 16). Mood (94%, n = 15), pain (44%, n = 7), bone health (63%, n = 10), sleep (62%, n = 10) and skin integrity (56%, n = 9). Formal functional assessment was completed in 94% (n = 15) of CGAs with the Barthel index being the tool most used 81% (n = 13). Half of the CGAs included a section describing carer strain (50%, n = 8). The majority of CGAs included a patient centred question which was some variation of 'what matters most to me' (75% n = 11). 87.5% of assessments included a care plan summary (n = 14). CONCLUSIONS: This report highlights that the core tenets of CGA are being assessed across different community based initial CGA screening instruments. There was significant variability in the discussion of challenging topics such as carer strain and social well-being. Our results should prompt a discussion about whether a minimum dataset should be developed for inclusion in nationwide initial baseline CGA document, aiming to improve standardisation of assessments, which will impact areas highlighted for intervention and ultimately guide population health policy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.623
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.070
GPT teacher head0.411
Teacher spread0.342 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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