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Record W2057049441 · doi:10.1093/ageing/afs080

Quality of care and the quality of life in care homes

2012· letter· en· W2057049441 on OpenAlexaff
John Gladman, Clive Bowman

Bibliographic record

VenueAge and Ageing · 2012
Typeletter
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineQuality (philosophy)NursingNursing homesQuality managementGerontologyQuality of life (healthcare)Operations management

Abstract

fetched live from OpenAlex

Netten et al. asked whether, in England, a relationship existed between quality of life in care homes and a now-discarded ‘star’ rating used by the regulator [1]. They found both ‘yes’ and ‘no’ answers, the ‘yes’ relating to residential care and the ‘no’ to nursing. The regulator for England, then the Commission for Social Care Inspection (CSCI), introduced Quality Ratings in 2008. Regulation of care homes now considers 28 domains, of which 16 are deemed core standards [2]. They are grouped in six areas: involvement and information; personalised care, treatment and support; safeguarding and safety; staffing; quality and management and suitability of management. All are, essentially, measures of processes, although they are described as ‘outcomes’. For example, the standards require that homes provide a choice of suitable and nutritious food and support to enable eating and drinking (‘outcome’ 5), rather than a resident-based experience. As a result, it is possible that although a regulator's report could comment favourably on the engagement of staff and general happiness of the residents, the home could be rated poorly because of deficits in process such as the recording of administration of medicines. It is easy to see how such regulation could potentially focus on compliance with processes rather than on resident contentment. Initially, the Quality Ratings were: no stars (poor), one star (adequate), two stars (good) and three stars (excellent). After a year's experience, the regulator concluded that the Quality Ratings had a strong impact on the commissioning of care services for people in their community and that they were an effective lever for improving both the quality of services and the outcomes for people who use them [3]. Within 2 years, with a change to the regulatory framework, under the Care Quality Commission, a dramatic improvement occurred and over 80% of homes were reported good or excellent (unpublished analysis by Bupa). It is likely that the dramatic improvement in star ratings was that providers had understood how to satisfy the measurement metrics. It is not so clear whether the changes represented substantial progress in the quality of care as experienced by individuals. This explains why the question posed by Netten et al. is important: the Quality Ratings were about the process of care, but did they reflect the outcome of care? Despite these concerns, the paper by Netten et al. suggests that measures of care process such as star ratings can act as crude proxies for care outcomes for the residents of residential homes, but not for nursing homes. For nursing homes, it could be that the measures of process were too ‘social’ for people whose needs are driven by disease, disability and frailty: it is increasingly clear that the residents of care homes, particularly nursing homes, are increasingly in these categories [4]. Clinical markers for good care used in hospital care by the Department of Health, the ‘Essence of Care’ benchmarks [5], specifically include continence, pain, skin care and communication, which do not specifically feature in the regulator's standards. The same argument may be true for assessments of quality of life: social-care-based assessments may be insensitive to the effects of health conditions. Given the similarity between nursing home populations and hospitals, a less social model of regulation and expectation should be considered with a greater focus on outcomes. Possible ways forward for quality assurance away from process might include the development of a range of patient-reported outcome measures (PROM) or other direct measures of satisfaction. Another way forward is benchmarked care between institutions [6], which would be all the more valuable if adjusted for case mix. The presumption of a social model for care homes may also explain the inconsistency of health care provision, as highlighted in the British Geriatrics Society's ‘Quest for Quality’ [7] and Failing the Frail: A Chaotic Approach to Commissioning Healthcare Services for Care Homes [8]. If care homes are assumed to be social institutions, it is easy to assume that their health care needs are more similar to those of a hotel than those of a hospital. It is surely necessary to regulate the adequacy of health care provision to care homes, especially nursing homes. Therefore, we could see the routine application of health care delivering comprehensive geriatric assessment to nursing home residents and, given the size of the sector, the emergence of a new discipline of nursing home medicine in the UK!

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.033
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0040.004
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0330.023
Insufficient payload (model declined to judge)0.0050.001

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 head0.069
GPT teacher head0.408
Teacher spread0.338 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations5
Published2012
Admission routes1
Has abstractno

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