MétaCan
Menu
Back to cohort
Record W6992997567

National evaluation of Partnerships for Older People Projects

2009· article· en· W6992997567 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
Fundersnot available
KeywordsOlder peopleGeneral partnershipAccident and emergencyPhoneEmergency departmentQuarter (Canadian coin)Hospital bedVoluntary sectorIndependence (probability theory)
DOInot available

Abstract

fetched live from OpenAlex

Executive SummaryThe Partnership for Older People Projects (POPP) were funded by the Department of Health to develop services for older people, aimed at promoting their health, well-being and independence and preventing or delaying their need for higher intensity or institutional care. The evaluation found that a wide range of projects resulted in improved quality of life for participants and considerable savings, as well as better local working relationships. •Twenty-nine local authorities were involved as pilot sites, working with health and voluntary sector partners to develop services, with funding of £60m•Those projects developed ranged from low level services, such as lunch-clubs, to more formal preventive initiatives, such as hospital discharge and rapid response services•Over a quarter of a million people (264,637) used one or more of these services•The reduction in hospital emergency bed days resulted in considerable savings, to the extent that for every extra £1 spent on the POPP services, there has been approximately a £1.20 additional benefit in savings on emergency bed days. This is the headline estimate drawn from a statistically valid range of £0.80 to £1.60 saving on emergency bed days for every extra £1 spent on the projects.•Overnight hospital stays were seemingly reduced by 47% and use of Accident & Emergency departments by 29%. Reductions were also seen in physiotherapy/occupational therapy and clinic or outpatient appointments with a total cost reduction of £2,166 per person•A practical example of what works is pro-active case coordination services, where visits to A&E departments fell by 60%, hospital overnight stays were reduced by 48%, phone calls to GPs fell by 28%, visits to practice nurses reduced by 25% and GP appointments reduced by 10%•Efficiency gains in health service use appear to have been achieved without any adverse impact on the use of social care resources•The overwhelming majority of the POPP projects have been sustained, with only 3% being closed – either because they did not deliver the intended outcomes or because local strategic priorities had changed•PCTs have contributed to the sustainability of the POPP projects within all 29 pilot sites. Moreover, within almost half of the sites, one or more of the projects are being entirely sustained through PCT funding – a total of 20% of POPP projects. There are a further 14% of projects for which PCTs are providing at least half of the necessary ongoing funding•POPP services appear to have improved users’ quality of life, varying with the nature of individual projects; those providing services to individuals with complex needs were particularly successful, but low-level preventive projects also had an impact•All local projects involved older people in their design and management, although to varying degrees, including as members of steering or programme boards, in staff recruitment panels, as volunteers or in the evaluation•Improved relationships with health agencies and the voluntary sector in the locality were generally reported as a result of partnership working, although there were some difficulties securing the involvement of GPs

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)0.164
metaresearch head score (Gemma)0.151
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.868

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1640.151
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.004
Science and technology studies0.0040.002
Scholarly communication0.0060.005
Open science0.0020.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0180.002

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 head0.537
GPT teacher head0.494
Teacher spread0.043 · 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 designObservational
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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueFigshareSame topicHealthcare innovation and challengesFrench-language works237,207