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Record W7027640524

The costs and benefits of active case
\nmanagement and rehabilitation for
\nmusculoskeletal disorders

2006· book· en· W7027640524 on OpenAlexfundno aff

Bibliographic record

VenueUniversity of Huddersfield Repository (University of Huddersfield) · 2006
Typebook
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsnot available
FundersRoyal Australasian College of PhysiciansWashington State Department of Labor and IndustriesWorkers' Compensation Board – AlbertaWorkers Compensation Board of ManitobaHealth and Safety ExecutiveInternational Association for the Study of PainWashington State UniversityUniversity of Washington
KeywordsRehabilitationWork (physics)Quality (philosophy)Health careKey (lock)Scientific evidenceBest practice
DOInot available

Abstract

fetched live from OpenAlex

The burden of musculoskeletal disorders (MSDs) to employers and workplaces is significant; and
\nthe most important cost to employers and society is lost time from work.
\n‘Case management’ is a goal-oriented approach to keeping employees at work and facilitating an
\nearly return to work. There is good scientific evidence that case management methods are costeffective
\nthrough reducing time off work and lost productivity, and reducing healthcare costs.
\nThere is even stronger evidence that best-practice rehabilitation approaches have the very
\nimportant potential to significantly reduce the burden of long-term sickness absence due to
\nMSDs. The combination of case management with suitable rehabilitation principles is currently
\nbeing used effectively in multiple settings throughout the UK, and there is growth within the case
\nmanagement sector. Current providers vary widely in quality and experience. There is limited
\nprofessional regulation, although localised standards of practice have recently become available.
\nMany of the factors influencing the adoption of cost-effective case management and rehabilitation
\napproaches rest with employers, and funders/commissioners of healthcare. It may be easier to
\nintegrate these practices into large and medium-sized workplaces, but there is no reason why the
\nsame principles cannot be applied to small businesses and the self-employed. It appears to be very
\ntimely for the distribution of information to employers and other key players about how effective
\ncase management and suitable rehabilitation approaches can be, and how applicable they are to
\nUK settings. To this end, an integrated model specific to the UK has been developed.
\nAn evidence-based model for managing those with MSDs was developed that is widely
\napplicable to all types of industry and business in the UK. It describes the principles to apply in
\norder to integrate case management and rehabilitation with the workplace. It was derived from
\nhigh quality scientific studies, and research conducted into views on the applicability and
\neffectiveness within the UK.
\nIt is recommended that HSE distribute guidance based on this model.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.155
Teacher spread0.152 · 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 designQualitative
Domainnot available
GenreOther

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
Published2006
Admission routes1
Has abstractyes

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