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Record W2896466859 · doi:10.7939/r3mw28p2d

Evaluation of A Clinical Decision Support Tool for Selecting Optimal Rehabilitation Intervention for Injured Workers

2014· article· en· W2896466859 on OpenAlexaboutno aff
Ziling Qin

Bibliographic record

VenueUniversity of Alberta Library · 2014
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationIntervention (counseling)Decision support systemMedicinePhysical medicine and rehabilitationPhysical therapyComputer scienceRisk analysis (engineering)NursingArtificial intelligence

Abstract

fetched live from OpenAlex

Objective: To evaluate the concurrent validity of a newly developed clinical decision support tool (Work Assessment Triage Tool, WATT) by comparing the rehabilitation interventions determined using the WATT with the current gold standard–clinician recommendations. Methods: This is a secondary data analysis study. Data were collected in a clinical trial conducted previously at the Workers’ Compensation Board of Alberta rehabilitation facility. A variety of statistical methods were used to compare recommendations for rehabilitation strategies determined using the WATT, clinician recommendations, actual programs claimants undertook and return-to-work outcomes. Analyses included percent agreement, crosstabs, and likelihood ratios. Results: Percent agreement between clinician recommendations and WATT recommendations were low (r = 0.19) to moderate (r = 0.46). The WATT does not appear to improve upon clinician recommendations as only half of the RTW claimants whose actual rehabilitation programs did not match those of the clinician recommendations, matched recommendations identified using WATT. Discussions: Contrary to internal validation demonstrating that the WATT outperformed clinician recommendations; results of the external validation of the WATT were not as promising. Findings do not provide evidence of concurrent validity of the WATT against the current gold standard. Four possible reasons could explain the results: (1) important differences were observed in claimant characteristics between the original WATT development data and our validation dataset; (2) insufficient data for claimants who failed RTW and those with successful RTW whose actual rehabilitation program did not match with the clinician recommendations; (3) data processing techniques that were used to overcome rehabilitation class imbalance when building the WATT, which may contribute to errors in the WATT recommendations; (4) clinician recommendations conflicted somewhat with existing evidence as some rehabilitation programs that were highly supported by research evidence (i.e. workplace interventions) were rarely recommended by clinicians in our validation dataset. Conclusion: WATT recommendations do not concur with clinician recommendations. With respect to concurrent validity, no conclusion can be drawn as to which method, WATT or clinician judgment, provides better recommendations for return-to-work in actual practice. Further research is needed to resolve this uncertainty.

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)0.062
metaresearch head score (Gemma)0.238
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 score0.062
Threshold uncertainty score0.330

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0620.238
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.089
GPT teacher head0.473
Teacher spread0.384 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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