Risk Adjustment Measures and Outcome Measures for Prehospital Trauma Research: Recommendations from the Emergency Medical Services Outcomes Project (EMSOP)
Bibliographic record
Abstract
OBJECTIVES: The objectives were to conduct a comprehensive, systematic review of the literature for risk adjustment measures (RAMs) and outcome measures (OMs) for prehospital trauma research and to use a structured expert panel process to recommend measures for use in future emergency medical services (EMS) trauma outcomes research. METHODS: A systematic literature search and review was performed identifying the published studies evaluating RAMs and OMs for prehospital injury research. An explicit structured review of all articles pertaining to each measure was conducted using the previously established methodology developed by the Canadian Physiotherapy Association ("Physical Rehabilitation Outcome Measures"). RESULTS: Among the 4,885 articles reviewed, 96 RAMs and/or OMs were identified from the existing literature (January 1958 to February 2010). Only one measure, the Glasgow Coma Scale (GCS), currently meets Level 1 quality of evidence status and a Category 1 (strong) recommendation for use in EMS trauma research. Twelve RAMs or OMs received Category 2 status (promising, but not sufficient current evidence to strongly recommend), including the motor component of GCS, simplified motor score (SMS), the simplified verbal score (SVS), the revised trauma score (RTS), the prehospital index (PHI), EMS provider judgment, the revised trauma index (RTI), the rapid acute physiology score (RAPS), the rapid emergency medicine score (REMS), the field trauma triage (FTT), the pediatric triage rule, and the out-of-hospital decision rule for pediatrics. CONCLUSIONS: Using a previously published process, a structured literature review, and consensus expert panel opinion, only the GCS can currently be firmly recommended as a specific RAM or OM for prehospital trauma research (along with core measures that have already been established and published). This effort highlights the paucity of reliable, validated RAMs and OMs currently available for outcomes research in the prehospital setting and hopefully will encourage additional, methodologically sound evaluations of the promising, Category 2 RAMs and OMs, as well as the development of new measures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.247 | 0.374 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.013 |
| Bibliometrics | 0.019 | 0.013 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".