Effectiveness of interventions designed to reduce the use of imaging for low-back pain: a systematic review
Bibliographic record
Abstract
BACKGROUND: Rates of imaging for low-back pain are high and are associated with increased health care costs and radiation exposure as well as potentially poorer patient outcomes. We conducted a systematic review to investigate the effectiveness of interventions aimed at reducing the use of imaging for low-back pain. METHODS: We searched MEDLINE, Embase, CINAHL and the Cochrane Central Register of Controlled Trials from the earliest records to June 23, 2014. We included randomized controlled trials, controlled clinical trials and interrupted time series studies that assessed interventions designed to reduce the use of imaging in any clinical setting, including primary, emergency and specialist care. Two independent reviewers extracted data and assessed risk of bias. We used raw data on imaging rates to calculate summary statistics. Study heterogeneity prevented meta-analysis. RESULTS: A total of 8500 records were identified through the literature search. Of the 54 potentially eligible studies reviewed in full, 7 were included in our review. Clinical decision support involving a modified referral form in a hospital setting reduced imaging by 36.8% (95% confidence interval [CI] 33.2% to 40.5%). Targeted reminders to primary care physicians of appropriate indications for imaging reduced referrals for imaging by 22.5% (95% CI 8.4% to 36.8%). Interventions that used practitioner audits and feedback, practitioner education or guideline dissemination did not significantly reduce imaging rates. Lack of power within some of the included studies resulted in lack of statistical significance despite potentially clinically important effects. INTERPRETATION: Clinical decision support in a hospital setting and targeted reminders to primary care doctors were effective interventions in reducing the use of imaging for low-back pain. These are potentially low-cost interventions that would substantially decrease medical expenditures associated with the management of low-back pain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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; a candidate call from one teacher head, not a consensus.
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".