Attitudes and Opinions of Doctors of Chiropractic Specializing in Pediatric Care Toward Patient Safety: A Cross-sectional Survey
Bibliographic record
Abstract
OBJECTIVE: The purpose of this cross-sectional survey was to evaluate attitudes and opinions of doctors of chiropractic (DCs) specializing in pediatric care toward patient safety. METHODS: The Medical Office Survey on Patient Safety Culture of the Agency for Healthcare Research and Quality was adapted for providers who use spinal manipulation therapy and sent out to 2 US chiropractic organizations' pediatric council members (n = 400) between February and April 2014. The survey measured 12 patient safety dimensions and included questions on patient safety items and quality issues, information exchange, and overall clinic ratings. Data analyses included a percent composite average and a nonrespondent analysis. RESULTS: The response rate was 29.5% (n = 118). Almost one- third of respondents' patients were pediatric (≤17 years of age). DCs with a pediatric certification were 3 times more likely to respond (P < .001), but little qualitative differences were found in responses. The patient safety dimensions with the highest positive composite percentages were Organizational Learning (both administration and clinical) and Teamwork (>90%). Patient Care Tracking/Follow-up and Work Pressure and Pace were patient safety dimensions that had the lowest positive composite scores (<85%). The responses also indicated that there was concern regarding information exchange with insurance/third-party payors. Two quality issues identified for improvement were (1) updating a patient's medication list and (2) following up on critically abnormal results from a laboratory or imaging test within 1 day. The average overall patient safety rating score indicated that 83% of respondents rated themselves as "very good" or "excellent." CONCLUSIONS: Compared with 2014 Agency for Healthcare Research and Quality physician referent data from medical offices, pediatric DCs appear to have more positive patient safety attitudes and opinions. Future patient safety studies need to prospectively evaluate safety performance with direct feedback from patients and compare results with these self-assessed safety attitudes, as well as make further use of this survey to develop a comparable database for spinal manipulation providers.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; a candidate call from one source (direct Gemma or distilled Codex), 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".