Evaluative reports on medical malpractice policies in obstetrics: a rapid scoping review
Bibliographic record
Abstract
BACKGROUND: The clinical specialty of obstetrics is under particular scrutiny with increasing litigation costs and unnecessary tests and procedures done in attempts to prevent litigation. We aimed to identify reports evaluating or comparing the effectiveness of medical liability reforms and quality improvement strategies in improving litigation-related outcomes in obstetrics. METHODS: We conducted a rapid scoping review with a 6-week timeline. MEDLINE, EMBASE, LexisNexis Academic, the Legal Scholarship Network, Justis, LegalTrac, QuickLaw, and HeinOnline were searched for publications in English from 2004 until June 2015. The selection criteria for screening were established a priori and pilot-tested. We included reports comparing or evaluating the impact of obstetrics-related medical liability reforms and quality improvement strategies on cost containment and litigation settlement across all countries. All levels of screening were done by two reviewers independently, and discrepancies were resolved by a third reviewer. In addition, two reviewers independently extracted relevant data using a pre-tested form, and discrepancies were resolved by a third reviewer. The results were summarized descriptively. RESULTS: The search resulted in 2729 citations, of which 14 reports met our eligibility criteria. Several initiatives for improving the medical malpractice litigation system were found, including no-fault approaches, patient safety policy initiatives, communication and resolution, caps on compensation and attorney fees, alternative payment system and liabilities, and limitations on litigation. CONCLUSIONS: Only a few litigation policies in obstetrics were evaluated or compared. Included documents showed that initiatives to reduce medical malpractice litigation could be associated with a decrease in adverse and malpractice events. However, due to heterogeneous settings (e.g., economic structure, healthcare system) and variation in the outcomes reported, the advantages and disadvantages of initiatives may vary.
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 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 | 0.082 | 0.305 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.071 | 0.053 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".