Trial reportBMJ (Clinical research ed.)2020
Effect of monitoring surgical outcomes using control charts to reduce major adverse events in patients: cluster randomised trial.
Trial report in BMJ (Clinical research ed.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02569450 (The Impact of Surgical Outcomes Monitoring Using Control Chart on Surgical Performance), which is not on this map. Cited by 26 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
The Impact of Surgical Outcomes Monitoring Using Control Chart on Surgical Performance: A Cluster Randomized Trial
Who cites it
26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 47 citations in OpenAlex.
- Training and education provided to local change champions within implementation trials: a rapid systematic review.Implementation science : IS · 2025Pooled it
- Incidence and predictors of postoperative complications in Sub-Saharan Africa: a systematic review and meta-analysis.Frontiers in health services · 2024Pooled it
- Cluster randomised evaluation of a training intervention to increase the use of statistical process control charts for hospitals in England: making data count.BMJ quality & safety · 2025Trial
- Economic analysis of surgical outcome monitoring using control charts: the SHEWHART cluster randomised trial.BMJ quality & safety · 2024Trial
- Who Needs Most? Multicenter Subanalysis of Blood Transfusion Profiles in the German Patient Blood Management Network Registry.Journal of clinical medicine · 2026Article
- Risk-adjusted observed minus expected cumulative sum (RA O-E CUSUM) chart for visualisation and monitoring of surgical outcomes.BMJ quality & safety · 2025Article
- Measuring variations in healthcare data using run charts and statistical process control charts: a survey of general physicians attending the quality improvement workshop.Internal medicine journal · 2025Article
- Hidden costs of surgical complications: a retrospective cohort study.BMJ surgery, interventions, & health technologies · 2025Article
- Safety of inpatient care in surgical settings: cohort study.BMJ (Clinical research ed.) · 2024Article
- Comment on A Method for Continuous Surgeon Improvement in Rectal Cancer: Observed Minus Expected (O-E) Chart Versus CUSUM Chart.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2024Article
- An interview study about how nurses and physicians talk about the same concepts differently.BMC medical education · 2024Article
- Optimizing patient outcome in intracranial tumor surgery: a detailed prospective study of adverse events and mortality reduction strategies in neurosurgery.Acta neurochirurgica · 2024Article
- Article
- National and regional trends in the prevalence of type 2 diabetes and associated risk factors among Korean adults, 2009-2021.Scientific reports · 2023Article
- Use of Statistical Process Control Methods for Early Detection of Healthcare Facility-Associated Nontuberculous Mycobacteria Outbreaks: A Single-Center Pilot Study.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Adverse events in neurosurgery: a comprehensive single-center analysis of a prospectively compiled database.Acta neurochirurgica · 2023Article
- Retrospective evaluation of an intervention based on training sessions to increase the use of control charts in hospitals.BMJ quality & safety · 2023Article
- Safe implementation of surgical innovation: a prospective registry of the Versius Robotic Surgical System.BMJ surgery, interventions, & health technologies · 2023Article
- Failure in Medical Practice: Human Error, System Failure, or Case Severity?Healthcare (Basel, Switzerland) · 2022Article
- Early recognition and response to increases in surgical site infections using optimised statistical process control charts-The early 2RIS trial: A multicentre stepped wedge cluster randomised controlled trial.EClinicalMedicine · 2022Article
Corrections and comments
- Commented on by
Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo determine the effect of introducing prospective monitoring of outcomes using control charts and regular feedback on indicators to surgical teams on major adverse events in patients.
designNational, parallel, cluster randomised trial embedding a difference-in-differences analysis.
setting40 surgical departments of hospitals across France.
participants155 362 adults who underwent digestive tract surgery. 20 of the surgical departments were randomised to prospective monitoring of outcomes using control charts with regular feedback on indicators (intervention group) and 20 to usual care only (control group).
interventionsProspective monitoring of outcomes using control charts, provided in sets quarterly, with regular feedback on indicators (intervention hospitals). To facilitate implementation of the programme, study champion partnerships were established at each site, comprising a surgeon and another member of the surgical team (surgeon, anaesthetist, or nurse), and were trained to conduct team meetings, display posters in operating rooms, maintain a logbook, and devise an improvement plan.
main outcome measuresThe primary outcome was a composite of major adverse events (inpatient death, intensive care stay, reoperation, and severe complications) within 30 days after surgery. Changes in surgical outcomes were compared before and after implementation of the programme between intervention and control hospitals, with adjustment for patient mix and clustering.
results75 047 patients were analysed in the intervention hospitals (37 579 before and 37 468 after programme implementation) versus 80 315 in the control hospitals (41 548 and 38 767). After introduction of the control chart, the absolute risk of a major adverse event was reduced by 0.9% (95% confidence interval 0.4% to 1.4%) in intervention compared with control hospitals, corresponding to 114 patients (70 to 280) who needed to receive the intervention to prevent one major adverse event. A significant decrease in major adverse events (adjusted ratio of odds ratios 0.89, 95% confidence interval 0.83 to 0.96), patient death (0.84, 0.71 to 0.99), and intensive care stay (0.85, 0.76 to 0.94) was found in intervention compared with control hospitals. The same trend was observed for reoperation (0.91, 0.82 to 1.00), whereas severe complications remained unchanged (0.96, 0.87 to 1.07). Among the intervention hospitals, the effect size was proportional to the degree of control chart implementation witnessed. Highly compliant hospitals experienced a more important reduction in major adverse events (0.84, 0.77 to 0.92), patient death (0.78, 0.63 to 0.97), intensive care stay (0.76, 0.67 to 0.87), and reoperation (0.84, 0.74 to 0.96).
conclusionsThe implementation of control charts with feedback on indicators to surgical teams was associated with concomitant reductions in major adverse events in patients. Understanding variations in surgical outcomes and how to provide safe surgery is imperative for improvements.
trial registrationClinicalTrials.gov NCT02569450.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.