Background The Hospital Frailty Risk Score (HFRS) has made it possible internationally to identify subgroups of patients with characteristics of frailty from routinely collected hospital data. Objective To externally validate the HFRS in France. Design A retrospective analysis of the French medical information database. Setting 743 hospitals in Metropolitan France. Subjects All patients aged 75 years or older hospitalised as an emergency in 2017 (n = 1,042,234). Methods The HFRS was calculated for each patient based on the index stay and hospitalisations over the preceding 2 years. Main outcome measures were 30-day in-patient mortality, length of stay (LOS) >10 days and 30-day readmissions. Mixed logistic regression models were used to investigate the association between outcomes and HFRS score. Results Patients with high HFRS risk were associated with increased risk of mortality and prolonged LOS (adjusted odds ratio [aOR] = 1.38 [1.35–1.42] and 3.27 [3.22–3.32], c-statistics = 0.676 and 0.684, respectively), while it appeared less predictive of readmissions (aOR = 1.00 [0.98–1.02], c-statistic = 0.600). Model calibration was excellent. Restricting the score to data prior to index admission reduced discrimination of HFRS substantially. Conclusions HFRS can be used in France to determine risks of 30-day in-patient mortality and prolonged LOS, but not 30-day readmissions. Trial registration: Reference ID on clinicaltrials.gov: ID: NCT03905629.

Objectives:The control chart is a graphical tool for data interpretation that detects aberrant variations in specific metrics, ideally leading to the identification of special causes that can be resolved. A clear assessment of control chart utilization and its potential impact in surgery is required to justify recommendations for its dissemination. This review aims to describe how performance monitoring using control charts was used over time in surgery.Methods: A systematic search of PubMed regarding statistical process control in surgery from its inception until December 2019 was performed using Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Information extracted from selected publications included study aim and population setting, monitored indicators, control charts methodological parameters, and implementation strategy. Results:One hundred thirteen studies met the selection criteria with a median of 1916 monitored patients. Overall, 57.5% of studies focused on control chart methodology, 24.8% aimed at evaluating performance changes using control charts retrospectively, and 17.7% implemented control charts for continuous quality improvement prospectively. Although there was a great diversity of used indicators and charting tools, the evaluation of patient safety (72.6%) or efficiency (15.9%) metrics based on Shewhart control chart (33.6%) or cumulative sum chart (54.9%) were common. To foster control charts implementation, 14 studies promoted their periodic review, but only three assessed their impact on patient outcomes. Conclusions:The scientific literature supports the feasibility and utility of control chart to improve patient safety in multiple surgical settings. Additional studies are necessary to reveal the optimal manner in which to implement this affordable tool in surgical practice.

Purpose The mobilization of most available hospital resources to manage coronavirus disease 2019 (COVID-19) may have affected the safety of care for non-COVID-19 surgical patients due to restricted access to intensive or intermediate care units (ICU/IMCUs). We estimated excess surgical mortality potentially attributable to ICU/IMCUs overwhelmed by COVID-19, and any hospital learning effects between two successive pandemic waves. Methods This nationwide observational study included all patients without COVID-19 who underwent surgery in France from 01/01/2019 to 31/12/2020. We determined pandemic exposure of each operated patient based on the daily proportion of COVID-19 patients among all patients treated within the ICU/IMCU beds of the same hospital during his/her stay. Multilevel models, with an embedded triple-difference analysis, estimated standardized in-hospital mortality and compared mortality between years, pandemic exposure groups, and semesters, distinguishing deaths inside or outside the ICU/IMCUs. Results Of 1,870,515 non-COVID-19 patients admitted for surgery in 655 hospitals, 2% died. Compared to 2019, standardized mortality increased by 1% (95% CI 0.6–1.4%) and 0.4% (0–1%) during the first and second semesters of 2020, among patients operated in hospitals highly exposed to pandemic. Compared to the low-or-no exposure group, this corresponded to a higher risk of death during the first semester (adjusted ratio of odds-ratios 1.56, 95% CI 1.34–1.81) both inside (1.27, 1.02–1.58) and outside the ICU/IMCU (1.98, 1.57–2.5), with a significant learning effect during the second semester compared to the first (0.76, 0.58–0.99). Conclusion Significant excess mortality essentially occurred outside of the ICU/IMCU, suggesting that access of surgical patients to critical care was limited. Supplementary Information The online version contains supplementary material available at 10.1007/s00134-023-07000-3.