Is there variation between hospitals within each region in postoperative mortality for lung cancer surgery in France? A nationwide study from 2013 to 2020

Quality indicators in surgical oncology: systematic review of measures used to compare quality across hospitals

BACKGROUND

Measurement and reporting of quality indicators at the hospital level has been shown to improve outcomes and support patient choice. Although there are many studies validating individual quality indicators, there has been no systematic approach to understanding what quality indicators exist for surgical oncology and no standardization for their use. The aim of this study was to review quality indicators used to assess variation in quality in surgical oncology care across hospitals or regions. It also sought to describe the aims of these studies and what, if any, feedback was offered to the analysed groups.

METHODS

A literature search was performed to identify studies published between 1 January 2000 and 23 October 2023 that applied surgical quality indicators to detect variation in cancer care at the hospital or regional level.

RESULTS

A total of 89 studies assessed 91 unique quality indicators that fell into the following Donabedian domains: process indicators (58; 64%); outcome indicators (26; 29%); structure indicators (6; 7%); and structure and outcome indicators (1; 1%). Purposes of evaluating variation included: identifying outliers (43; 48%); comparing centres with a benchmark (14; 16%); and supplying evidence of practice variation (29; 33%). Only 23 studies (26%) reported providing the results of their analyses back to those supplying data.

CONCLUSION

Comparisons of quality in surgical oncology within and among hospitals and regions have been undertaken in high-income countries. Quality indicators tended to be process measures and reporting focused on identifying outlying hospitals. Few studies offered feedback to data suppliers.

Is the Validity of Logistic Regression Models Developed with a National Hospital Database Inferior to Models Developed from Clinical Databases to Analyze Surgical Lung Cancers?

In national hospital databases, certain prognostic factors cannot be taken into account. The main objective was to estimate the performance of two models based on two databases: the Epithor clinical database and the French hospital database. For each of the two databases, we randomly sampled a training dataset with 70% of the data and a validation dataset with 30%. The performance of the models was assessed with the Brier score, the area under the receiver operating characteristic (AUC ROC) curve and the calibration of the model. For Epithor and the hospital database, the training dataset included 10,516 patients (with resp. 227 (2.16%) and 283 (2.7%) deaths) and the validation dataset included 4507 patients (with resp. 93 (2%) and 119 (2.64%) deaths). A total of 15 predictors were selected in the models (including FEV1, body mass index, ASA score and TNM stage for Epithor). The Brier score values were similar in the models of the two databases. For validation data, the AUC ROC curve was 0.73 [0.68-0.78] for Epithor and 0.8 [0.76-0.84] for the hospital database. The slope of the calibration plot was less than 1 for the two databases. This work showed that the performance of a model developed from a national hospital database is nearly as good as a performance obtained with Epithor, but it lacks crucial clinical variables such as FEV1, ASA score, or TNM stage.

Diffusion of Minimally Invasive Approach for Lung Cancer Surgery in France: A Nationwide, Population-Based Retrospective Cohort Study

BACKGROUND

The minimally invasive approach (MIA) has gained popularity thanks to its efficacy and safety. Our work consisted of evaluating the diffusion of the MIA in hospitals and the variability of this approach (within and between regions).

METHODS

All patients who underwent limited resection or lobectomy for lung cancer in France were included from the national hospital administrative database (2013-2020). We described between-hospital differences in the MIA rate over four periods (2013-2014, 2015-2016, 2017-2018, and 2019-2020). The potential influence of the hospital volume, hospital type, and period on the adjusted MIA rate was estimated by a multilevel linear regression.

RESULTS

From 2013 to 2020, 77,965 patients underwent a lobectomy or limited resection for lung cancer. The rate of the MIA increased significantly over the four periods (50% in 2019-2020). Variability decreased over time in 7/12 regions. The variables included in the multilevel model were significantly related to the adjusted rate of the MIA. Variability between regions was considerable since 18% of the variance was due to systematic differences between regions.

CONCLUSIONS

We confirm that the MIA is part of the surgical techniques used on a daily basis for the treatment of lung cancer. However, this technology is mostly used by surgeons in high volume institutions.