Effect of institutional case volume on mid-term mortality after coronary artery bypass grafting surgery

Factors affecting the length of hospital stay for total knee arthroplasty in Japan: a retrospective study using the diagnosis procedure combination database

BACKGROUND

We aimed to evaluate the length of hospital stay following total knee arthroplasty to determine the impact of relevant factors using data from the Diagnosis Procedure Combination database.

METHODS

This was a retrospective observational study. The study cohort included 5,831 patients who had osteoarthritis of the knee and had undergone total knee replacement between February 2018 and October 2022 at 38 hospitals.

RESULTS

Multivariate analysis showed that the factors influencing the length of stay included: age (p < 0.001), height (p < 0.001), weight (p = 0.049), body mass index (p = 0.008), Barthel index (p < 0.001), method of anesthesia (p < 0.001), bone transplant (p = 0.010), timing of postoperative rehabilitation (p < 0.001), atrial fibrillation (p < 0.001), chronic pain (p < 0.001), and number of institutionally treated cases (p < 0.001) (r = 0.451, p < 0.001).

CONCLUSIONS

Shorter or longer hospital stays were found to be associated with the patients' background characteristics and facility-specific factors; these can lead to more accurate estimates of the length of hospital stay and appropriate allocation of resources.

Institutional case volume and mortality after aortic and mitral valve replacement: a nationwide study in two Korean cohorts

Background

There are only a handful of published studies regarding the volume-outcome relationship in heart valve surgery. We evaluated the association between institutional case volume and mortality after aortic valve replacement (AVR) and mitral valve replacement (MVR).

Methods

Two separate cohorts of all adults who underwent AVR or MVR, respectively, between 2009 and 2016 were analyzed using a Korean healthcare insurance database. Hospitals performing AVRs were divided into three groups according to the average annual case volume: the low- (< 20 cases/year), medium- (20–70 cases/year), and high-volume centers (> 70 cases/year). Hospitals performing MVRs were also grouped as the low- (< 15 cases/year), medium- (15–40 cases/year), or high-volume centers (> 40 cases/year). In-hospital mortality after AVR or MVR were compared among the groups.

Results

In total, 7875 AVR and 5084 MVR cases were analyzed. In-hospital mortality after AVR was 8.3% (192/2318), 4.0% (84/2102), and 2.6% (90/3455) in the low-, medium-, and high-volume centers, respectively. The adjusted risk was higher in the low- (OR 2.31, 95% CI 1.73–3.09) and medium-volume centers (OR 1.53, 95% CI 1.09–2.15) compared to the high-volume centers. In-hospital mortality after MVR was 9.3% (155/1663), 6.3% (94/1501), and 2.9% (56/1920) in the low-, medium-, and high-volume centers, respectively. Compared to the high-volume centers, the medium- (OR 1.97, 95% CI 1.35–2.88) and low-volume centers (OR 2.29, 95% CI 1.60–3.27) showed higher adjusted risk of in-hospital mortality.

Conclusions

Lower case volume is associated with increased in-hospital mortality after AVR and MVR. The results warrant a comprehensive discussion regarding regionalization/centralization of cardiac valve replacements to optimize patient outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13019-022-01945-0.

Risk prediction models incorporating institutional case volume for mortality after hip fracture surgery in the elderly

INTRODUCTION

While higher institutional case volume is associated with better postoperative outcomes in various types of surgery, institutional case volume has been rarely included in risk prediction models for surgical patients. This study aimed to develop and validate the predictive models incorporating institutional case volume for predicting in-hospital mortality and 1-year mortality after hip fracture surgery in the elderly.

MATERIALS AND METHODS

Data for all patients (≥ 60 years) who underwent surgery for femur neck fracture, pertrochanteric fracture, or subtrochanteric fracture between January 2008 and December 2016 were extracted from the Korean National Health Insurance Service database. Patients were randomly assigned into the derivation cohort or the validation cohort in a 1:1 ratio. Risk prediction models for in-hospital mortality and 1-year mortality were developed in the derivation cohort using the logistic regression model. Covariates included age, sex, type of fracture, type of anaesthesia, transfusion, and comorbidities such as hypertension, diabetes, coronary artery disease, chronic kidney disease, cerebrovascular disease, and dementia. Two separate models, one with and the other without institutional case volume as a covariate, were constructed, evaluated, and compared using the likelihood ratio test. Based on the models, scoring systems for predicting in-hospital mortality and 1-year mortality were developed.

RESULTS

Analysis of 196,842 patients showed 3.6% in-hospital mortality (7084/196,842) and 15.42% 1-year mortality (30,345/196,842). The model for predicting in-hospital mortality incorporating the institutional case volume demonstrated better discrimination (c-statistics 0.692) compared to the model without the institutional case volume (c-statistics 0.688; likelihood ratio test p value < 0.001). The performance of the model for predicting 1-year mortality was also better when incorporating institutional case volume (c-statistics 0.675 vs. 0.674; likelihood ratio test p value < 0.001).

CONCLUSIONS

The new institutional case volume incorporated scoring system may help to predict in-hospital mortality and 1-year mortality after hip fracture surgery in the elderly population.