The quality of data in electronic healthcare databases is a critical component when used for research and health practice. The aim of the present study was to assess the data quality in the Paulista Cardiovascular Surgery Registry II (REPLICCAR II) using two different audit methods, direct and indirect. The REPLICCAR II database contains data from 9 hospitals in São Paulo State with over 700 variables for 2229 surgical patients. The data collection was performed in REDCap platform using trained data managers to abstract information. We directly audited a random sample (n = 107) of the data collected after 6 months and indirectly audited the entire sample after 1 year of data collection. The indirect audit was performed using the data management tools in REDCap platform. We computed a modified Aggregate Data Quality Score (ADQ) previously reported by Salati et al. (2015). The agreement between data elements was good for categorical data (Cohen κ = 0.7, 95%CI = 0.59-0.83). For continuous data, the intraclass coefficient (ICC) for only 2 out of 15 continuous variables had an ICC < 0.9. In the indirect audit, 77% of the selected variables (n = 23) had a good ADQ score for completeness and accuracy. Data entry in the REPLICCAR II database proved to be satisfactory and showed competence and reliable data for research in cardiovascular surgery in Brazil.

The Enhanced Recovery After Surgery (ERAS) protocol affected traditional cardiac surgery processes and COVID-19 is expected to accelerate its scalability. The aim of this study was to assess the impact of an ERAS-based protocol on the length of hospital stay after cardiac surgery. From January 2019 to June 2020, 664 patients underwent consecutive cardiac surgery at a Latin American center. Here, 46 patients were prepared for a rapid recovery through a multidisciplinary institutional protocol based on the ERAS concept, the “TotalCor protocol”. After the propensity score matching, 46 patients from the entire population were adjusted for 12 variables. Patients operated on the TotalCor protocol had reduced intensive care unit time (P < 0.025), postoperative stay (P ≤ 0.001) and length of hospital stay (P ≤ 0.001). In addition, there were no significant differences in the occurrence of complications and death between the two groups. Of the 10-central metrics of TotalCor protocol, 6 had > 70% adherences. In conclusion, the TotalCor protocol was safe and effective for a 3-day discharge after cardiac surgery. Postoperative atrial fibrillation and renal failure were predictors of postoperative stay > 5 days.

The objectives of this study were to describe a novel statewide registry for cardiac surgery in Brazil (REPLICCAR), to compare a regional risk model (SPScore) with EuroSCORE II and STS, and to understand where quality improvement and safety initiatives can be implemented. Methods A total of 11 sites in the state of São Paulo, Brazil, formed an online registry platform to capture information on risk factors and outcomes after cardiac surgery procedures for all consecutive patients. EuroSCORE II and STS values were calculated for each patient. An SPScore model was designed and compared with EuroSCORE II and STS to predict 30day outcomes: death, reoperation, readmission, and any morbidity.

It is observed that death rates in cardiac surgery has decreased, however, root causes that behave like triggers of potentially avoidable deaths (AD), especially in low-risk patients (less bias) are often unknown and underexplored, Phase of Care Mortality Analysis (POCMA) can be a valuable tool to identify seminal events (SE), providing valuable information where it is possible to make improvements in the quality and safety of future procedures. Our results show that in São Paul State, only one third of AD in low-risk cardiac surgery was related to specific surgical problems. After a revisited analysis, 75% of deaths could have been avoided, which in the pre-operative phase, the SE was related judgment, patient evaluation and preparation. In the intra-operative phase, most occurrences could have been avoided if other surgical technique had been used. Sepsis was responsible for 75% of AD in the intensive care unit. In the ward phase, the recognition/management of clinical decompensations and sepsis were the contributing factors. Logistic regression model identified age, previous coronary stent implantation, coronary artery bypass grafting + heart valve surgery, ≥ 2 combined heart valve surgery and hospital-acquired infection as independent predictors of AD.