The Adherence to an Intraoperative Blood Product Transfusion Algorithm Is Associated With Reduced Blood Product Transfusions in Cardiac Surgical Patients Undergoing Coronary Artery Bypass Grafts and Aortic and/or Valve Replacement Surgery: A Single-Center, Observational Study.

OBJECTIVE: To demonstrate the value of a viscoelastic-based intraoperative transfusion algorithm to reduce non-RBC product administration in adult cardiac surgical patients. DESIGN: A prospective observational study. SETTING: At a quaternary academic teaching hospital. PARTICIPANTS: Cardiac surgical patients. INTERVENTIONS: Viscoelastic-based intraoperative transfusion algorithm. MEASUREMENTS AND MAIN RESULTS: The study authors compared intraoperative blood product transfusion rates in 184 cardiac surgical patients to 236 historic controls after implementing a viscoelastic-based algorithm. The authors found a non-significant reduction in transfusion of 23.8% for fresh frozen plasma (FFP) units (0.84 ± 1.4 v 0.64 ± 1.38; p = ns), 33.4% for platelet units (0.90 ± 1.39 v 0.60 ± 131; p = ns), and 15.8% for cryoprecipitate units (0.19 ± 0.54 v 0.16 ± 0.50; p = ns). They found a 43.9% reduction in red blood cell (RBC) units transfused (1.98 ± 2.24 v 0.55 ± 1.36; p = 0.008). There were no statistically significant differences in time to extubation (8.0 hours (4.0-21.0) v 8.0 (4.0-22.3), reoperation for bleeding (15 [12.3%] v 10 [10.6%]), intensive care unit length of stay (ICU LOS) (51.0 hours [28.0-100.5] v 53.5 [33.3-99.0]) or hospital LOS (9.0 days [6.0-15.0] v 10.0 [7.0-17.0]). Deviation from algorithm adherence was 32.7% (48/147). Packed RBC, FFP, platelets, cryoprecipitate, and cell saver were significantly reduced in the Algorithm Compliant Cohort compared with historic controls, whereas times to extubation, ICU LOS, and hospital LOS did not reach significance. CONCLUSIONS: After the implementation of a viscoelastic-based algorithm, patients received fewer packed RBC, FFP, platelets, cryoprecipitate, and cell saver. Algorithm-compliant patients received fewer transfusions; however, reductions in times to extubation, ICU LOS, and hospital LOS were not statistically significant compared with historic controls.

Novel Electronic Health Records-Based Consultation Workflow Improves Time to Operating Room for Vascular Surgery Patients in an Acute Setting.

BACKGROUND: Inefficient clinical workflows can have downstream effects of increased costs, poor resource utilization, and worse patient outcomes. The surgical consultation process can be complex with unclear communication, potentially delaying care for patients requiring time-sensitive intervention in an acute setting. A novel electronic health records (EHR)-based workflow was implemented to improve the consultation process. After implementation, we assessed the impact of this initiative in patients requiring vascular surgery consultation. METHODS: An EHR-driven consultation workflow was implemented at a single institution, standardizing the process across all consulting services. This order-initiated workflow automated notification to clinicians of consult requests, communication of patient data, patient addition to consultants' lists, and tracking consult completion. Preimplementation (1/1/2020-1/31/2022) and postimplementation (2/1/2022-12/4/2022) vascular surgery consultation cohorts were compared to evaluate the impact of this initiative on timeliness of care. RESULTS: There were 554 inpatient vascular surgery consultations (255 preimplementation and 299 postimplementation); 45 and 76 consults required surgery before and after implementation, respectively. The novel workflow resulted in placement of a consult note 32 min faster than preimplementation (preimplementation: 462 min, postimplementation: 430 min, P = 0.001) for all vascular surgery consults. Furthermore, vascular surgery patients with ASA class III or IV status requiring an urgent or emergent operation were transported to the operating room 63.3% faster after implementation of the workflow (preimplementation: 284 min, postimplementation: 180 min, P = 0.02). There were no differences in procedure duration, postoperative disposition, or intraoperative complication rates. CONCLUSIONS: We implemented a novel workflow utilizing the EHR to standardize and automate the consultation process in the acute inpatient setting. This institutional initiative significantly improved timeliness of care for vascular surgery patients, including decreased time to operation. Innovations such as this can be further disseminated across shared EHR platforms across institutions, representing a powerful tool to increase the value of care in vascular surgery and healthcare overall.

A practical guide to adopting Bayesian analyses in clinical research.

Background: Bayesian statistical approaches are extensively used in new statistical methods but have not been adopted at the same rate in clinical and translational (C&T) research. The goal of this paper is to accelerate the transition of new methods into practice by improving the C&T researcher's ability to gain confidence in interpreting and implementing Bayesian analyses. Methods: We developed a Bayesian data analysis plan and implemented that plan for a two-arm clinical trial comparing the effectiveness of a new opioid in reducing time to discharge from the post-operative anesthesia unit and nerve block usage in surgery. Through this application, we offer a brief tutorial on Bayesian methods and exhibit how to apply four Bayesian statistical packages from STATA, SAS, and RStan to conduct linear and logistic regression analyses in clinical research. Results: The analysis results in our application were robust to statistical package and consistent across a wide range of prior distributions. STATA was the most approachable package for linear regression but was more limited in the models that could be fitted and easily summarized. SAS and R offered more straightforward documentation and data management for the posteriors. They also offered direct programming of the likelihood making them more easily extendable to complex problems. Conclusion: Bayesian analysis is now accessible to a broad range of data analysts and should be considered in more C&T research analyses. This will allow C&T research teams the ability to adopt and interpret Bayesian methodology in more complex problems where Bayesian approaches are often needed.