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Significant knowledge gaps exist in the perioperative pain management of patients with a history of chronic pain, substance use disorder, and/or opioid tolerance as highlighted in the US Health and Human Services Pain Management Best Practices Inter-Agency Task Force 2019 report. The report emphasized the challenges of caring for these populations and the need for multidisciplinary care and a comprehensive approach. Such care requires stakeholder alignment across multiple specialties and care settings. With the intention of codifying this alignment into a reliable and efficient processes, a consortium of 15 professional healthcare societies was convened in a year-long modified Delphi consensus process and summit. This process produced seven guiding principles for the perioperative care of patients with chronic pain, substance use disorder, and/or preoperative opioid tolerance. These principles provide a framework and direction for future improvement in the optimization and care of 'complex' patients as they undergo surgical procedures. [ABSTRACT FROM AUTHOR]

Background: Maternal hemorrhage protocols involve risk screening. These protocols prepare clinicians for potential hemorrhage and transfusion in individual patients. Patient‐specific estimation and stratification of risk may improve maternal outcomes. Study Design and Methods: Prediction models for hemorrhage and transfusion were trained and tested in a data set of 74 variables from 63 973 deliveries (97.6% of the source population of 65 560 deliveries included in a perinatal database from an academic urban delivery center) with sufficient data at pertinent time points: antepartum, peripartum, and postpartum. Hemorrhage and transfusion were present in 6% and 1.6% of deliveries, respectively. Model performance was evaluated with the receiver operating characteristic (ROC), precision‐recall curves, and the Hosmer‐Lemeshow calibration statistic. Results: For hemorrhage risk prediction, logistic regression model discrimination showed ROCs of 0.633, 0.643, and 0.661 for the antepartum, peripartum, and postpartum models, respectively. These improve upon the California Maternal Quality Care Collaborative (CMQCC) accuracy of 0.613 for hemorrhage. Predictions of transfusion resulted in ROCs of 0.806, 0.822, and 0.854 for the antepartum, peripartum, and postpartum models, respectively. Previously described and new risk factors were identified. Models were not well calibrated with Hosmer‐Lemeshow statistic P values between.001 and.6. Conclusions: Our models improve on existing risk assessment; however, further enhancement might require the inclusion of more granular, dynamic data. With the goal of increasing translatability, this work was distilled to an online open‐source repository, including a form allowing risk factor inputs and outputs of CMQCC risk, alongside our numerical risk estimation and stratification of hemorrhage and transfusion. [ABSTRACT FROM AUTHOR]