We previously developed a personalized AI model to predict surgical transfusion risk. Here we simulated using it for preop T&S decisions at 45 US hospitals. Our model (S-PATH) did better than the standard of care approach (MSBOS). We also measured performance using a clinically meaningful benchmark, the number of T&S ordered. S-PATH needed ~ 1/3 fewer while maintaining 96% sensitivity for finding patients who need blood. Importantly, we used S-PATH out of the box. No retraining or fine tuning on individual hospitals. Nonetheless, it still performed well. This kind of robustness is rare among AI models, and suggests S-PATH could be immediately useful for many hospital systems.
Presurgical blood orders are important for patient safety during surgery, but excess orders can be costly to patients and the healthcare system. We assessed clinician perceptions on the presurgical blood ordering process and perceived barriers to reliable decision-making, including lack of information on surgical transfusion risk, lack of experience in ordering clinicians, and poor communication between stakeholders.
Preparation for transfusion is important, but excessive preparation is common, costly, and contributes to blood waste. This tool helps doctors identify patients at risk for transfusion so they can get the care they need. We evaluated the tool's performance at 414 NSQIP-contributing hospitals, and found that it showed promising generalizability and could potentially be used across a diverse range of hospitals to assist with perioperative planning.
We compared EHR-based workload with reimbursement in anesthesiology and found that payments for anesthesia services are likely poorly calibrated with clinical workload, largely by not recognizing the physical and cognitive effort of caring for the sickest patients. This likely penalizes academic and safety net hospitals the most. Our method for measuring clinical workload from EHR audit log data could be used to measure the time and intensity of clinical work more objectively to better inform healthcare policy.
Surgical transfusion has an outsized impact on hospital-based transfusion services, leading to blood product waste and unnecessary costs. In this paper, we describe the design and implementation of a streamlined reliable process for perioperative blood ordering and delivery to reduce red cell waste.
20 million patients have surgery in the US every year, and ~ 1 million of those patients require life-saving blood transfusion. Presurgical preparation for transfusion is important to allow for safe and timely transfusion during surgery, but excessive preparation is unfortunately common, costly, and contributes to blood waste. In this paper, we develop a personalized surgical transfusion risk prediction model using a database of 3 million surgical patients, and show that using such a model to guide presurgical type and screen orders can potentially improve patient safety while reducing the number of unnecessary orders. Reproducible code is provided to make predictions for new patients.
Clinical work environments are filled with competing demands for clinicians' attention, resulting in attention switching between different tasks up to 150 times an hour. The consequences of such fragmented work are not well-understood, partially because measuring attention switching has traditionally been laborious observational work. We developed a novel scalable method of measuring clinician attention switching using passively collected EHR audit log data. As a case study, we applied this method to critical care clinicians. We found that ICU work was highly fragmented, and increased attention switching was associated with decreased clinician efficiency and increased errors.
Double lumen tube (DLT) sizes can vary considerably between manufacturers. This can lead to inadvertent oversizing of DLTs, especially if using conventional height/gender based sizing, which can potentially contribute to tracheal injury. We advocate for CT based sizing of DLTs, especially in high risk patients, and for thermal softening of DLTs as routine practice to help prevent tracheobronchial injury.
The sinuses of Valsalva are outpouchings in the aortic root just distal to the aortic valve that serve several physiologic functions. Aneurysm of this segment of the aorta is quite rare and infrequently encountered in clinical practice. Due to the …