Learning and Collaboration during Crisis: A Novel University-Community Partnership to Manufacture Medical Personal Protective Equipment.

Research on crisis management focuses on pre-planning for disasters in order to understand potential barriers. However, one significant barrier to crisis response is that organizations may come together in unplanned configurations during crisis response. This means that significant opportunities exist for understanding the process by which individuals learn, collaborate, and create new systems during crises. In this case report, we present the case of face shield production by a university, academic medical center, and community partners during the supply chain collapse of the early COVID-19 pandemic with the aim of identifying the relationships that formed during the COVID-19 response, so that this case of relationship formation and participant experiences might inform similar disaster response challenges in the future. Thirteen participants responded to an in-depth questionnaire designed to simulate an asynchronous in-depth interview. Respondents reported on the activities of 80 individuals from 38 units/organizations, providing insight into communication challenges and resolutions. Responses were analyzed using thematic analysis, highlighting roles and relationships among participants. The findings grant insight into the experience of learning from crisis response efforts, responding to recent calls for social scientific work on COVID-19 responses.

A Preoperative Risk Model for Postoperative Pneumonia After Coronary Artery Bypass Grafting.

BACKGROUND: Postoperative pneumonia is the most prevalent of all hospital-acquired infections after isolated coronary artery bypass graft surgery (CABG). Accurate prediction of a patient's risk of this morbid complication is hindered by its low relative incidence. In an effort to support clinical decision making and quality improvement, we developed a preoperative prediction model for postoperative pneumonia after CABG. METHODS: We undertook an observational study of 16,084 patients undergoing CABG between the third quarter of 2011 and the second quarter of 2014 across 33 institutions participating in the Michigan Society of Thoracic and Cardiovascular Surgeons Quality Collaborative. Variables related to patient demographics, medical history, admission status, comorbid disease, cardiac anatomy, and the institution performing the procedure were investigated. Logistic regression through forward stepwise selection (p < 0.05 threshold) was utilized to develop a risk prediction model for estimating the occurrence of pneumonia. Traditional methods were used to assess the model's performance. RESULTS: Postoperative pneumonia occurred in 3.30% of patients. Multivariable analysis identified 17 preoperative factors, including demographics, laboratory values, comorbid disease, pulmonary and cardiac function, and operative status. The final model significantly predicted the occurrence of pneumonia, and performed well (C-statistic: 0.74). These findings were confirmed through sensitivity analyses by center and clinically important subgroups. CONCLUSIONS: We identified 17 readily obtainable preoperative variables associated with postoperative pneumonia. This model may be used to provide individualized risk estimation and to identify opportunities to reduce a patient's preoperative risk of pneumonia through prehabilitation.