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Introduction Decision aids (DAs) are helpful instruments used to support shared decision making (SDM). Patients with atrial fibrillation (AF) face complex decisions regarding stroke prevention strategies. While a few DAs have been made for AF stroke prevention, an encounter DA (EDA) and patient DA (PDA) have not been created to be used in conjunction with each other before. Design Using iterative user-centered design, we developed 2 DAs for anticoagulation choice and stroke prevention in AF. Prototypes were created, and we elicited feedback from patients and experts via observations of encounters, usability testing, and semistructured interviews. Results User testing was done with 33 experts (in AF and SDM) and 51 patients from 6 institutions. The EDA and PDA underwent 1 and 4 major iterations, respectively. Major differences between the DAs included AF pathophysiology and a preparation to meet with the clinician in the PDA as well as different language throughout. Content areas included personalized stroke risk, differences between anticoagulants, and risks of bleeding. Based on user feedback, developers 1) addressed feelings of isolation with AF, 2) improved navigation options, 3) modified content and flow for users new to AF and those experienced with AF, 4) updated stroke risk pictographs, and 5) added structure to the preparation for decision making in the PDA. Limitations These DAs focus only on anticoagulation for stroke prevention and are online, which may limit participation for those less comfortable with technology. Conclusions Designing complementary DAs for use in tandem or separately is a new method to support SDM between patients and clinicians. Extensive user testing is essential to creating high-quality tools that best meet the needs of those using them. Highlights First-time complementary encounter and patient decision aids have been designed to work together or separately. User feedback led to greater structure and different experiences for patients naïve or experienced with anticoagulants in patient decision aids. Online tools allow for easier dissemination, use in telehealth visits, and updating as new evidence comes out.

Introduction: Since the 1999 Institute of Medicine report, hospitals have implemented a myriad of measures to protect patients from medical errors. At this point, looking beyond errors may bring additional safety benefits. This study aims to analyze predictors of in-hospital death regardless of underlying diagnoses in an effort to identify additional targets for improvement. Methods: We performed a retrospective study of hospitalizations from the 2016-2019 National Inpatient Sample (NIS) database. Logistic regression analyses were used to calculate adjusted odds ratios (OR) for variables associated with in-hospital death. Results: There were 121,026,484 adult hospital discharges in the database. Multivariable analysis showed the following variables were associated with higher in-hospital death: Age (OR, 1.04), Charlson Comorbidity Index (OR, 1.23), male (OR, 1.16), income Q1 (OR, 1.12), income Q2 (OR, 1.07), west region (OR, 1.07), non-elective admission (OR, 2.01), urban hospital location (OR, 1.17), and weekend admission (OR, 1.14). Percentage of deaths for weekend versus weekday admissions was 2.7% versus 2.1%. Fewer procedures (ICD-10-PCS) were done in first 24 hours of weekend admissions when compared to weekday admissions (34.8% vs 46.8%; p