Sara K. Pasquali

Background: While the representation of women in medicine has increased in recent years, advancement into leadership roles lags behind. Solutions often focus on providing women with leadership training, yet the experience of participants in such programs and ongoing barriers remain understudied. Methods: All women selected to participate in an 18-month institutional leadership program in medicine launched in 2014 and designed to support advancement to senior leadership roles were invited to complete an electronic survey regarding current barriers. Descriptive results from structured survey questions and free-text options are reported. Results: Of 114 participants, 67 responded (59%). Most (79%) were 15+ years from training and held a variety of mid-level leadership roles. Less than half reported that institutional leaders had proactively discussed advancement and future opportunities with them, including chairs (40%), divisional leadership (26%), hospital leaders (15%), and the dean’s office (15%). Nearly half (45%) had never applied for a higher-level leadership position. Of those who were offered such a role 56% turned it down, most often due to insufficient resources/compensation. Overall, the most common barriers to advancement reported were lack of sponsorship (67%) and mentorship (48%), implicit (61%) or overt (39%) bias, and a pre-determined candidate in mind (56%), with 48% also reporting challenges with personal/family responsibilities. Free-text responses highlighted similar themes to the quantitative data. Conclusions: This study of a unique cohort of mid-career women leaders suggests additional efforts beyond leadership training alone are needed to advance women in medicine to senior leadership roles. Our findings highlight current barriers and opportunities for future efforts focused on the organizational culture women are navigating including support for sponsorship and mentorship, addressing biases, and succession planning models.

Background:Hospitals are increasingly likely to implement clinical informatics tools to improve quality of care, necessitating rigorous approaches to evaluate effectiveness. We leveraged a multi-institutional data repository and applied causal inference methods to assess implementation of a commercial data visualization software in our pediatric cardiac intensive care unit. Methods:Natural experiment in the University of Michigan (UM) Cardiac Intensive Care Unit pre and postimplementation of data visualization software analyzed within the Pediatric Cardiac Critical Care Consortium clinical registry; we identified N=21 control hospitals that contributed contemporaneous registry data during the study period. We used the platform during multiple daily rounds to visualize clinical data trends. We evaluated outcomes-case-mix adjusted postoperative mortality, cardiac arrest and unplanned readmission rates, and postoperative length of stay-most likely impacted by this change. There were no quality improvement initiatives focused specifically on these outcomes nor any organizational changes at UM in either era. We performed a difference-in-differences analysis to compare changes in UM outcomes to those at control hospitals across the pre versus postimplementation eras. Results:We compared 1436 pre versus 779 postimplementation admissions at UM to 19 854 (pre) versus 14 160 (post) at controls. Admission characteristics were similar between eras. Postimplementation at UM we observed relative reductions in cardiac arrests among medical admissions, unplanned readmissions, and postoperative length of stay by -14%, -41%, and -18%, respectively. The difference-in-differences estimate for each outcome was statistically significant (P<0.05), suggesting the difference in outcomes at UM pre versus postimplementation is statistically significantly different from control hospitals during the same time. Conclusions:Clinical registries provide opportunities to thoroughly evaluate implementation of new informatics tools at single institutions. Borrowing strength from multi-institutional data and drawing ideas from causal inference, our analysis solidified greater belief in the effectiveness of this software across our institution.

As more adults survive with congenital heart disease, the need to better understand the long‐term complications, and comorbid disease will become increasingly important. Improved care and survival into the early and late adult years for all patients equitably requires accurate, timely, and comprehensive data to support research and quality‐based initiatives. National data collection in adult congenital heart disease will require a sound foundation emphasizing core ethical principles that acknowledge patient and clinician perspectives and promote national collaboration. In this document we examine these foundational principles and offer suggestions for developing an ethically responsible and inclusive framework for national ACHD data collection.

Background: Congenital heart disease practices and outcomes vary significantly across centers, including postoperative chest tube (CT) management, which may impact postoperative length of stay (LOS). We used collaborative learning methods to determine whether centers could adapt and safely implement best practices for CT management, resulting in reduced postoperative CT duration and LOS. Methods and Results: Nine pediatric heart centers partnered together through 2 learning networks. Patients undergoing 1 of 9 benchmark congenital heart operations were included. Baseline data were collected from June 2017 to June 2018, and intervention‐phase data were collected from July 2018 to December 2019. Collaborative learning methods included review of best practices from a model center, regular data feedback, and quality improvement coaching. Center teams adapted CT removal practices (eg, timing, volume criteria) from the model center to their local resources, practices, and setting. Postoperative CT duration in hours and LOS in days were analyzed using statistical process control methodology. Overall, 2309 patients were included. Patient characteristics did not differ between the study and intervention phases. Statistical process control analysis showed an aggregate 15.6% decrease in geometric mean CT duration (72.6 hours at baseline to 61.3 hours during intervention) and a 9.8% reduction in geometric mean LOS (9.2 days at baseline to 8.3 days during intervention). Adverse events did not increase when comparing the baseline and intervention phases: CT replacement (1.8% versus 2.0%, P =0.56) and readmission for pleural effusion (0.4% versus 0.5%, P =0.29). Conclusions: We successfully lowered postoperative CT duration and observed an associated reduction in LOS across 9 centers using collaborative learning methodology.

Background: Optimal strategies to improve national congenital heart surgery outcomes and reduce variability across hospitals remain unclear. Many policy and quality improvement efforts have focused primarily on higher-risk patients and mortality alone. Improving our understanding of both morbidity and mortality and current variation across the spectrum of complexity would better inform future efforts. Methods: Hospitals participating in the Society of Thoracic Surgeons Congenital Heart Surgery Database (2014–2017) were included. Case mix–adjusted operative mortality, major complications, and postoperative length of stay were evaluated using Bayesian models. Hospital variation was quantified by the interdecile ratio (IDR, upper versus lower 10%) and 95% credible intervals (CrIs). Stratified analyses were performed by risk group (Society of Thoracic Surgeons–European Association for Cardiothoracic Surgery [STAT] category) and simulations evaluated the potential impact of reductions in variation. Results: A total of 102 hospitals (n=84 407) were included, representing ≈85% of US congenital heart programs. STAT category 1 to 3 (lower risk) operations comprised 74% of cases. All outcomes varied significantly across hospitals: adjusted mortality by 3-fold (upper versus lower decile 5.0% versus 1.6%, IDR 3.1 [95% CrI 2.5–3.7]), mean length of stay by 1.8-fold (19.2 versus 10.5 days, IDR 1.8 [95% CrI 1.8–1.9]), and major complications by >3-fold (23.5% versus 7.0%, IDR 3.4 [95% CrI 3.0–3.8]). The degree of variation was similar or greater for low- versus high-risk cases across outcomes, eg, ≈3-fold mortality variation across hospitals for STAT 1 to 3 (IDR 3.0 [95% CrI 2.1–4.2]) and STAT 4 or 5 (IDR 3.1 [95% CrI 2.4–3.9]) cases. High-volume hospitals had less variability across outcomes and risk categories. Simulations suggested potential reductions in deaths (n=282), major complications (n=1539), and length of stay (101 183 days) over the 4-year study period if all hospitals were to perform at the current median or better, with 37% to 60% of the improvement related to the STAT 1 to 3 (lower risk) group across outcomes. Conclusions: We demonstrate significant hospital variation in morbidity and mortality after congenital heart surgery. Contrary to traditional thinking, a substantial portion of potential improvements that could be realized on a national scale were related to variability among lower-risk cases. These findings suggest modifications to our current approaches to optimize care and outcomes in this population are needed.